Goélia called on Dydu to deploy a chatbot for its customers on its website. Clara Labrune, Quality & Guest Experience Director, looks back at the implementation of this project and future developments. 

Can you describe your company and your role?

Goélia is a family-run vacation resort business founded in 2001. We manage more than 70 3* and 4* resorts in France and market other partner resorts (as a travel agency) in France and abroad (Italy, Spain, and Portugal). 

I am currently the Quality & Guest Experience Director. My role is to ensure that our guests are satisfied by:

• carrying out quality control visits and improvements/renovations at our resorts
• continually monitoring our online reputation, including our guests’ feedback before, during, and after their stay

What challenge(s) did you want to address by implementing a bot?

We were getting a lot of customer inquiries via various channels: phone calls, emails, and social media. Most of the requests were simple questions that could have been answered by searching our website. We wanted to provide a simple and easy solution so that we could respond quickly to customer queries and spend more qualitative time on complex information requests. 

Why did you choose Dydu?

We conducted market research and met several companies specializing in chatbot creation, including some in tourism. Although none of Dydu’s clients are in tourist accommodation, the solution, price, and good connection with the sales rep convinced us to move forward.

Can you describe your solution?

We’ve implemented a chatbot on our website (B2C) to guide our customers and answer questions to simplify the booking process.

How many people manage the chatbot internally, and what do they do?

4 people manage the chatbot internally:

• Two people from the quality and guest experience department: bot management, knowledge base updates, reading dialogs, and statistics analysis   
• One person from the booking office who reads the dialogs and actively responds to any special requests (e.g., invoice requests, booking changes or cancellations, etc.)
• One project manager who informs our website provider of any problems with the chatbot or developments

How did you communicate about your chatbot internally and externally?

Internally, our employees were delighted to hear that we were implementing a chatbot. We asked for their help to test our knowledge articles before launching the bot on our site. They liked to be involved.

Externally, we communicated about this new feature via social media to raise awareness and encourage customers to use it.

How did you build your knowledge base?

We used the FAQ page on our website and spoke to employees from various departments (call center, community manager, resorts) to determine the most frequently asked questions. We then looked at the chatbot dialogs and questions we hadn’t thought of to enrich our knowledge base.

What are the main features you use?

Our chatbot includes various features:

• Top knowledge
• Decision trees for some of our knowledge articles
• A side panel to provide additional information

Which KPIs do you monitor to manage your bot’s activity, and what benefits have you observed since implementing the solution?

We carefully monitor customer requests via phone calls, emails, and social media. The number of queries has decreased:

• up to 83% less direct messages on social media 
• up to 45% fewer calls to our call center

The requests are also more qualitative, enabling our call center to spend more time advising customers and helping them book a vacation. Our community manager has been able to take on additional tasks since they are spending less time giving advice. 

What are the main benefits for end-users?

Our customers have access to instant answers to simple questions 24/7. Our website user experience and booking process are more seamless. Customers no longer need to wait for someone to answer their email or call to find out when to pay their booking balance or how to connect to their account online, for example. Implementing a chatbot on our website has benefitted our customer satisfaction. 

Do you think the project is a success?

The project is a success because it has improved our customer relationship and the quality of work for various teams at our head office.

What developments and updates are you planning to improve the bot and encourage its use?

We’re developing an API to personalize our customer responses even more (resort-specific information) and avoid generic answers.

The French public procurement agency UGAP (Union des Groupements d’Achats Publics) called on Dydu to deploy a conversational bot for its clients. It has racked up more than 1.8 million visitors since its launch and boasts a 95% interaction qualification rate.

Achylle EBELE, assistant director of the multi-channel contact center, discusses this success in an interview for Dydu’s Client Focus.

UGAP is the only “generalist” public procurement agency in France. It provides access to more than 1.4 million products in over 3,500 markets. Its clients include public bodies (ministries, local authorities, hospitals, etc.) and public service institutions.

Customer relations at the heart of UGAP’s strategy

UGAP recorded 5.6 million orders in 2022 and has made customer relations a priority by implementing:

• a regional sales network (25 regional offices) to be as close as possible to its clients
• an online sales site: UGAP.fr (more than 5 million visits/year)
• a multi-channel contact center (200,000 calls/year)

These three entry points provide clients with a wide choice of access to the company’s products and services.

The multi-channel contact center, created in 2011, provides simple answers to a range of queries within a short timeframe. UGAP set two objectives to achieve high satisfaction levels:

• 90% pick-up rate
• 90% next-day resolution rate

Digitalizing the customer relationship

UGAP wanted to provide its clients with a more innovative and digital experience. The aim was to offer a simplified user journey, with ever shorter response times to simple, recurring questions. So, the company turned to conversational AI solutions.

The Dydu chatbot was officially launched in February 2022 on the UGAP.fr website. We installed an API to enable the bot to inform clients in real time of their order delivery status. The tool reduces the number of requests and increases satisfaction with a shorter response time.

The bot recorded more than 16,000 interactions in the first year. Clients use it primarily to request information about products, despite the fact that the website includes a FAQ section.

Both channels have recorded more than 45,000 interactions to date. The sharp increase in the number of users has led to new challenges for the company.

Given the use of the bot and the large number of user questions, UGAP decided to implement MailJet.
This tool retrieves complex client requests and e-mails them to the multi-channel contact center. The support team then contacts the client once the request has been processed.

This solution is the first step before implementing a live chat system, which will increase customer support.

TotalEnergies is the 3rd largest electricity and gas provider in France. It provides electricity and natural gas to more than 5 million consumers and businesses, as well as innovative services to optimize their consumption. Innovation and customer satisfaction are at the heart of the company’s strategy.

After launching a live chat service in 2014, TotalEnergies wanted to further innovate its customer experience. The aim was to be available 24/7 while relieving its support teams who were overwhelmed with requests.

In order to meet these new challenges, we helped TotalEnergies implement a conversational chatbot for consumers that redirects users.

This conversational agent now has 300 knowledge articles and generates more than 2,500 conversations per day, thus automating tier 1 customer service requests.

In an interview for Dydu’s Client Focus, François Rémuhs, Tier 1 Customer Service Activities Manager at TotalEnergies, looks back at this success. He discusses the company’s initial challenges, the project implementation, results and next steps.

Download our client case study to find out more about TotalEnergies’ customer support chatbot and its key figures:

TotalEnergies is the 3rd largest electricity and gas provider in France. It provides electricity and natural gas to more than 5 million consumers and businesses, as well as innovative services to optimize their consumption. Innovation and customer satisfaction are at the heart of the company’s strategy.

After launching a live chat service in 2014, TotalEnergies wanted to further innovate its customer experience. The aim was to be available 24/7 while relieving its support teams who were overwhelmed with requests.

In order to meet these new challenges, we helped TotalEnergies implement a conversational and redirectional chatbot for individual customers.

This conversational agent now has 300 knowledge articles and generates more than 2,500 conversations per day, thus automating tier 1 customer service requests.

In an interview for Dydu’s Client Focus, François Rémuhs, Tier 1 Customer Service Activities Manager at TotalEnergies, looks back at this success. He discusses the company’s initial challenges, the project implementation, results and next steps.

Download our client case study to find out more about TotalEnergies’ customer support chatbot and its key figures:

The car manufacturer Renault called on Dydu to deploy an internal conversational bot for its salespeople and sales managers. Stéphanie Lecomte, Head of Digital Transformation and Sales Tools, looks back at the implementation of the chatbot and shares the next steps for the future.

Can you describe your company and your role?

My name is Stéphanie Lecomte. I’m the Head of Digital Transformation and Sales Tools. I’m in charge of all the sales and CRM tools and the digital transformation of our network (e.g., highlighting the network stock on our website or booking test drives online).

What are your current IT support challenges, and what issues did you want to address by implementing a chatbot?

We wanted to address cost and availability issues.

We wanted to end phone support while maintaining a high level of support for our salespeople. Chatbots are efficient solutions that cost less than phone assistance.

Chatbots are also available 24/7, whereas our call center was only available during working hours.

Before we set up our chatbot Maeva, we couldn’t help our salespeople on open days because they mainly take place on weekends.

We implemented the chatbot for Renault and its network in France, which includes around 370 businesses and 5,000 users (4,000 salespeople and 1,000 managers).

Why did you choose Dydu?

We’ve been working with Dydu on our internal HR chatbot for several years. We’re very pleased with it, and it meets all our expectations. So, when the IT team wanted to set up a support chatbot, we naturally turned to Dydu.

What scope does your chatbot cover?

Our chatbot, Move Maeva, assists our salespeople and sales managers. It handles tier 1 issues relating to their sales positions or CRM tools.

How many people manage the chatbot internally, and what do they do? (bot administration, updating the knowledge base, monitoring dialogs, analytics, etc.)

We have a team of 6 people managing the chatbot, each specializing in a different area.

We organize reading workshops once a month to analyze the chatbot’s dialogs and improve our knowledge base.

How did you build your knowledge base?

To get started, we used an Excel file that was created during our sales and CRM tools audit.

We then added any questions raised by our pilot group of salespeople to build up the new chatbot’s knowledge base.

Since rolling out the chatbot, we’ve continued to manage and update the knowledge base.

Which features do you use the most?

We connected our chatbot, Move Maeva, to our ticketing tool.

Maeva can answer users’ tier 1 questions directly. If users have a tier 2 or 3 problems, the bot automatically offers to create a ticket so that they can get the assistance they need.

Which KPIs do you monitor to manage your bot’s activity?

We analyze the following KPIs to manage our chatbot’s activity:

• number of dialogs
• salespeople’s satisfaction rate
• number of tickets created via the chatbot
• qualification of dialogs (which allows us to check that the chatbot is answering the questions correctly) 

What benefits have you observed since implementing the solution?

We’re able to monitor incidents more closely with the creation of tickets via the bot.

Before implementing the chatbot, we used several different channels (emails, tickets, and phone calls), so we weren’t able to follow up on our sellers’ requests properly.

Do you think the project is a success? Why?

We think that the project is well on its way to being a success. Our support teams already appreciate it, as do the salespeople who have used it. We’re now trying to encourage our sales network to use it more, with a video to promote the chatbot and introduce the team that manages it. We’re confident that the bot’s success will continue to grow. 

What developments and updates are you planning to improve the bot and encourage its use?

To improve our user experience, we’re thinking about adding an option to enable users to attach a file when they create a ticket via the chatbot. This feature is part of the Dydu roadmap and will give us all the information we need to solve our users’ problems. We’re also thinking about adding the dialog history to our tickets.

Finally, we’d like to set up an internal organization that involves training our teams and implementing a live chat via the chatbot so that we can provide employees with tier 2 support.

Bpifrance, the French public investment bank for entrepreneurs, wanted to relieve its IT support team while continuing to provide employees with a high level of service.

As part of its modernization and digitalization process, the company implemented an IT chatbot to handle the top 20 recurring requests from employees.

Every month, the chatbot handles more than 1600 questions related to applications and hardware: in addition to getting personalized answers, users can use the chatbot to create incident tickets or switch to a livechat operator if necessary. 

Find out how Dydu’s conversational agents help Bpifrance optimize employee relations management. 

TotalEnergies, the 3rd largest electricity and gas provider in France, has implemented a comprehensive and efficient self-care tool for customers combining conversational AI and livechat technology.

With innovation and customer satisfaction at the center of its strategy, TotalEnergies wanted to provide 24/7 assistance for its customers while optimizing the way incoming contacts were handled.

With more than 77,000 conversations per month, the TotalEnergies chatbot automates 40% of incoming enquiries : it provides customers with personalized answers and lets them switch to a livechat for cases requiring an agent’s intervention.

Find out how Dydu’s conversational agents became a key aspect of customer relations management at TotalEnergies. 

Bpifrance, a French bank, called on Dydu to deploy a conversational IT bot for employees. Hugo Parlier, ITSM and Chatbot Product Owner, looks back at the chatbot’s implementation and shares plans for future developments.

Can you describe Bpifrance and your role?

Bpifrance is a bank for entrepreneurs. We support companies at every stage of their development. We help them with financing, guarantees, innovation projects, exporting products, international expansion, etc. We also offer training, coaching, and support services.

I’m Hugo Parlier, ITSM and Chatbot Product Owner. I work in the IT department, made up of almost 1,000 people, to meet the needs of Bpifrance’s 5,600 users.

What are the current IT support challenges at BPI?

For the past 2 years, we’ve been in the process of modernising and digitalising the
IT department to provide Bpifrance employees with new tools.

What issues does your chatbot address?

Our tier 1 internal support team, dealing with incidents and requests, was under a lot of pressure, so we had to find new ways to communicate. We wanted to keep the same level of support while providing greater flexibility. A lot of our users were encountering the same problems and we thought that a chatbot could solve this issue. We analysed the top 20 recurring incidents. Our support team already had the knowledge to deal with these topics, which we then adapted to the chatbot.

