Client Testimonial:  The French Development Agency Looks Back at the Implementation of their Chatbots

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.