Take VPN, for example. We regularly get requests for help with this complex technology, especially since the first lockdown. The chatbot has made it easy to provide users with a solution and to help them solve problems by themselves.

The same applies to authorisation requests and access rights management. We integrated a dynamic list that enables users to identify their IT correspondents and contact them directly, without going via the support team. OID (OpenID Connect, an open authentication protocol) also allows us to identify users and personalise the chatbot’s answers.

Why did you choose Dydu?

We benchmarked all the tools on the market and reviewed the existing editors. Dydu stood out for its innovation: its chatbox, integration with Teams, and, more generally, its roadmap. Dydu also hosts data in France and has a competitive offer. Since we use Teams as a collaboration platform at Bpifrance, it makes sense to integrate the chatbot into the tool, so that users always use the same interface. We’re currently working on implementing authentication in Teams.

What scope does your chatbot cover?

Alfred, our IT chatbot, covers user questions and requests related to apps and IT equipment within Bpifrance. We’ve also connected our chatbot to EasyVista, our IT ticketing tool. The chatbot can therefore provide users with tier 1 support for any computer or app problems and create an incident ticket.

How many people manage the chatbot internally and what do they do?

Three people currently manage the bot, including a tier 1 support staff member from my team. The tier 1 support team helped to integrate the chatbot and qualify its knowledge articles. Today, the support team adds and manages knowledge independently. We assist with any technical problems or to implement new developments (e.g. APIs, etc.).

We’re currently deploying a new chatbot for the short-term financing team, to assist all our salespeople in France. We’re helping the team deploy and train their chatbot until they can manage the knowledge by themselves.

After we’ve deployed 3 or 4 chatbots, we plan on reorganising our chatbot team to provide the best possible support and guidance.

How did you build your knowledge base?

The knowledge bases for our IT chatbot and sales chatbot, which is currently in production, already existed. We helped the bot managers with the syntax of their answers and showed them how to use the different features so that they can integrate the knowledge base as soon as the chatbot is deployed.

Which features do you use the most?

The features we use most are the decision trees, side panel, top knowledge, and carousel.

We use the features proactively wherever possible. For example, we’ve added an app status overview to the side panel, using an API, which also informs users of any incidents. This means that users don’t need to create incident support tickets. We also use the chatbot to highlight important information.

Which KPIs do you monitor to manage the bot’s activity?

We support the business teams by monitoring the following KPIs on a weekly and monthly basis:

• Number of dialogues (between 250 and 300 per month)
• Number of interactions
• Dialogue qualification rate
• Accuracy rate
• User rating
• Number of incidents opened via the chatbot (approx. twenty per month)

Bpifrance has an IT portal that users can use to report the same type of incidents as on the chatbot. We’ve found that users still tend to use this portal out of habit. The integration of the chatbot into Teams should resolve this issue and significantly increase the statistics. We also always check that users are satisfied.

What benefits have you observed since implementing the solution?

Our IT chatbot was officially deployed in July 2021. The project is currently in a stabilisation phase. We want to tailor it to users’ needs. It’s difficult to put a number on what we’ve gained regarding the support team’s workload. But we’ve noticed within the IT department that employees use the chatbot more for major incidents, like when a VPN is down. We instantly see a spike in the chatbot’s use, which takes some of the pressure off our internal support teams.

Do you consider the project to be a success? Why?

Overall, employees at Bpifrance are very positive about the chatbot. Users are increasingly aware of the value of getting answers immediately, rather than waiting for support to become available.

I think that the more conversations employees have with the chatbot, the more it will become a part of their day-to-day life and impact their way of working. This transformation has only just begun. When we deployed the chatbot, we carried out an internal communication campaign to raise awareness, but we believe this should happen naturally, through word-of-mouth. We also have change management teams working on the bots. Many users are used to working a certain way, so it will take time for the chatbot to become part of all the employees’ daily lives.

Some of the conversations take place outside office hours, which provides more flexible support.

How do you plan on improving the bot and encouraging its use?

This year, we will deploy 2 chatbots, one for our short-term financing department, which will cover a legal and sales scope, and another for HR. Then, we’ll launch a larger communication campaign within Bpifrance to encourage employees to use them. We want to continue to deploy Teams and to set up a live chat to better meet employee needs. We firmly believe that robots and humans can work together.

Do you have any anecdotes about the deployment of your IT chatbot?

We called our IT bot “Alfred”, after Batman’s butler, so that users would view it as their butler. When we deployed Alfred, we noticed that the question “who are you?” came up a lot, so we decided to create a knowledge article to introduce the bot to users. Alfred has his own avatar, and today IT and other departments think of him as an employee in his own right.

In the long term, we’d like to widen the chatbot’s scope beyond IT.

The French Development Agency – Agence Française de Développement (AFD) – called on Dydu to deploy two HR conversational robots within their company: an internal chatbot for AFD employees, and a recruitment chatbot for applicants. Meng-Han Chiang, Head of HR Digital Transformation at AFD, looks back at the implementation of these two chatbot projects.

Can you describe AFD and your role?

The Agence Française de Développement (AFD) funds, supports and accelerates the transition towards a fairer and more sustainable world. Climate, biodiversity, peace, education, urbanism, health, governance… Our teams carry out over 4,000 projects in the French Overseas Territories and 115 countries. We contribute to the commitment of France and French people to the Sustainable Development Goals (SDG).

AFD has a network of 85 branches and 17 regional directorates in the world. We have more than 2,600 employees and 80 different nationalities in 5 continents.

I am Meng-Han Chiang, Head of HR Digital Transformation at AFD. We conduct digital HR projects.

What problems were you trying to solve by implementing a HR chatbot and a recruitment chatbot?

We noticed that employees were asking our HR managers a lot of recurring questions, to which they were providing the same answers. We wanted to provide a tool that could answer simple and recurring questions, to help my colleagues focusing on specific cases. Our 85 branches operate in different time zones, so it was important to opt for a tool that was available 24/7.

How did the project come about?

We began to look into chatbots in 2018, the year I joined AFD. At the time, AFD’s innovation hub was launching an entrepreneurial programme which enabled us to push new projects and test our ideas on employees. We put together a small HR team to take part in the programme’s first edition. We tested different tools on user groups, such as interactive FAQs and chatbots. Following these tests, we realised that chatbots were better suited to our needs. Our executive committee then approved the project for a pilot phase. After conducting several POCs with different editors, we decided to launch our chatbot projects with Dydu.

What were the different chatbot implementation stages?

We started with the recruitment chatbot. Recruitment was our primary focus because there was a limited number of recurring questions, and we could cover a fairly large population. We receive 3,000 applications per month, so we wanted to improve our employer brand through the chatbot, and to use this digital tool as a lever for social interaction. For example, our chatbot shares job videos on applicants to promote careers at AFD.

The HR department’s scope is very wide, so we defined themes for the internal chatbot, according to the different HR areas of expertise. We first worked on appraisal interviews, for which our HR policy is the same for all employees. We then addressed internal mobility and training.

We launched both chatbots in October 2020. The recruitment chatbot on AFD’s careers site and the HR chatbot on our 3 HRIS tools: career management, training and e-training. We communicated on the launch of our internal bot with infographics and chatbot presentation videos via our HR newsletter.

Why did you choose Dydu?

We met several chatbot builders and chose Dydu because the solution offered the most advanced features. In particular analytics, anonymous dialogues and the possibility of creating decision trees allow us to provide an answer according to the employee’s situation.

With Dydu, we can manage two separate chatbots in one environment. In the Dydu back office, I can manage our recruitment chatbot’s knowledge articles, dialogues and analytics internally. The other editors did not offer this type of all-in-one functionality.

What do you want to achieve?

With this chatbot project, we want to make information easily accessible to everyone, lighten our HR management teams’ workload and strengthen AFD’s employer brand.

We set ourselves goals and indicators to reach within 1 year:

• Identify the most popular 20% of knowledge articles in each HR field to answer 80% of recurring questions.
• Provide information at the right time.
• Free up time for our HR teams, so that they can focus on more added-value tasks.
• Achieve an 80% user satisfaction rate with the answers provided by the bot.

Overall, we have achieved these goals. We are continuing to feed the bot and hope that it will free up time for HR employees in the long run, when it has become an expert on all HR topics and deployed on all our HRIS platforms.

What benefits have you seen since implementing the solution?

Since implementing our recruitment chatbot, we can answer most applicants’ questions, whereas we struggled to do so without the tool. We can only gain from this new service. It also helps develop our employer brand. Our recruitment chatbot has 1,200 dialogues per month with a 96% qualification rate of interactions. A lot of our dialogues, therefore, have an excellent accuracy rate, and we are delighted.

Our internal chatbot is also a new internal support service. There are on average 200 dialogues per month, with an 86% accuracy rate. The questions are logically tied to major HR events, such as appraisals, internal mobility, etc. The rest of the year, the questions are often about training.

How do you manage the project?

Today, in run mode, I’m the only chatbot administrator. I spend an hour per week reading the dialogues to identify any trends (it’s an excellent tool to know what is preoccupying employees), improve the bots’ understanding and identify any new knowledge articles to create. Once every two months, we have a meeting with experts from our different HR teams to review the most frequently asked questions. We then decide together if we need to create a new knowledge article and which ones to highlight in the Top 3.

Which KPIs do you monitor to manage the bot’s activity?

We monitor several indicators in the Dydu back office:

• Number of visitors per month
• Percentage of visitors with a dialogue
• Number of dialogues per month
• Qualification rate per interaction
• Number of knowledge articles that cover 80% of user questions
• Customer satisfaction for the knowledge articles highlighted in the Top 3. If satisfaction is not sufficient (below 80%), we try to improve the knowledge article’s phrasing and add additional information to our answers.
• Contact channel: this allows us to know which tools applicants use to communicate with the recruitment bot (Windows, Android, iPhone, or Mac) and to improve our user experience.
• Platforms of use: this allows us to know which HRIS platforms employees use to interact with the internal HR bot.

I check these indicators regularly and share them with our HR experts during our steering committee.

What prospects or developments do you have planned for the project?

We plan on deploying the internal chatbot on other HR platforms and to integrate all HR knowledge. We also want to translate the knowledge base into English and possibly Spanish. With regards to translation, we will identify the most used knowledge articles and focus on them first.

Our IT department has also provided support from the start of this adventure and is very interested in the potential of a conversational robot.

In 2019, PwC France, one of the Big 4 specialising in consulting, audit and legal services, called on Dydu to create Alex, a “concierge” chatbot for its 6,000 employees.

KEY FIGURES

• 2,800 knowledge articles around 10 subjects
• 15,000 interactions per month with a 97% comprehension rate
• 4,000 dialogues per month, of which ​​85% are successful

[Only in french]

PwC’s Human Resources chatbot currently includes 2,800 knowledge articles, based on ten recurring subject areas (Human Resources, HelpDesk, work premises, events, corporate strategy, etc.). With 15,000 questions per month and a comprehension level of 97%, the chatbot has become a strategic tool for PwC’s internal support management. It simplifies employees’ working life and helps to onboard new recruits.

During our client meeting in March 2022, Nelly Fercoq, the PwC chatbot project manager, revealed that the chatbot had been particularly useful when implementing remote working for everyone. PwC recorded a 4% increase in the number of chatbot requests.

The tool’s managing team regularly promotes the bot. They also work continuously on improving and updating its knowledge base. “We read the conversations every day. This enables us to see the sentences that haven’t been understood correctly or any little bugs, so that we can correct them and continuously improve the bot. We add phrases and we create knowledge articles in accordance with current events. Any that are no longer relevant are deleted,” Nelly Fercoq explained.

PwC is planning on interconnecting the bot with their HRIS to perform more transactional tasks, such as checking an employees’ leave balance or requesting leave via the bot. They also want to deploy the chatbot on more internal channels, such as Teams.

SNCF Connect and Dydu have been working together for more than 10 years. The first chatbot, created at the time of Voyages SNCF, took the form of a Helpbox available on the website and passenger app.

KEY FIGURES:

• 10 million questions handled by the bot in 2021
• 6 languages available
• 5 times more requests made to the SNCF Connect bot since its launch and the merging of all SNCF bots
• 95% of questions asked to the bot have been answered since the migration

In addition to the Helpbox, SNCF Connect deployed their own bot in 2017, Oui Bot, which answered travellers’ questions about buying and booking tickets.

In anticipation of the OUI.sncf website migration to SNCF Connect, they decided to use one chatbot instead of two. “We wanted an easily identifiable assistant everywhere, all the time. We also wanted to end the OUI Bot (SNCF bot) / Helpbox (Dydu bot) split, so that customers would only see one bot,” Franck Gbenou, Head of Passenger Information and Customer Support at SNCF Connect, commented. The aim was therefore to make the customer experience smoother and more efficient, without losing the richness of what had already been put in place with Dydu.

Today, with the merging of the two bots, the SNCF bot routes requests with the Dydu API, depending on the user’s question:

• The SNCF bot handles transactional or booking queries.
• The Dydu bot handles customer support and follow-up requests.
• If the question is not covered by the SNCF or Dydu knowledge base, the Dydu bot answers.

SNCF Connect has therefore succeeded in interfacing these technologies in a smooth and intelligent manner with a single dialogue box, and the possibility of switching to an operator via live chat.

Thanks to a more integrated and visible journey, the number of bot requests has been multiplied by five since the merging of the two.

Read all our client testimonials.

AFD, the French Development Agency, who funds social and environmental impact projects, wanted to leverage conversational AI to modernize its employer brand and become more efficient.

For AFD’s HR digital transformation unit, the purpose of the project was twofold: first, to provide better support for employees on HR topics, and second, to offer assistance to future talent in the application process.

The two Dydu chatbots implemented now handle over 40,000 questions every month, thus relieving the HR department of recurring requests – a resounding success for the team !

Find out how Dydu’s conversational agents became a key aspect of employee relations management at AFD. 

PwC France and Maghreb called on dydu in 2018 to create Alex, a conversational robot for employees. Nelly Fercoq, a chatbot project manager at PwC France and Maghreb, looks back at the implementation of the project.

• Can you describe your company and department ?

PwC provides consulting, auditing, and legal and tax expertise, with the strategic ambition of reconciling businesses, the economy and society. 6,000 employees currently work for PwC in France and North Africa.

I’ve been a member of the IT department for 13 years and have been a chatbot project manager for the last two. I’m responsible for managing and developing the chatbot with another colleague, who is in charge of the knowledge base, reviewing the dialogues and monitoring the analytics and KPIs.

Problems and solutions

• What problems does the implementation of a concierge chatbot seek to solve ?

Our project was born after interviewing a sample of employees. Our goal was to identify any obstacles in their day-to-day life. This survey revealed in particular that the intranet was seen as dense and complex, and that it was difficult to carry out a search.

We also wanted to help newcomers become autonomous more quickly. Indeed, nearly 2,000 new employees join us each year. The chatbot enables them to understand our whole ecosystem in a simple and quick manner.

To make everyday life easier for employees and to facilitate the onboarding of new recruits, we wanted to implement a tool that could instantly answer all their questions. We decided to deploy an internal chatbot and the project began as a pilot with a handful of employees. We started to feed the bot with knowledge from our intranet. We then launched it throughout the organisation in January 2019.

Project implementation

• What scope and use cases does your chatbot cover ?

The chatbot is internal. It acts as a concierge and helps employees with various day-to-day issues: HR, IT, office space, events, corporate strategy, etc. For example, it can provide information about how to access payslips, fill out expense reports, request leave, etc. The topics vary but the questions mainly relate to HR and IT.

• What channels is the chatbot available on ?

The chatbot can be accessed on the internet via an icon on our home page. It is also installed directly on desktops and mobile phones with a web app.

• What were the different project implementation stages ?

Design – We ran workshops with representatives from each department, with a mix of junior, experienced and senior profiles. We asked them to ask any questions they wanted a quick and clear answer for. This helped us determine which themes to include and the content to create. We also conducted an employee survey to choose the bot’s name; Alex was the most popular of 4 choices.

Building the Knowledge Base – Based on the questions we identified, we collected the official answers from the department representatives. There were 15 of them, divided up by theme. We built a first list of knowledge articles with their answers.

Launch – We communicated a lot when we launched the bot, using all of our internal communication platforms: internal newsletter, cafeteria screens on every level, annual convention, etc. We also presented the solution via a stand during our innovation days, and we always present the chatbot to newcomers during our onboarding programme.

Updates – The number of questions asked is gradually increasing. We add new knowledge articles to a Google Sheet, along with our department representatives. We hold regular calls to clean the knowledge base by deleting or updating any obsolete articles. Every month, we look at the most asked questions with the representatives. My team centralises everything and carries out any updates in the bot management system (BMS) for all the department reps.

• How did the dydu teams support you in setting up and monitoring the project ?

We assessed various existing solutions. In the end, we chose dydu because of the quality of the BMS, that can be used with many functions by a non-developer, the transparency of pricing, client references and the possibility for on premise of SaaS hosting.

During the implementation phase, dydu’s teams trained us to use the BMS. The aim was to become as autonomous as possible to build knowledge articles and use important functionalities, such as decision trees and variables.

Today, we are fully autonomous. We do however still benefit from dydu support and we have a dedicated customer success manager (CSM) for any questions, update requests or bugs. I’ve had three contacts at dydu since I started working on this project, and I’ve always found them quick to respond. They’re always ready to solve problems and find workarounds when on very short deadlines.

Benefits and good practices

• What benefits have you seen since implementing the solution ?

When we all began working remotely full time, bot requests increased by 4%. Employees broached new topics as a result of the crisis, which brought about several changes: adjusted working hours for some departments, curfew, guidelines for coming on site, etc.

We updated or adapted a lot of knowledge articles to the situation. We added answers to questions such as, “Who is the Covid rep?”, “How can I get psychological support during the health crisis?”, “Where can I find a permission form if I have to travel for business reasons during curfew?”, or “What are useful Coronavirus contacts?”.

We try to guide our employees as best as possible, so that they can easily find answers during these difficult times. Since the beginning of the year, there are on average 4,000 dialogues per month, with more than 15,500 interactions. More than 300 knowledge articles are used, 136 of which represent 80% of the bot use.

• Which KPIs do you monitor to steer the bot’s activity ?

We look at the number of dialogues and the number of visitors per day to ensure that employees are still using the bot. When these numbers go down, we communicate about the bot again. We also check the satisfaction rate and review the dialogues between the bot and employees on a daily basis, to make any necessary corrections. We carefully monitor all the KPIs and check the themes to understand employee concerns.

Today, we consider that we have reached our goal. The bot is used regularly, and the satisfaction rate is high. As for any innovative tool, we regularly interview a sample of around 100 employees with different profiles. This enables us to check that our tools still meet their expectations and to identify any new needs.

• What advice or good practices do you have about the relevance , use and management of the bot ?

If the chatbot cannot answer an employee’s questions several times, they are unlikely to return. I therefore recommend having all the necessary resources internally, to offer the best possible service. This involves reading the dialogues, adding matches, and creating new knowledge articles. We pay particular attention to the quality of the answers we provide, to ensure that they are precise and current.

Alex also has its own email address. We make a note of the name of any employees with unanswered questions and reply a little later by email. This is particularly appreciated internally.

• Why would you recommend the dydu solution ?

Using the BMS to add knowledge articles is very clear. The tool is easy to use because it is very intuitive. Everything is simple, clear, and quick for end-users too. All our contacts are accessible and friendly. Our CSM is very responsive. We know that we can contact her if we have a problem. Dydu immediately takes our issues on board and finds a solution. I also really appreciated the exchange workshops with other dydu clients about developments we would like to see for the software; very few publishers do this.

Next steps …

• What prospects or developments do you have planned for the projetc ?

The next step will be to interface the chatbot with some of our HR tools so that it can provide fully personalised answers. The chatbot is already connected to our authentication system, which means Alex can address employees by their first name. We’re also working on personalising the answers according to the employee’s site location, ranking and service line.

Harmonie Mutuelle deployed a chatbot in 2017 to help its employees navigate the company’s digital environment. Marc Pasquet, Head of User Support Manager, and Bruno Walter, User Support Project Manager, look back at the implementation of this conversational robot and its benefits.

To download a PDF of the client case study, click here.

• Can you describe your company and department in a few words?

Harmonie Mutuelle is a health and life insurance company. We are part of the user support department, which handles and resolves employee incidents with the digital environment and escalates them to a specialist team, if necessary.

Problem(s) and Solution(s)

• What tools are available for managing employee IT requests?

ITSM EasyVista is an end-to-end tool that handles incidents and requests, entered directly by employees or support teams following a telephone or email exchange.

What problem(s) are you looking to solve by implementing a Chatbot?

Our main reasons for deploying a chatbot were to answer questions at any time, encourage employee autonomy and reduce the support teams’ workload. Simple requests entered into the chatbot are sent directly to the competent team, along with all any information required. This allows to bypass the first level of support to qualify the request, making the process faster and less resource-consuming.

The chatbot and its services are currently available for Harmonie Mutuelle’s internal employees and contractors, which represents about 6,000 people.

The Project

• What is the chatbot’s scope?

The chatbot primarily focuses on our digital environment, access to applications, printing services, videoconference procedures, etc. It frequently refers users to documents or pages on the Intranet. The chatbot can also open a user file, such as for password reset requests.

• How many people manage the chatbot internally and what do they do?

The knowledge base is currently administered by two people (IT knowledge scope) half a day per week, with certain periods requiring more or less responsiveness.

Can the chatbot escalate issues to specialist teams?

Yes, the chatbot creates and escalates tickets to the right support team, the Webservice we use is recognised by the ITSM tool and routed accordingly.

• What major changes have been made to the bot since its implementation?

The first version of the chatbot answered simple questions about our digital environment. The second one allowed requests and incidents to be sent directly via Webservices to the ITSM tool and specialised support teams. The chatbot currently has 480 knowledge articles, 55 of which represent 80% of the questions asked.

• What are its main functionalities?

We mainly use decision trees, data retrieval in the form of variables and webservice.

Benefits

• What benefits have you seen since implementing the solution?

Implementing the chatbot has enabled us to offer users an additional service, available 24/7, when the helpdesk is overwhelmed. The productivity gains (solutions provided by the chatbot without any helpdesk involvement) represent 8% less helpdesk requests, and up to 13.3% during the first lockdown.

Which KPIs do you monitor to steer the bot’s activity?

We use the following analytics: number of dialogues, number of interactions, quality of dialogues, most used knowledge articles, use of webservices (incidents and requests opened via the chatbot).  

• Do you consider this project to be a success? Why?

This project is a success because it fulfils the role it was set up for. The chatbot holds 500 dialogues per month on average (approximately 1,350 interactions), with an 80% comprehension rate. Now, we need to encourage even more people to use it. We need to take advantage of the opportunities for use with maximum benefit (simplicity and efficiency). We will also communicate more about the bot via video.

• Do you think the chatbot was even more useful during lockdown?

Yes, the chatbot was very useful during lockdown. It enabled us to answer a lot of user questions about remote working tools, as well as the usual requests, at a time when the helpdesk was under a lot of pressure.

 Why would you recommend the dydu solution?

The dydu solution allows to implement a quality chatbot that fits perfectly into your intranet or website, for example.

Next Steps

• Are you planning any changes or updates to further improve the chatbot? And the management of IT requests in general?

Enabling users to fill out forms in the chatbot to create more complex service requests via webservice. We also plan on making it possible to book appointments with the helpdesk via the chatbot.

Feel free to download a PDF of the client case study.

Dydu has signed three new accounts in the e-commerce, automotive and distribution industries.

Logista France

Strator has implemented a chatbot for tobacconists and newsagents using the dydu solution. Strator (part of Logista France) is the leader in POS terminals, tools dedicated to the sales and management of shopkeepers’ businesses. Their brand new chatbot answers retailers’ questions about how to use Strator: stock management, inventories, dematerialised products, dashboards, etc. They have deployed the chatbot on their online Help website, that can be accessed via Strator terminals, PCs and mobile phones. The conversational robot, an expert in Strator’s software, helps save time by answering user questions immediately, 24/7. 

Renault

The Renault Group is deploying a new internal chatbot, using dydu’s technology. The car manufacturer already has a HR and IT bot and has just implemented a new selfcare tool to improve the experience of the 11,000 employees at their Technocentre (R&D hub), and to relieve the busiest departments. The conversational robot, that is still in a testing phase, answers questions about practical services (company rules and regulations, entry passes, lost and found, etc.), on-site services (media library, works council, concierge service, taxis, etc.) and events (activities, exhibitions).

Cdiscount

Cdiscount used dydu’s technology to create an FAQ tool on their website. It provides visitors with immediate answers to their most frequently asked questions, on topics such as tracking orders, returns and refunds, breakdowns and warranties, customer account management or the marketplace. This new selfcare tool handles more than 20,000 interactions per day, which saves customer services a significant amount of time and increases productivity.

S2E deployed and now manages conversational robots for 4 major banking and insurance companies, in order to answer their recurring customer questions about employee savings. Stéphane Palvadeau, the Chatbot Administrator and Call Centre Supervisor at S2E, shares his experience managing these 4 bots using dydu’s software.

Who is S2E (Service Epargne Entreprises)?

S2E was born in 2006, grouping together 4 major players in employee savings plans, to support their development. S2E manages the administrative processing of employee savings schemes for 70,000 companies and close to 3 million employees.

S2E works with dydu’s solution to manage and monitor 4 chatbots aimed at employees with an employee savings scheme.

Stéphane Palvadeau, who are you and what is your role?

I joined S2E in October 2018 to finalise the employee savings business aspects of the chatbot, drawing on the expertise I previously acquired working in account and business administration. With regards to the shared management of the 4 bots, I am currently responsible for publishing content, analysing the dialogues, and reporting to the custodian account keepers.

More generally, my role is to continually improve the customer experience by identifying how the online customer journey can be improved, as well as any navigation issues. I also liaise with the custodians’ call centres to ensure that the chatbots and operators are providing consistent information. I begin most days by analysing the previous day’s dialogues and I optimising the knowledge base accordingly. The rest of my day is then spent improving and enriching content, liaising with call centres, producing reports, requesting updates, etc.

What issues do company pension plan bots respond to?

The bots specialise in employee savings in the banking and insurance industry. They answer generic user questions and help navigate the custodian’s website. The aim is to relieve call centres of requests with low added-value. One of the custodian account keepers already had their own chatbot. So, when S2E was contacted to deploy the same service on other custodian websites, we merge the content and management for several clients with the same issues. A large part of the knowledge base is therefore based on a regulatory framework, which can be shared among our clients. Similarly, the insights gained from analysing the dialogues can often be shared too.

In order to share this knowledge, we therefore first had to define nearly 200 common knowledge articles in collaboration with the custodian account keepers. This phase took about a year. During this time, we also identified a dozen differentiating topics to be managed outside of the collective framework, by the custodian’s individual bot. Some content is customised for each of our 4 clients, based on their schemes’ specificities or their communication strategy.

This enables us to offer each of our custodian clients a personalised and scalable service, while ensuring a common knowledge base, particularly on the regulatory side. In order to target the best period for each client, the final deployment phase for the 4 chatbots took place between October 2019 and February 2020.

How does this project work?

The 4 bots benefit from the same overall services, including the knowledge base administration, bot management or the production of reports. Content is updated and added by S2E, who then informs the custodians. This mode of operating ensures maximum agility when using the product.

The number of potential users for each custodian varies greatly, so the volume of dialogues observed on each bot is naturally heterogenous. The most used chatbot carries out more than 5,000 conversations per month. But whatever the numbers, the volumes observed justify this chatbot self-care approach.

Drawing on user questions to the 4 bots to update and add to the shared knowledge articles, also ensures that all our clients’ users share the same experience. This is a particularly virtuous model that has a positive impact on the bots’ performance.

How do you measure the bots’ performance?

We send a monthly custom report to each of our clients, based on indicators made available by dydu and the 30 most used shared knowledge articles. The bots have now reached a level of maturity that will enable us to make these reports quarterly.

Once a year, we send the custodians a global report, to provide them with an overview of the activity, and identify areas for improvement and development. The initial objective was to maintain a high qualification rate for the interactions. We therefore monitor this indicator carefully. We continually monitor the knowledge articles, in a centralised manner, and improve them accordingly, which explains why the 4 bots have interaction qualification rates that are over 98%, compared to a 93%* industry average.

We also, of course, monitor and regularly seek ways to improve the level of other customer satisfaction indicators. User feedback and reasons for dissatisfaction are therefore always analysed to ensure that the content published is continually improved.

How have the bots been used during the health crisis?

The first lockdown didn’t change user behaviour, but we have observed a change in questions, particularly with regard to stock market trends and the impact of the fall in prices on employee savings plans. We were able to quickly create new knowledge articles and update others, in order to answer these questions. Dydu’s product makes it possible for us to react quickly, because we can adapt our answer model to the situation in a very short amount of time.

What are your chatbot administrator best practices?

When it comes to employee savings plans, certain key terms that appear in user questions, such as “payment” or “transfer”, can have different meanings depending on the context or even the time of year.

To overcome this issue, I avoid updating knowledge articles with ambiguous phrases and allow the chatbot to suggest alternative phrasings instead (suggestion of several knowledge articles), so as to not provide a potentially irrelevant direct answer. In my experience, users are able to select the knowledge article that reflects their situation. In some cases, I think that indirect matching should be favoured over direct matching. If I notice that a knowledge article’s phrase is misleading users, I delete it.

It is also very important, in my opinion, to take great care when adding phrases to knowledge articles. Indeed, during my daily dialogue analysis, I add to the knowledge articles if I think a user question is likely to be asked again. This means that the bot can now understand a question that it misunderstood the day before. Before adding these new phrases, I correct spelling mistakes, delete any irrelevant contextual elements, and chose the most suitable matching groups. This process has enabled to gradually improve the matching rate over time.

What developments are you planning for the future?

Some of our clients want to expand their service with LiveChat, so that users can continue a conversation they started with the chatbot, with an agent. Dydu’s solution allows to define the triggering of knowledge articles based on behavioural targeting rules (time of inactivity, determined number of unsatisfactory answers, etc.).

We would also like to add an onboarding step before users can enter a question, in order to contextualise the relationship and explain the chatbot good practices. This will avoid any confusion between the chatbot and LiveChat.

The more personalised the information, the more relevant and appreciated by users it is. With this in mind, we plan on providing the chatbot with custom information, so that it can publish individualised content. This will meet the specificities of some of our clients’ operations that are not currently covered by the shared knowledge.

And finally, why not deploy the chatbot on a mobile app, which has proved hugely successful over the past few years?

* dydu data for the entire year 2020, based on more than 15 customer relationship chatbots in the banking/insurance industry.

Pixelraise partnered up with dydu to implement a gamification layer to the Jules chatbot, a homework helper for secondary school students, deployed by the CNED with dydu’s solution. Moezz Sedkaoui, founder and managing director of Pixelraise, looks back at this collaboration and explains the advantages and mechanics of a chatbot-gamification association.

Can you describe your company and role in a few words?

Pixelraise is an IT consultancy firm and web and mobile developer, with an entity in France and Switzerland (WebGoeSon). Our 25 employees develop custom IT solutions, e-commerce sites, native and cross platform mobile apps, and CMS-based sites. Pixelraise has a large client portfolio: Merck, EMS Medical, Produits Dentaires, Carglass Suisse, the French Ministry of Education, Sword, Hermes, Plezi, etc.

How was the Pixelraise and dydu partnership born?

Dydu put out a call for tender looking for a partner that could quickly gain the skills required for their chatbot technology and, above all, enhance the existing Jules chatbot app through gamification. A shared contact brought the decision makers from both companies together, giving rise to a great collaboration and successful project over a 10 month period.

Can you describe the role Pixelraise played in the CNED Jules project?

Pixelraise was responsible for developing the gamification layer (excluding UX and design), with 3 main objectives:

• develop digital uses for the “Devoirs faits” programme (personalised support and help with homework for secondary school students)
• reward effort with prizes, to encourage students to use the app 
• motivate users to play regularly

What does the Jules chatbot currently offer in terms of gamification?

The gameplay we developed enables the user to win flames and gifts. By earning flames, the user can move to the next level, and is rewarded with a gift at every level. These gifts include outfits for the user’s avatar or backgrounds to personalise the environment.  

What were the different steps to implement gamification in the chatbot? How does this combination work technically?

The first step was to understand and perfectly master the dydu component (Assembly.js), the chatbot’s engine that contains the knowledge base. Then, we developed all the APIs to interact with user actions, to reward and encourage them to learn while playing. Technically, the interactions between the quizzes and dydu’s chatbot are done via a function call in Js, using JavaScript Window Option. Finally, the app authentication is based on an API managing the creation of user accounts (student and teacher profiles – web and mobile) and the connection.

What are the main game mechanics and keys to a successful game or challenge?

Gameplay is the first aspect, including playability and the rules of the game. The player should be immediately immersed in the action with an adapted design. The second important aspect is finding the right balance between constraints and possible actions; too many rules make the game difficult to play and too much freedom leads users to drop out, without any retention. The last aspect is the pleasure or fun of playing, based on innovation, whether technical, design or narrative. 

The keys to a successful game can be summed up in 5 points:

• choose a unique gameplay; use well-known game mechanics that the majority of gamers are familiar with, and add customisation to make the game unique,
• opt for an innovative design; UX is very important, and it is essential to carefully design the game so as to offer a unique and coherent experience from the very first session. The game should be fun. If the user’s first impression is negative, there is little chance they will play again (and they will probably uninstall the app),
• work on retention; for example, create addiction with random rewards,
• optimise the response time; make sure that your game takes no more than 2.5 seconds to load, in order to reduce your abandonment / unsubscribe rate, 
• market the game with a suitable budget to make it visible among the many games available, in a very competitive market.

What other web and mobile developments have you carried out for the Jules project? (application, authentication interfaces, etc.)

We developed an external back-office on the Java / Springboot / BD Postgress / J2ee stack, in order to manage certain items such as the flames, quizzes, levels, outfits, backgrounds, etc. It also contains user information.

Do you think there will be other opportunities for dydu and Pixelraise to work together, beyond the Jules project?

Absolutely, we are complementary and perfectly capable of integrating dydu’s chatbot solutions. We recommend dydu to our clients as an expert partner in chatbot solutions.

In your opinion, how is UX design evolving in web projects?

Over the past 10 years, the user experience (UX Design) has taken a new direction, and users are now at the heart of projects (User Centric). UX design is not just about the design aspect of the interface. It also involves a reflection on the standard user journey in order to meet user expectations. The science behind the user experience is central to all web projects because more then 7 out of 10 internet users will not return to a website if their first experience does not live up to their expectations.
P.S.: by the way, I’ll soon be announcing the release of our UX addict websites

How do you think Artificial Intelligence will impact UX?

I believe that artificial intelligence will revolutionise the user experience. Artificial intelligence and user experience are closely linked in today’s world, where we are now facing a turning point in a new era including big data, voice search, chatbots, etc.

Real AI allows a degree of customisation that is hard to find on other more traditional channels. Within the context of voice search in particular, AI makes it possible to introduce greater personalisation, fluidity, and intuitiveness, all of which greatly benefit the UX. It is important that UX designers offer three options at the most per interaction, because the user will struggle to retain more than three.

The start-up, City-Drop, which specialises in one-way van rentals in major European cities, decided to use dydu’s conversational software to deploy a chatbot that answers recurring customer questions 24/7 and relieves their support teams.

More than 7,000 questions handled by the chatbot in 3 months

The City-Drop teams receive about 6,000 calls per month, some of which are recurring requests, asking  for information about bookings, rates, special offers, support (breakdown, vehicle location…), etc. For example: “How will I locate the vehicle?”, “Where should I leave it?”, “Do I need to fill up the petrol tank?”, “Where can I find my password?”, etc. To answer such questions, City-Drop therefore decided to deploy a chatbot. Since its implementation last November on the company website and mobile app, the tool has answered more than 7,000 questions. With a 90% success rate! 

“What sets City-Drop apart is that all our vehicles are connected. All you need is a smartphone to locate them, open them and use them. We therefore wanted to offer our connected clientele an additional service that they would find useful, in line with their expectations. Our chatbot enables us to maintain a virtual and continuous presence to answer requests at any time, immediately. We are also able to manage the tool internally and completely autonomously, which allows us to develop it as our needs evolve,” the co-founder of City-Drop, Frédéric Dubois, explains.

A quick deployment in 5 weeks, for an instantly optimised customer experience

“The chatbot was deployed very quickly, in just 5 weeks, and already has approximately 150 knowledge articles. This allows the chatbot to handle 20% of incoming calls! And this number will continue to rise. By gradually adapting the chatbot’s knowledge over time, City-Drop will be able to respond to more requests and therefore continue to optimise their customer experience, while relieving pressure on their teams, who no longer have to handle the most frequent questions,” Katia Houbiguian, dydu’s Marketing and Customer Experience Manager adds. 

This simple and precious tool automatically answers recurring questions for the 6 customer service employees. “Our customers still ask the same questions, but they turn to the chatbot instead of the phone. This tool therefore improves our support team’s day-to-day working experience, by making their job less repetitive and rushed, and enabling them to manage requests with higher added value,” Frédéric Dubois, co-founder of City-Drop, concludes. The chatbot therefore complements the existing customer services as it takes over recurring tasks and ensures a continuous presence, beyond 8am-9pm when the team is available.

To support their development abroad, City-Drop also plans to translate the chatbot into Spanish. In order to make the customer experience even simpler and smoother and to enhance their service, City-Drop is also looking at interconnecting the solution, so that customers can perform actions via the bot, such as locking or unlocking a vehicle.

SPB, the European leader in affinity insurance, called upon dydu to implement a chatbot to facilitate the diagnosis of breakdowns and reduce the number of requests to the after-sales service department.

Isabelle Eloir, Marketing Director at SPB, looks back on the project 5 months after its launch.

Can you describe your company and your role?

I’m the marketing director at SPB, a broker-manager and leader in insurance policies for household items. We co-design white-label insurance policies for distributor clients (retail, e-commerce, telco, banks, etc.), on a wide variety of products and risks. Within the framework of our partnerships, we develop extranet sites for sign-ups and claims, and manage the relationship with policyholders.

My team’s role is to support the sales reps and our customers on several levels:

• Market studies and monitoring, to keep up to date with the best practices
• Digital marketing and web design, to help them design their sales journeys and manage their customer relationship, including seamless claims management.
• Relationship marketing in order to improve sales, while complying with the IDD, Insurance Distribution Directive, issued by the ACPR (French Prudential Supervision and Resolution Authority), which regulates our profession.

In your opinion, what challenges do your customers face in terms of the digitalising customer relations, particularly after-sales services?

With more than 50 million policy holders, we handle 1 million claims per year. This is a crucial moment in our customer relationship. For many years now, we have provided customers with a digital journey to report mobile phone damage or theft. This has enabled us to increase online claims by 50%. This is already very good, but we want to further improve this rate to meet our customers’ expectations.

ISSUES AND SOLUTIONS

What issue(s) were you looking to solve with a chatbot?

Up until now, within the framework of warranty extensions, breakdowns of household and high tech appliances were handled over the phone. Lots of products, complex situations, risk of fraud… We found more than 750 different scenarios and therefore just as many obstacles to completely digitalising the customer journey.

Why did you choose dydu?

We made a request for information (RFI) and a request for proposal (RFP), and dydu came out on top because it was the only tool on the market that could provide us with:

• an interface enabling our customer relations experts to take control of the configuration of scenarios and subsequent bot training
• a natural language processing (NLP) model that is already well trained in managing spelling, grammar and syntax is several languages, enabling us to deploy it in all the European countries we operate in
• an editor-integrator that is as close as possible to our business needs and IT teams, enabling rapid and efficient deployment
• easy integration with our claims extranets
• the possibility to move towards a callbot, directly reusing the existing scenarios in voice

THE CHATBOT PROJECT

What areas does your troubleshooting chatbot address?

The bot currently handles online breakdown claims for all large household appliances, as well as some smaller products (such as microwaves, coffee machines), the TV and games consoles.

What steps were involved in the project?

We used an agile method and worked with a tightly-knit project team. This enabled us to deploy the chatbot is just ten weeks, from the first design workshops to the launch.

What benefits have you seen after implementing the solution? Time, productivity, image, satisfaction, etc.

Firstly, user satisfaction thanks to:

• customer service available 24/7
• a highly efficient interface – we handle 97% of claims directly in just 6 to 7 customer interactions

We have gained in efficiency because the breakdown details are sent directly to our service providers to anticipate repairs. Finally, our managers can focus on customers who prefer to use the telephone.

What aspects of the project implementation and management are you particularly proud of?

All of them! But more rationally, as far as we are aware, it is the only online breakdown claims chatbot in France. We were awarded the bronze trophy at the 2020 CX Awards in the best selfcare and chatbot strategy category, as well as the gold e-commerce trophy in the “Retail Innovation” category. Proof that start-ups aren’t the only innovators. An over 55-year-old medium-sized company can be at the cutting edge of technology too, with the aim of providing better service for its customers!

AND TOMORROW

Are you thinking of extending your chatbot’s scope, and if yes, in which area?

We would like to expand our “Products” category, provide a multi-lingual service, and maybe one day migrate towards a callbot.

The Conseil Départemental du Val d’Oise (local government council) implemented a HR chatbot in January 2020 to answer recurring questions from staff. The chatbot was created and deployed by Sword, an international consulting, software, and services company, in
partnership with dydu, an automated conversational software publisher.

The Conseil Départemental du Val d’Oise, Sword and dydu take a look back over the project, 6 months after the bot went live.

What issues were you trying to solve? Why did you choose a chatbot?

Karen Leclech, HRIS project manager at the Conseil Départemental du Val d’Oise

Nearly 4,000 people work for the Val D’Oise department, both on and off site. One of our main goals was to provide a tool that can be accessed 24/7, instantly answer the most frequent generic HR questions, and facilitate access to existing resources (particularly on the Intranet).

For example, in response to a recurring query about how to request leave days, the chatbot acts as an intermediary, providing both the answer and a link to the leave request form, available on the Intranet. Another equally important goal was to free up time for HR.

The chatbot handles generic questions, enabling our teams to focus on individual cases and provide more support. The chatbot therefore perfectly fits into our HR modernisation strategy. It is an innovative tool, and fully integrated with our Intranet. What particularly appealed to us was the training and support provided, the possibility to update the bot in line with any regulatory changes or new council projects, and its simple maintenance. For all these reasons, we launched a tender and chose dydu and Sword to bring our project to life.

What were the different stages of this project?

Samuel Payen, Digital Consulting Director at Sword

Sword is an IT solutions integrator and dydu partner. We supported and assisted the Conseil Départemental du Val d’Oise throughout this project. On average, it takes 8 to 12 weeks from start to finish to deploy a chatbot. This includes phases that are shared by all IT projects:

• launch: this is the framework of the project, when the scope, objectives and KPIs to be achieved and measured are defined.

• design and technical integration: the bot’s visual and editorial identity are defined so that it best embodies the Conseil Départemental du Val d’Oise. Any interconnections with internal software, such as the HRIS, are planned for at this stage. This is also when we talk about scalability with the different interfacing options, that will allow the tool to be updated later on. We work hard to support the HR and IT teams during this phase.
• training: the teams are trained to use dydu’s back-office so that they can build and update the chatbot’s knowledge base themselves and become completely autonomous.
• knowledge base: this is the chatbot’s content. A knowledge article includes a question and an answer. They are created by teams with expert knowledge on the subject, so in this case the HR department. We recommend creating approximately one hundred knowledge articles for a straightforward project, but nearly 500 were created for the Conseil Départemental du Val d’Oise. Sword created the first to help guide the teams before they then took over. The aim is for HR to be completely autonomous when it comes to their chatbot’s content. Behind the knowledge base is natural language processing, the added value brought by dydu’s software, which has been part of their solution for the past 10 years.
• testing: when the bot is almost ready for use, we carry out a testing phase before rolling it out to all users.
• follow-up and updates: this refers to the support, chatbot audits and any changes or updates made to the knowledge base, interconnections, functionalities, etc.

During the entire set up phase, a project manager was in close contact with the Conseil Départemental du Val d’Oise to provide weekly updates, monitor the risks and send an alert if any were to arise. He was assisted by a technical expert who configured the chatbot, set up any interconnections and liaised with the software IT teams. During the run phase, we provided technical assistance so that the Conseil Départemental could inform us of incidents or request any changes.

How did the project implementation go on the client-side?

Ophélie Lannoye, HR Support Officer at the Conseil Départemental du Val d’Oise

On our side, most of the work consisted in building the knowledge base. At first, we thought the chatbot would only address certain key themes, but we decided to extend the bot’s scope along the way to cover all HR topics. Which is why we have 500 knowledge articles instead of the recommended 100.

When building the base, we held several workshops internally to define the most frequent HR questions and their answers. In practice, we then tested the first knowledge articles on a Test group and on their departments. Through these workshops and tests, we finetuned the knowledge articles and defined the bot’s behaviour by customising its answers and identity.

During the test phase, we noticed that there were a lot of “personal” questions, such as “tell me a joke”, or “who are your parents”. But these questions don’t come up very often now that the chatbot is in place. We have however noticed a certain level of politeness in the way people address the bot, such as “Hello, thank you, goodbye”, “thank you for your answer”, etc. This shows that the project is successful and also reflects a certain respect for the tool and those working behind the scenes.

We also co-designed our chatbot Dimo internally, with the help of dydu and Sword. The avatar and chatbox colours were chosen by users within the Conseil Départemental, and we asked HR employees for their input too. This encouraged a better adoption of the tool.

What goals did you want to reach?

• Offer our staff a 24/7 service : our HR chatbot Dimo can be found on the Human Resources page of our Intranet. It is available at any time and provides instant answers.
• Strengthen our HR department’s innovative image : this HR bot has improved the image of our department, and I think other departments may be interested in doing the same.
• Provide generic and contextualised answers : we decided not to connect Dimo to our HRIS, so that users do not have to identify themselves. Our employees can chat with the bot anonymously and the answers are therefore generic and the same for everyone.
• Ensure users get an answer in 3 clicks max : we want users provide users with an immediate answer. If they don’t find what they’re looking for within 3 clicks (despite the bot rewording their request), Dimo offers to search the Intranet.
• Ensure HR managers can focus on high-priority issues : recurring questions tend to revolve around the same topics, such as leave, working hours and HR forms. By automatically replying to these questions, the chatbot frees up time for HR staff to handle more complex issues.

All these goals have been achieved or are close to being so. We are proud of our answer accuracy rate (90% to 95%). Our users are also satisfied and give their feedback directly via the bot through the answer rating system.

What are the next steps for this project?

We are continuing to communicate around the chatbot, to encourage user adoption. We are also continuing its deployment by making the best use of the tool’s features, such as the “top 3”, which highlights 3 hot topics in the chatbox.

As for the knowledge base, we will maintain the number of knowledge articles and adjust the answers according to current regulations and new projects. We are also studying other channels such as mobiles, and the addition of a voice functionality (voicebot).

TotalEnergies, formerly Total Direct Energie, is the leading renewable energy supplier in France, and third electricity and gas operator. It became part of the TOTAL group in 2019, after a merger between Total Spring and Direct Energie. It is a private company and has been supplying consumers with electricity and gas since 2003.

Today, TotalEnergies has more than 4 million customers and delivers over 52 TWh of energy per year. The company has invested in a number of gas-fired plants and therefore produces a large part of its electricity itself.

In terms of business development, its focus revolves around innovation, leading to a more responsible consumption for professionals (400,000 clients), local authorities (100,000) and individual households.

The Chatbot

Direct Energie’s chatbot was implemented in July 2016, after the launch of a Live Chat at the end of 2014, with the aim, as always, of innovating and improving the customer relationship. Since early 2010, customer contact via digital channels has increased sharply. Total Direct Energie therefore decided to make this a key part of its development strategy. With 3 million customers at the time, many of their questions and requests revolved around the same recurring topics. As customers did not always look at the FAQs, TotalEnergies turned its attention to virtual assistant technologies, with performance indicators relating both to user rates and customer satisfaction, in order to provide continual assistance and to absorb the sheer volume of incoming requests.

Over the last 4 years, the number of bot interactions has steadily increased. This, of course, reflects a growing number of customers, but also the major steps taken to optimise the tool to meet these customers’ needs. This can be divided up into 3 main phases.

Firstly, the launch of the chatbot by creating a knowledge base – fifty or so articles initially – and deploying it on the customer account page. Within the first few months, there were already 300 conversations per day, during which the knowledge articles (question/answer pairs available in the chatbot database) were carefully reviewed, fine-tuned, and added to.

It soon became clear that personalising answers depending on the customer type – private household or professional -, history or consumption, would be a real asset. TotalEnergies therefore decided to implement sophisticated variables and decision trees, which had a positive impact on the chatbot’s frequency of use and satisfaction rate.

Finally, since the bot is located on the customer account home page, there were a lot of questions about logging in. More knowledge articles were therefore added and adapted to these requests. This took the chatbot use to yet another level and the number of conversations per day is now around 2,000. 

Chatbot Use and Benefits

The main benefit for customers is that the chatbot can provide answers at any time of day or night, whether during the week, weekend, or on a bank holiday. It can answer questions about logging into a customer account, but also queries about contracts, (documents required, contract types, peak/off peak times, etc.) or  invoicing and payments (due dates, receipt, checking your account, etc.). The bot can also redirect the user to more detailed documents or a phone agent for more complex requests. By analysing the answers and satisfaction rates, the bot helps avoid direct contact with customer services at least 4 times out of 10, allowing them to optimise their services.

Today, 18% of the chatbot’s knowledge articles cover 80% of the questions asked. The conversations are nonetheless continually reviewed in order to adapt to customer needs in real time. The knowledge base is thus regularly and quickly updated (currently nearly 250 knowledge articles). The tool is flexible and easy to use remotely. During the health crisis, this enabled Total Energie Direct to provide information about support measures as soon as they were announced by the government, such as the extension of the energy voucher scheme.

Advantages of the dydu Solution

The dydu solution was chosen for its simplicity and autonomous nature, which still apply today.

“The chatbot user interface is simple. You don’t need any particular skills to add knowledge articles. The tool is a turnkey solution. We are completely autonomous,” François Remuhs explains, in charge of general customer services for digital customer relations and new uses within TotalEnergies’ operations department, who was behind the implementation and development of the chatbot.

While user support is highlighted, the design and ergonomics of a “fun” product is what wins employees over.

And tomorrow…

Until now, the chatbot has been fairly independent. But it will soon be interconnected with a multi-channel solution, in order to assist customers via instant messaging or social media as well. New environments such as Messenger or Twitter are currently being looked at. Finally, the chatbot will move from a purely informational and “redirectional” tool, to a transactional one. To take its use further and provide a more personal experience, it will be connected to TotalEnergies’ CRM, enabling the bot to send emails or carry out simple actions such as gathering data for a new contract.

A service culture is at the heart of TotalEnergies’ values, who closely monitors customer satisfaction and their tendency to recommend the brand to others. TotalEnergies is now reaping the benefits of its strategy and investments, winning the “Prix de l’Excellence Client” in 2019 (awarded by the Académie du Service, Ipsos and Trusteam Finance), alongside 9 others out of 160. And we have no doubt that the dydu chatbot played a part.

At the request of the French Ministry of National Education and Youth, the CNED (National Centre for Distance Learning) implemented a virtual homework assistant for secondary school pupils in January 2019. Since the beginning of lockdown, Jules, the virtual character who embodies this digital tool designed by dydu, has seen peaks in traffic with nearly 235,000 interactions per month. This chatbot provides valuable and free educational support from Year 7 (6 th grade US) to Year 10 (9 th grade US),
bringing pupils greater autonomy and motivation, and helping them complete their homework.

Already 70,000 users*

Methodology sheets, advice, quizzes, tips, videos… Everything a pupil needs to help them learn and revise. Jules, an animated character who reacts to different emotions, makes learning fun and helps develop research skills by encouraging students to rephrase and clarify their questions in order to
obtain the correct answer. The number of users has significantly increased since mid-March, with over 70,000 users (not including teachers) having now registered since the beginning of the school year.

An important figure that reflects the evolution and democratisation of this digital tool, which perfectly complements the lessons taught by teachers in the classroom and at a distance.

“dydu is immensely proud to contribute to the mission of public education through our collaboration with the CNED. Lockdown has reinforced our product’s use, as reflected by the increase in dialogues, and it will continue to be a true ally for pupils, teachers and parents, until secondary schools fully reopen… and even after!” Mathieu Changeat, co-founder of dydu, adds.

Three goals: autonomy, motivation, support

Jules answers questions in a friendly tone about French, Maths, History and Geography, such as: “What is an ellipse?”, “What is Pythagorean theorem?”, “What are the theatrical genres?”, “How do you mentally divide an integer by 25?”, “What are the keywords to remember about the Roman Empire?”, “What was the situation just before the Second World War?”, etc.

Easy to use, and perfectly adapted to 11-15 year olds, Jules motivates pupils and encourages them to be more autonomous, which has been required of them since the beginning of lockdown. It is available on the schools’ Virtual Learning Environment (VLE), the CNED website and the “Devoirs Faits” app on iOS and Android. Jules is a key academic support resource.

“Interaction is a key part of learning; to be able to ask questions, ask for clarification, confirm an intuition… Jules, dydu’s conversational chatbot, makes these exchanges possible at any time of the day and at a distance. With a well-adapted level of understanding, Jules provides clear and serious answers in a tone that is well suited to secondary school pupils” Jérôme Villot, director of Learning, Teaching and Digital at the CNED.

Continually enriched knowledge base

Jules is doted with a scalable knowledge base, that is continually enriched by teachers, delivering differentiated content that allows pupils to explore key learning concepts through a network of interconnected knowledge articles. With every user interaction, the digital companion improves; the
more it is solicited by students, the more relevant the content it provides. With up to 235,000 interactions per month, Jules is continually perfecting the chatbot’s knowledge to support the most curious students. By the end of the year, Jules will provide academic support in two new subjects.

*Number of users over the 2019-2020 school year.

French sports media outlet, L’Équipe, and dydu launch the first expert chatbot dedicated to the Ligue 1, France’s top football league. Looking for info about a season’s top goal scorer? A player, manager or club’s achievements? Botaldo has all the answers to your questions about French championship players and teams since the 1960s.

The idea for Botaldo came to Cyril Texier, co-founder of dydu and a football fan, on the way back from a trip to Luxemburg with his associates Mathieu Changeat and Jérôme Vérité in 2015. His idea was to take to the technology created by dydu, natural language processing, and apply it to a field he particularly enjoyed, football. The aim? To provide immediate answers to questions asked by football amateurs, who would otherwise find themselves scrolling through Wikipedia pages in search of the correct answer.

The dydu technology enables the chatbot to understand the users’ questions and requests, but we still needed the right answers! This issue was solved by connecting the chatbot to the L’Equipe sports media outlet’s Ligue 1 data, which dates back to the 1960s. dydu’s conversational expertise, combined with L’Equipe’s data, allows the chatbot to provide the user with correct answers, while ensuring the dialogue is as smooth as possible.

The chatbot provides answers to queries such as, “Tell me more about Marius Trésor”, “How many goals did Mbappé score for Monaco?”, or “What’s Jean-Pierre Papin’s record number of goals scored in one season?”. At the end of the answers, Botaldo formulates new suggestions, allowing the user to continue the conversation and find out more about their favourite players and clubs. The chatbot learns from the user dialogues, through supervised learning, and improves its football knowledge on a daily basis.

“Conversation is a new form of interaction that is developing more and more with the rise of messaging platforms,” comments Emmanuel Alix, director of the digital division at L’Equipe. “As the first sports media outlet in France, we had a duty to offer this new innovative form of exchange to our subscribers. Botaldo is the first chatbot in the world to offer such high quality sports content. We are currently studying the possibility of making it vocal and accessible to football fans via their connected speakers.”

“I am very proud to launch Botaldo at the start of this new football season,” Cyril Texier, co-founder of dydu, reveals. “As co-founder of dydu, this project is of course close to my heart, but also as a football fan, and more specifically of the Girondins de Bordeaux. This is a very ambitious project because, for over a year, we had to think about all the possible questions a user could ask and teach them all to Botaldo. I hope every football fan will love this chatbot as much as me.”

Agirc-Arrco is a supplementary pension fund for the private sector, that supplements, by definition, the basic pensions paid in France by the Sécurité Sociale or the MSA. The Agirc and Arrco schemes merged on 1 st January 2019 into one scheme. Agirc-Arrco had over 22 million contributors in 2017 and decided to call upon dydu to implement a chatbot for their subscribers.

Maxime Garcia, Project Manager in the Digital Innovation Team at Agirc-Arrco, is describing the set up of the chatbot and its results.

What is your role within the organisation?

I am a project manager within the Digital Innovation team for Pension Product Management. I manage several projects focusing on customer relations and digital innovation, including the chatbot which is my main task.

What digital issues are you currently tackling, particularly in terms of conversational technology?

We aim to provide a range of homogenous services within the sphere of supplementary pensions,whilst improving the schemes’ brand image; responsive, innovative and readable.

Which problem(s) were you looking to solve by automating your user dialogues?

We receive numerous requests from our users, and they cannot be handled solely by our advisers. We needed to implement a chatbot to deal with the excess requests via automated responses. Our objective was to increase customer satisfaction while decreasing management costs, by allowing the user to be autonomous on the internet.

Why did you choose dydu?

Dydu covered all our specifications and requirements by offering a solution adapted to our needs.

What difficulties did you face and how did you overcome them?

We didn’t come across any particular difficulties. The few bugs we encountered were rapidly resolved.

What benefits have you observed since implementing the solution?

The chatbot has helped reduce the flow of calls to our customer relation centres. It has also made it possible to provide a customer service outside of the centres’ opening hours. The chatbot currently handles 30 000 dialogues per month on average, with an 85% success rate.

Do you consider the project to be a success? For what reasons?

The implementation of the project has been a success because our call flow diversion targets have been met, while maintaining a high level of understanding of our users’ questions.

How do you see conversational technologies evolving in years to come?

Automated conversations are becoming more and more essential to meet a company’s productivity targets. It is therefore necessary to rapidly develop these kind of tools.

How do you plan to remain innovative in this sector?

To avoid becoming obsolescent, we plan on continually improving our tools by closely following all the latest innovations in the field. We must seize all the opportunities that arise at the correct moment and stay tuned to the uses of tomorrow’s conversational technology (voicebots, callbots,
etc.).

Following the request of the French Ministry of Education, the CNED (the french distance learning center) has set up a homework support chatbot for middle school students, which is part of the “devoirs faits” program. Accompanied by dydu, the digital assistant is embodied by a virtual character named Jules.

Jules provides each middle school student with specific and adapted answers to help them complete their homework in French and mathematics. 

AI at the service of education

With an evolving knowledge base which is continuously enriched by teachers, Jules is able to offer personalized content allowing the pupils to browse though the fundamental notions. It promotes the autonomy of students and cultivates their research and reflection skills. Thanks to Artificial Intelligence, Jules improves over the uses: the more the students ask him, the more he brings them relevant content.

“Our collaboration with the CNED began 5 years ago with Tom, a virtual assistant developed for the “D’COL” project, which aims to help, support and accompany 5th and 6th grade students. The CNED has renewed their trust in this new project and we are very proud of it. By the number of students and teachers involved, this project is the first of that kind in the field of Tech in education, and chatbots in general. Because of its size, this project required a specific organization and a permanent communication between our two teams, in order to meet the expectations of the pupils” says Cyril Texier, co-founder of dydu.

Jules is available on the national middle schools plateform, the CNED website and the app “Devoirs Faits” on iOS and Android. Once connected to their account, students can interact with Jules and get personalized answers.

An innovative project

“In addition to the size of the project, the other challenge was to be able to recognize mathematical symbols and formulas,” says Pierre Féret, dydu’s project manager. “Mastering our techno enabled us to implement this feature quickly, without impacting the launch date of the chatbot.” 

To promote its adoption by students, Jules offers innovative features: 

• a history to consult previous conversations
• methodological sheets to get help with revisions, tips and tricks
• an animated avatar that reacts differently according to emotions
• a link of intentions allowing students to deepen their question with related topics in the program 

Michel Reverchon-Billot, General Director of the CNED added: “« dydu has provided the CNED with an intuitive and easy-to-use software to create the digital tool we needed. By promoting students’ research and reflection skills, he supports them and helps them to do their homework in a playful way.»

The Groupe ADP, formerly Aéroports de Paris, is a French company that builds, designs and operates airports. The Paris and surrounding region’s airports are operated under the Groupe ADP’s traveller brand, Paris Aéroport. The Groupe employs over 6 500 people and called upon dydu to implement IT, HR and legal chatbots.

Jean-Michel Duvivier, IT Innovation Project Manager, is describing the set up of the chatbot and their first results.

What is your role within the organisation?

I am a project manager within the innovation branch of the Information Systems Division at Groupe ADP. 

What digital issues are you currently tackling, particularly in terms of conversational technology?

Our objective is to improve user satisfaction with the assistance provided to the different business units. This meets our commitment to significantly improve the quality of our tier 1 service departments’ (IT, HR, etc) responses.

Which problem(s) were you looking to solve by automating your user dialogues?

A portion of our employees work outside of normal working hours. With the implementation of chatbots, our support services are available 24/7 and in real time.

Why did you choose dydu?

Exchanges and seminars with our partners and subsidiaries are organised throughout the year. Within this context, we carried out several benchmark studies in 2017, including one on conversational robots. 

Following this analysis, we decided to carry out a trial run with dydu, which proved to be successful, and are currently entering an industrialisation and production phase..

What difficulties did you face and how did you overcome them?

We have been working with the same dydu teams from the beginning of the project, so the difficulties faced haven’t been of a technical nature, but more with the implementation of internal change management. 

Any anecdotes about the project?

When we launched the POC with beta-testers within the Information Systems Division, the first exchanges with the bot were of a culinary, and not technical, nature. There was a social movement at the time and with the office canteen closed, users wanted to know where to go for lunch.

What benefits have you observed since implementing the solution?

We don’t have any figures at this stage, rather qualitative objectives:  

• Increase of user satisfaction through an improved handling of requests
• Decrease of number of calls and emails to the different service departments
• Reduction of subcontracting costs
• Improved productivity amongst the in-house service department teams
• Redeployment and upskilling of tier 1 support teams to tiers 2 & 3

Do you consider the project to be a success? For what reasons?

Yes, absolutely. The departments that placed their trust in us during the trial runs now want the project to enter production.

How do you see conversational technologies evolving in years to come?

Chatbots will assist users with any recurring and currently non-automated tasks:

• Booking a meeting room
• Preparing for an appointment
• Requesting and approving leave
• Booking transportation
• Controlling the office air conditioning

With these new features the user will no longer need to connect to multiple applications, because the chatbot will instead.

How do you plan to remain innovative in this sector?

Today, chatbots dialogue through writing, tomorrow chatbots will be voicebots. We’re even launching a POC with dydu this year!

dydu and the Prefecture of Paris region launch NOA, a chatbot which aim to facilitate exchanges between administrations and start-ups. NOA is a friendly character with a blue, white and red straps, it is resulting from a call for projects of the “Programme d’Investissements d’Avenir” (future investment program). The chatbot answers questions related to administrative procedures for company creation : financial contributions, support programs, trademark registration…

“We were also a very young start-up 10 years ago, we know that it is not always easy : we don’t know where to start, who to contact, and we often learn afterwards that there were facilities to carry out some procedures. It’s from this observation that came the idea to create an inter-administration chatbot” says Cyril Texier, co-founder of dydu.

The virtual advisor of the Prefecture guarantees :

• a better dissemination of information on administrative procedures
• quick and easy access to a qualified advisor
• 24H availability in two languages (French and English)

An innovative and collaborative approach

The chatbot’s base of intentions was co-created by 10 administrations (Préfecture d’Ile de France, DRIAAF, DIRECCTE, Douanes, DRIEE, Pôle Emploi, Banque de France, préfecture de police, l’URSSAF et la DRFIP). Each administration contribute to the bot regarding its field of competence on the basis of the defined themes.

“With the creation of this chatbot, the regional prefecture is part of an innovative approach, illustrating its active support for start-ups in the Paris region. Facilitating the administrative procedures of entrepreneurs, this tool brings the public service closer to the needs of economic actors.” explains Michel Cadot, Prefect of Ile de France.

NOA is currently available on the websites of French Tech Centrale, the Préfecture d’Ile de France and Pôle Emploi. It will be shortly deployed on the websites of the other administrations.

Press release – 05/12/2016

Voyages-sncf.com has chosen Helpbox, the smart tool produced by Do You Dream Up, to provide its users with an intuitive, customised and effective interface through which they can find help online.

In 2012, Voyages-sncf.com set up its virtual assistant Léa thanks to Do You Dream Up. This was a key tool in its customer relations through which over 2 million conversations took place in 2015.

Now Léa has been replaced by Helpbox, which seeks to simplify the online help feature as well as the user’s browsing path. It supports users as they explore the site, without disrupting their browsing.

Since Helpbox takes the form a special window that can be accessed at any time, customer services are at the user’s fingertips via a single point of entry. The user can receive an answer to their question immediately, or be directed to the suitable channel of communication: live chat, click-to-call, e-mail, telephone, social media, etc.

Thanks to Helpbox, Voyages-sncf.com offers its customers the channels of communication that best meet their requirements. The top three questions associated with the web page being browsed appear when the help window is brought up.

Users are also provided with an autocomplete search bar in which they can easily ask all their questions.

Questions are firstly analysed by the Do You Dream Up natural language processing engine. Answers come from the content of the Voyages-sncf.com information base. The option of moving to another, more suitable channel of communication can then be put forward within the same dialogue window.

Helpbox also enhances the user’s experience via multimedia content (images, videos, forms, maps, etc.) that can be accessed in a side bar, again without disrupting browsing.

« For several years we have been working with the Voyages-sncf.com teams. Once again, they placed their faith in us for this project. By setting up our new self-service solution for the overhaul of their online help feature, we were able to strengthen our expertise and remain at the cutting edge of technology’ »

Cyril Texier, co-founder of Do You Dream Up

« High-quality customer relations represent a vital asset in our market and our online help is precious to our users. Do you Dream Up has proven capable in offering a solution that meets our requirements for overhauling our interface. Thanks to the new browsing path offered by Helpbox we can provide our users with an online experience that is as intuitive, as customised and as effective as possible.»

Julien Nicolas, France Director at Voyages-sncf.com.

This new online help feature from Voyages-sncf.com can already be accessed in French on desktops and tablets. Over the coming months, it will be gradually rolled out on other channels of communication (mobile site, ‘V.’ application, European sites, etc.). As for each new feature on the site, Voyages-sncf.com takes user feedback into account as it develops and invites users to share their comments on Twitter at #OpenVSC or directly on  https://open.voyages-sncf.com/

About Voyages-sncf.com

Voyages-sncf.com is a key stakeholder in European tourism and an expert in rail distribution and France as a destination. It has 1,000 employees, of which two thirds work solely in the field of the French and European markets. To meet the demands of customers’ new modes of consuming and travelling, Voyages-sncf.com is today present in 30 countries via 67 internet and mobile sites, four shops and a call centre service. The site brings together several rail operators including SNCF, Eurostar, Thalys and TGV Lyria, 400 airlines, 435,000 referenced hotels, 1,300 campsites, over 25,000 holiday packages, and 30 car hire companies.

For more information: https://open.voyages-sncf.com/

Press contacts

Voyages-sncf.com
Clotilde Huet – +33 (0)1 58 13 74 71
chuet@voyages-sncf.com

About Do You Dream Up – www.doyoudreamup.com

Do You Dream Up, created in 2009, is specialised in digital customer relations. They develop smart self-service tools for major accounts. The automatic natural language processing software company developed an innovative algorithm and knowledge base management solution. They make it possible to offer a better user experience and to improve client knowledge, while reducing the number of requests made to contact centres. Do You Dream Up solutions are available on desktops, tablets and mobiles to offer an innovative and coherent experience on all digital channels.

Key accounts in France and worldwide, such as EDF, Voyages-sncf.com, Orange, Humanis, Caisse des Dépôts and also PSA, have adopted Do You Dream Up solutions for their selfcare and e-commerce sites or for their internal helpdesks.

PSA Peugeot Citroën promotes self-service for its employees through the use of chatbot with Do You Dream Up.

PSA Digital department has implemented a self-service solution since 2012 in order to respond to internal questions in three domains: helpdesk, HR and practical services.

• Can you please present your company in a few words?

PSA is Europe’s 2nd largest motor manufacturer, established in 160 countries with 184,804 employees. The group’s 2014 turnover was €53.6 billion, with 2,900,000 cars sold. It has also been France’s biggest patent filer for the past 8 years.

• What is your role within your organisation?

We are part of the Digital, Data & Connectivity Engineering department (DDCE), more specifically in an entity in charge of collaborative and Intranet solutions. We coordinate these tools, upgrades and extensions.

• What are your internal challenges in terms of digitisation and your issues?

In December 2011, we initiated a Lean project to reduce helpdesk requests(telephone assistance for all malfunctions relating to the IT environment) and downsize local support teams.
In most cases, the users request these two services although cards (information sheets) are available on the Intranet. The documentation system is therefore not used to its full potential and is difficult to access.
Consequently, one of the primary objectives is to improve user autonomy to reduce the workload of these two support services, with a significant 20% drop in the number of calls.

Required solutions and expertise

• Which solution(s) and expertise did you seek to address these challenges?

As part of this project, one of the options is the implementation of a virtual assistant, designed to provide an answer within 30 seconds and in less than 3 questions. We believe this tool is the equivalent of a smart search engine.
We conducted market research among a number of companies. We chose the Do You Dream Up chatbot after shortlisting two solutions.

• What solution(s) have you implemented with Do You Dream UP? For which types of business process? In which languages?

The 1st version of the Eva chatbot was launched at the end of 2012 to manage employees’ requests in France. The Do You Dream Up project team worked very hard to index all data sheets in the documentary database, in collaboration with the PSA team. This initial phase took three months before production could start.

In 2013, our objective was to improve our responses to employees’ requests. Eva, the virtual assistant, helps identify user needs. This is why we focused our efforts on the most consulted documentation. Therefore we initiated a project designed to improve this content.
The scope was extended in 2014. Eva became multilingual. She is actually trilingual: French, English and Spanish, to reach all employees. In addition, EVA enhanced its content in terms of the company’s human resources and practical services (book a parking space or company vehicle, welcome an external visitor, etc.).

In 2015, Eva became accessible via the Group’s Intranet portal to respond to questions in three domains: helpdesk, HR and practical services.
All these continuous improvements and extensions are made possible by two employees who manage the virtual assistant project.

The results

• How many requests are made via the chatbot? Have you seen an evolution in terms of its adoption by users?

The objective we determined in 2012 was to receive 5,000 virtual agent requests per month.
In 2015, Eva was contacted 140,000 times a month on average. Better yet, the number of requests tripled between January 2015 and January 2016. The consultation of documentation has more than doubled in 3 years. Eva has become a web page traffic controller.
In addition, we have continually enriched the documentary database which currently features 3,000 pieces of information in French, 2,000 in English and 2,000 in Spanish.

• What benefits have you observed?

This chatbot has been favourably received. Eva has become essential to employees, a reflex in fact. We have observed a significant drop in the number of calls to the helpdesk, combined with a constant increase in requests made to the virtual assistant. 
Eva has even become a change management driver. It is practical and everybody has access to it.
We can use this channel to anticipate change, which is more readily accepted when it comes from Eva.
The feedback from employee surveys has been very positive.
An increasing number of business domains would like to join the scope of the Eva virtual assistant.

Choice of provider

• Why did PSA choose Do You Dream Up?

The solution proposed by Do You Dream Up helped us control the back office and upgrade the documentation ourselves. This aspect, combined with an efficient reporting system (thanks to the quality of the back office), is why we selected this particular solution.

• How did the Do You Dream Up team support you during this project?

During the start-up phase, the first 1,500 pieces of information were created by Do You Dream Up. Follow-up and corrections are made by the DYDU project manager as she goes along.
The Do You Dream Up project team is very effective and plays a driving role. Bimonthly progress assessments are organised, during which our dedicated project manager introduces new functionalities to be implemented. Scope extensions have rendered the project more complex, which is why assistance from the DYDU project team is vital.

Key success factors

• In your opinion, what are the success factors of this project?

To guarantee the full adoption of this tool, we initially paid particular attention to social issues, with a database of 1,000 pieces of general knowledge which was useful in convincing users. It is also essential to examine the requests on a daily basis in order to understand user needs, notably in the early phases of the project. The examination of negative opinions also helped make the application more reliable and complete.

And in the future…

• What changes do you envisage for these self-service tools? Are you planning to broaden their scope?
  

In 2016, we are continuing to improve the quality of the responses, but also the content of the documentation. The objective is to get this tool to answer more complex questions (decision tree and problem solving) to further reduce the number of calls to the hotline and even the troubleshooting department.

Interviewed persons

• Fréderic Durka, PSA Group Process architect
• Christine Dokchine,  PSA Group IT project manager
• Fabien Sauner, PSA Group IT project manager

Click here to download the pdf version of the interview

The Caisse des Dépôts promotes self service through the use of a chatbot with Do You Dream Up.

Customer relations management within the overall management of pensions and benefits by the Caisse des Dépôts promotes self service and a reduced amount of human contact related to frequently asked questions through the use of a chatbot.

The Caisse des Dépôts has fulfilled the role of manager, under a mandate from social organisations that include public pension schemes in France, since 1816. Management of pensions and benefits by the Caisse des Dépôts now includes 48 mandates in the area of social security.

• What is your role within your organisation?

The management of pensions and benefits by the Caisse des Dépôts is organised on two sites: Angers-Paris and Bordeaux. Each of these has its own Customer relations management service.
The role of the «Customer self-service» unit in Angers is to promote customer autonomy through the technical means available online. Encouraging autonomy means providing every possible way for the customer to find the information or service required without having to call a customer relations operator.
In customer relations management, within the scope of pension funds managed by the Bordeaux site, the aim of the «Digital information and customer experience» unit is to set up a digital
information service for active and retired members that is as comprehensive and simple as possible.

• What are the challenges with regard to customer relations in your organisation?
  

We have 3 types of customer. Employers, active members and retired members. Our customers expect information that is objective and simple, as the world of pensions is a complex one. We also have a duty to be transparent. In order to facilitate communications, our services must be available and we must listen to our customers. Trust and service are of vital importance for us in our capacity as providers of a social service. We are working on a very industrial scale but every individual request must be taken into account.

It is also our duty to be considerate, in other words to adopt a proactive and helpful approach. In simple terms, we have to put ourselves in the customer’s position and defend his or her interests. Putting ourselves in the customer’s position also means meeting his or her expectations in a very responsive way.

As a public service, we must respond in the same way to all our customers, both in France and in the various overseas countries, departments and territories, 24 hours a day, 7 days a week.
Due to the size of the population we serve, our customers are in almost constant touch with us or contact us via our websites.

One of our biggest problems concerned accessing private spaces. We were receiving a lot of hotline communications from our employer, active or retired member customers who were experiencing problems either registering or accessing their private space.

Required solutions and expertise

• What solution(s) and expertise had you considered to meet these challenges?

We came up with the idea of adding a chatbot option, as we had noticed that other large groups were using this procedure on their websites. Specialist magazines were also reporting the benefits of a virtual operator on web pages. In addition, we felt that having someone constantly there to answer or ask questions would be reassuring for our customers.

• What were the solution’s development stages?

It was a gradual process. In the 1st phase, we placed Ariane in the textbox for accessing personal spaces. A few months later, we also introduced the bot to the websites of CNRACL (Caisse Nationale des Retraites des Agents des Collectivités Locales – National pension fund for local public sector workers) and Ircantec (Institution de retraite complémentaire des agents non titulaires de l’État et des collectivités publiques – Additional pension organisation for non-permanent state and public sector workers).

With the help of Do You Dream Up which implemented the solution and developed the structure and training, we were operational in less than six months.

Results

• What benefits have you observed?

Ariane first officially responded to internet users on 11 January 2013. Since Ariane has been online, we have had an average of 11,600 conversations per month with a strong>success rate of 85%.
Thanks to our virtual assistant Ariane, we have reduced the amount of human contact related to frequently asked questions. This was our objective and it has been achieved. Customer feedback has been positive and managers are using chatbot more and more.

Choice of provider

• Why did you choose Do You Dream Up?

We chose Do You Dream Up chatbot because this solution seemed to be the most simple and user-friendly to implement.

• How did the Do You Dream Up team support you for this project?

Do You Dream Up supported us from the start of the project and throughout the entire course of its development. This was convenient for us operationally and enabled us to go online with the project very quickly.
From our perspective as a customer, Do You Dream Up is always available to answer our queries. Our suggestions for improvements were taken into account and this also helps with the development of AVI.

Key success factors

• In your opinion, what have been this project’s success factors?

Internally: dedicated teams for the development of automatic chat on each website, together with regular follow-up of conversations,
With regard to the service provider : Do You Dream Up teams that are responsive and extremely competent.

And in the future…

• What changes are you considering for your digital customer relations services? Are you planning to broaden their scope ?

To date, the services provided by Ariane have related only to general questions and those dealing with private spaces. We now hope to extend her assistance to personal questions, for example providing pension totals for retired members or the number of quarters already gained for active members.

• How do you see customer relations evolving in the coming years?

The world of pensions is changing, as is internet use. We have a duty to provide all our services in a simple digital way, which will allow us to optimise our organisation in order to meet these new challenges.
With the proliferation of smartphones and the constant use made of them by the current generation, the future of chat looks rosy.

Click here to download the .pdf version of the interview

With strong acquisition and customer retention objectives, Direct Energie, third largest electricity and gas supplier in France, supports its customers on the digital channel with live chat.

Julie Savart, e-commerce project manager and Edouard Racimora, Customer area project manager, tell us everything about their challenges concerning customer relations and e-commerce , live chat deployment and the benefits they have observed after 8 months.

“Direct Energie is the third largest electricity and gas supplier in France and already secured the loyalty of over 1.3 million customers. Direct Energie also developed its activity among companies and local authorities up to more than 100 000 delivery locations..

• What is your role within your organisation?

The online e-commerce team manages customer acquisition and conversion via the website, and the customer area team manages customer self-care and loyalty for private, professional and major account customers via the online channel.

• What are the challenges concerning customer relations and e-commerce in your organisation?

The online channel represents 20% of Direct Energie’s sales. Communication via telephone still dominates, but we would like to increase the online channel’s share. Our aim is to double the number of customers acquired by Direct Energie. It is therefore essential to be able to manage the flow of incoming contacts and relations with these new customers.

The online channel must be able to explain things clearly to the customer with complete transparency. In particular, it must enable them to follow and understand their consumption and billing.

Our aim is to guide, support and reassure the customer via the online channel during those key moments where human contact is necessary, for example during registration.

Within the customer page, the digital communication tools must enable us to reduce the number of calls to customer services.

The majority of the questions cover three subjects: billing, self meter reading and the procedure to follow for customers wishing to move.

Required solution and expertise

• What solution(s) and expertise had you considered to meet this challenge?

We looked at the possibility of a live chat, which not only offers human contact via the online channel, but also assistance during the registration process and increases customer loyalty whilst reducing the number of calls and emails.

We have implemented the Do You Dream Up Live Chat solution in France on the www.direct-energie.com website for the registration tunnel and the customer page.

• How long did it take to roll out the solution?

The live chat solution was rolled out between August and November 2014.

Results

• How many contacts have been made via the live chat ? How are they managed?

Nearly 10,000 conversations took place over 8 months via the live chat. During office hours, two staff members handle customer service contacts. The same staff members are also responsible for the social networks. For customer registrations, four operators have been trained. Two work simultaneously in a Webhelp call centre.

The use of the chat has stabilised. We have tried to add it to all the product pages, but few contacts are made via these pages. The need is mainly limited to the registration tunnel. For the moment, the live chat is only available on the private customer registration tunnel.

• What benefits have you observed?

The implementation of the live chat and notably the analysis of the conversations has given us the ability to optimise the purchase tunnel as and when necessary. The live chat is a customer «feedback factory».

This notably enables us to be aware when there is any malfunction on the website. The call centre teams also receive fewer calls with no added value. We have observed that certain Internet users prefer using the live chat to the telephone during the registration phase as this channel is less directive and they feel less constrained.

• Has the solution been well accepted by your inhouse teams? Do you have any feedback from the operators?

A digital cluster has been created at call centre level. The operators are happy to use the live chat. It is an innovative tool for them.

• Now that we have been working together for several months, what is your perception of our added value?

We have continuous and constant support from Do You Dream Up. Our dedicated project manager, Celia, defines the triggering rules. The rules are fairly technical, which means we are not very independent; we prefer to rely on Celia rather than take the risk of getting it wrong.

Key success factors

• In your opinion, what are the key success factors for this project?

The Do You Dream Up live chat is a turnkey solution which is simple to integrate, an essential factor for us given the strong constraints of our IS Department.

The second success factor for this project is the support provided by the Do You Dream Up sales and project teams. They advised us concerning the definition of the rules and their pertinence, and they also provided web design support. We also especially appreciated the teams’ responsiveness.”

Click here to download the .pdf version of the interview

Prosodie-Capgemini and Do You Dream Up participate in the development of the D’COL system, interactive tutoring by the CNED

As part of the digital public education service, the Minister of National Education, Higher Education and Research has entrusted the CNED (National Centre for Distance Education) with the development of a complete support and assistance system for French, mathematics and English, for students with difficulties who are in their first year of high school: D’COL. The originality of the system lies in the combination of in-class and on-line support: the student is accompanied at school and remotely at home.

To reinforce the ergonomics and attractiveness of D’COL, the CNED has asked Prosodie-Capgemini to set up and host a conversational agent called Tom. This avatar, developed by Do You Dream Up, the technological partner of Prosodie-Capgemini, is able to guide the student, to answer certain questions, to offer a first level of support, to orientate them towards new exercises and propose additional resources. And, when necessary, Tom can also put the student in contact with a CNED teacher, using the Do You Dream Up live chat.

To interact with students, the conversational agent uses a knowledge base created by the teachers. This knowledge base, which is regularly updated and expanded, covers a wide range of subjects and questions in order to answer all demands, irrespective of the level of syntax used by the student.

« The main objective of this system is to allow students in difficulty to be autonomous. The on-line service made available to them adapts to the level of each student, to offer personalised interactive exercises and allows them to progress »

Frédéric Artaud, CNED Project Manager.

« Conversational agents render on-line browsing more human, and offer immediate assistance, available at any time. For high school students, having an interlocutor, even a virtual one, can make a difference when they are taking their first steps and also throughout their learning path »

Laurent Marcheras, Product Manager at Prosodie-Capgemini.

This system was implemented for use by 30,000 students during the 2014-2015 school year.

About Prosodie-Capgemini

Since July 2011, Prosodie-Capgemini has been a subsidiary of the Capgemini Group specializing in designing and hosting Front Office services. Prosodie-Capgemini’s solutions are based on innovative proprietary technologies adapted to every stage of the users’ digital experience. These services are proposed in Cloud mode and in real-time thanks to a highly available and secure technical platform. Prosodie-Capgemini benefits from the international dimension of Capgemini to deploy its offer alongside the Group’s other entities.

For more information : http://www.prosodie.com

About Do You Dream Up – www.doyoudreamup.com

Do You Dream Up, created in 2009, is specialised in digital customer relations. They develop smart self-service tools for major accounts. The automatic natural language processing software company developed an innovative algorithm and knowledge base management solution. They make it possible to offer a better user experience and to improve client knowledge, while reducing the number of requests made to contact centres. Do You Dream Up solutions are available on desktops, tablets and mobiles to offer an innovative and coherent experience on all digital channels.

Key accounts in France and worldwide, such as EDF, Voyages-sncf.com, Orange, Humanis, Caisse des Dépôts and also PSA, have adopted Do You Dream Up solutions for their selfcare and e-commerce sites or for their internal helpdesks.

Humanis, a French group specialised in social protection, has integrated the Do You Dream UP dynamic FAQ solution since October 2014. Juliette Reisenthel, Head of Internet & e-commerce projects, tells us everything about the digital challenges of Humanis customer relations, the project stages and their results 10 months after the FAQ launch.

Humanis is a group specialising in social protection. Its activities include supplementary pensions, personal risks, health, international protection, savings and social action. Humanis has 700,000 member companies, 10 million beneficiaries and 6400 employees.

• What are the digital challenges of customer relations?

Our main challenge when it comes to customer relations is making information available in an instructive, customised format on our websites and in our customer spaces. This information can deal with both products and customer services. Our aim is to promote the shift to digital technology, self-service and exchanges between Internet users.

Digital technology should also be a driver of customer knowledge and loyalty. To that end, digitisation should free up time for the Customer Relations Department to provide our members with assistance and advice over the phone. Questions regarding the lifetime of contracts should be posted on the Internet (customer space, FAQs, etc.).

Required solutions and expertise

• What solution(s) and expertise did you seek out to meet this challenge?

We already had an FAQ section but its content was difficult to update. We thus sought out a new dynamic FAQ solution. The entire structure was involved in choosing the solution.

We were looking for an easy-to-administer solution in which our business teams could collaborate.

We ended up choosing the dynamic FAQ solution of Do You Dream UP, which we rolled out across three of the group’s sites: Humanis, Radiance Humanis, and Entreprise Humanis.

• What were the solution’s development stages?

To launch the project, we started by analysing the questions submitted by Internet users and enhanced the knowledge base with the corresponding answers. We put into place weekly maintenance with business advisers to rapidly enhance the knowledge base, which has grown from 100 to 400 data since October. We built on the questions asked by users to enhance the body of knowledge.

For the phase dedicated to transferring skills to business teams, we were assisted by Do You Dream Up. Our business teams are currently taking over management of the tool.

The project lasted just under 3 months before it was put into production in October 2014.

Results

• What benefits have you observed since the solution was launched?

The FAQ section meets the challenge of customer satisfaction for questions related to the lifetime of contracts.

Internet users can quickly find answers to their questions. User satisfaction has quickly risen, reaching an 85% response rate.

We study unresolved questions to find the missing answers.

We have noted that visitors in the FAQ section are highly active and navigate around the site, which increases traffic and the ranking of pages.

Customers have visited the FAQ section on a regular basis to find answers.

We have also saved time internally by directly using the administration tool for the knowledge base to enhance, validate and publish knowledge.

• What are the advantages of the Do You Dream UP FAQ solution compared to the one you used before?

The tool is dynamic. We can be extremely responsive by consulting the questions asked by visitors. This makes it possible to detect recurring requests and enhance the body of knowledge. It also helps us be familiar with the language used by customers and thus create formulation groups to be more relevant.

• Has the solution been adopted by your in-house teams? Have you received any feedback from the back office’s users?

Monthly meetings are organised to set objectives and anticipate topics of interest (legislative, product-related) by incorporating this knowledge into the back office.

Technology-savvy in-house users have quickly adopted the tool and say it is easy to use. The transition has been slower for people less comfortable with digital tools but everyone has gotten onboard.

Choice of provider

• Why did you choose Do You Dream Up?

We selected the publisher Do You Dream Up for the ergonomics of its solution and particularly its back office, the client proximity it offered as a smaller company and its economic model.

The Do You Dream Up project team with two dedicated advisers ensures close collaboration. It is easy to reach and responds very quickly. They have also assisted us during training sessions, and there was a pre-production phase.

Other positive point: Do You Dream Up sells a pre-packaged solution but actually the solution meets the needs of Humanis.

• How did the Do You Dream Up team support you for this project?

DYDU supported the team for the establishment of best practices, knowledge administration, technical support and training. Sophie, the Do You Dream Up project manager, draws up a monthly report and sends us alerts in the event of abnormalities.

• Do you have any anecdotes about the project you would like to share?

Some customers use the FAQ section as a chat tool. Many users are retired and think someone is answering them in person. We are currently correcting this point to help them better identify the type of tool they are using.

Key success factors

• In your opinion, what have been this project’s success factors?

Project management, the involvement of business teams, dedicated recruiting to enhance the knowledge base, having a team who centralises knowledge, and the monitoring of satisfaction. Lastly, the tool is easy and pleasant to use.

And in the future…

• What changes are you considering for your digital customer relations services? Are you planning to broaden their scope?

We are working on rolling out the FAQ solution for customer and partner spaces.

• How do you think digital technology is going to change in the coming years?

For customer relations, digital technology is going to become a point of contact and mediation for customers. It will be the main tool for customer assistance and loyalty-building.

Click here to download the .pdf version of the interview