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apidays LIVE Paris - From a simple chatbot to a fully programmable dating coach by Elisabeth Mouchy

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apidays LIVE Paris - From a simple chatbot to a fully programmable dating coach by Elisabeth Mouchy

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apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020

From a simple chatbot to a fully programmable dating coach
Elisabeth Mouchy, Chatbot Product Lead at Meetic Match group

apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020

From a simple chatbot to a fully programmable dating coach
Elisabeth Mouchy, Chatbot Product Lead at Meetic Match group

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apidays LIVE Paris - From a simple chatbot to a fully programmable dating coach by Elisabeth Mouchy

  1. 1. LARAD A T I N G C O A C H Elisabeth Mouchy Chatbot Product Lead @emouchy
  2. 2. Testing
  3. 3. MIDDLE WARE µSERVICES
  4. 4. +30%
  5. 5. Building
  6. 6. NLP µSERVICES MIDDLE WARE
  7. 7. NLP I am looking for a dark-haired, blue-eyed, tall man Describe your ideal match MIDDLE WARE µSERVICES
  8. 8. NLP Text query: “I am looking for a dark-haired, blue-eyed, tall man” MIDDLE WARE µSERVICES
  9. 9. NLP Not an exact match. Pass it over to NLP. MIDDLE WARE µSERVICES
  10. 10. NLP Got it. Here’s what I found: intention-detected: search_for_someone entity-detected: eyes_color: blue hair_color: dark height: >180 MIDDLE WARE µSERVICES
  11. 11. NLP Got it. I found an intent called “display_profile” that triggers an action “search_for_profile” MIDDLE WARE µSERVICES
  12. 12. NLP Launch the action & show profile. MIDDLE WARE µSERVICES
  13. 13. NLP Here’s Ryan, 34 years old, living in Paris. MIDDLE WARE µSERVICES
  14. 14. Ok, I’ve changed your age preferences Here I found Philippe, 24yo, Paris for you: Nah. Too old, around 25yo.
  15. 15. Could you tell me a joke? I was dating a microwave for a while, but things got too hot, too quickly. Have you ever been in loved? What do Vampires do on the first date? Go for a quick bite.
  16. 16. Optimizing
  17. 17. NLP CONVERS. DESIGN B. O. MIDDLE WARE µSERVICES
  18. 18. Hello, I'm Lara, your coach Hallo, ik ben Lara Bonjour ! Je suis Lara, ta coach Hallo, ich bin Lara Ciao, sono Lara Hola, soy Lara
  19. 19. PROVIDE DATING TIPS SEND A NEW MATCH EVERY DAY SUGGEST DATE LOCATIONS
  20. 20. NLP CONVERS. DESIGN B. O. MIDDLE WARE µSERVICES
  21. 21. Scaling Up Our Coach
  22. 22. PROFILE SUGGESTIONS ICEBREAKERS PROFILE OPTIMIZATION DATING TIPS CUSTOMER CARE
  23. 23. NLP CONVERS. DESIGN B. O. MIDDLE WARE µSERVICES
  24. 24. NLP CONVERS. DESIGN B. O. MIDDLE WARE µSERVICES
  25. 25. Globalizing
  26. 26. NLP CONVERS. DESIGN B. O. MIDDLE WARE µSERVICES
  27. 27. MIDDLE WARE µSERVICES NLP CONVERS. DESIGN B. O. こんにちは 👋
  28. 28. In A Nutshell
  29. 29. A fully scalable dating coach
  30. 30. Tech provider for Japanese chatbot
  31. 31. A new job created
  32. 32. A new job Creating couples every day
  33. 33. Thank You

Editor's Notes

  • Hi everyone
    My name is Elisabeth Mouchy and I am chatbot product lead at Meetic – For those who don't know, Meetic is the European arm of Match Group.
  • Today I want to talk to you about love. Because, yes, APIs can also help you find love.

    In 2016, a new love coach was born. Her name is Lara. Lara is amazing. 
    In her first year, she was already able to understand what you say in French and English. 
    In her second year, she learnt how to speak and understand 8 languages. 
    In her third year, she was able to speak with a clear voice. 
    And in her fourth year, she become a fully scalable dating coach, while helping give birth to a Japanese love coach. And yeah, Lara is an AI. Lara is a chatbot.
  • Let’s go back to the beginning.
  • We started Lara in 2016 when Facebook integrated the chatbots into messenger. It was a very good oppportunity for us to test the traction for a dating chatbot.
  • For this quick test we use Google tools for chatbot, called Dialogflow. Dialogflow is non-linear conversational design tool that allowed us to create a simple chatbot without many ressources. We also developed a simple middleware that connected Dialogflow with Meetic API.
  • The usecase proved itself. We discover that a conversational flow improves the registration rate by 30%,
    which is huge compared to previous increases in the industry.

  • So we decided to continue Building Lara.
  • The first real usecase that we wanted to develop was for the users to be able to search for a profile, which is the minimum use case that you could think of in the dating world. 
  • But to do that, we needed a new service, called NLP for Natural Language Processing. NLP allows us to understand what a user says in a natural language and transform it into a computer-understandable part. Here is how it would go
    On a fait notre propre NLP – on voulait degager dialogflow
    [description flow]
  • For that purpose, we needed to understand… NLP block
  • For that purpose, we needed to understand… NLP block
  • For that purpose, we needed to understand… NLP block
  • For that purpose, we needed to understand… NLP block
  • For that purpose, we needed to understand… NLP block
  • For that purpose, we needed to understand… NLP block
  • For that purpose, we needed to understand… NLP block
  • The NLP stack allows us to also understand user who would want to refine their search by saying stuff like “too old”, “younger”, “only brunette”, etc.
  • It also allows us to add a layer of smalltalk, which is exactly like in real life. Because it’s real people talking to lara, sometimes they tried different sentences like…
  • From then, Lara was working great. People loved talking to her, but we felt like we could do more.
    So to sustain our ambition, we decided to Optimize our system. 
  • So we internalize the tools that we were using, and stop using Dialogflow to develop our own conversation design tools.
    This tool is composed of 2 elements: one is t
    he interpreter, working like I explained before, and
    the other is the back office, that allows a person to create the chatbots’s conversations.
    Managing the backoffice is a complex task, that required a full time person dedicated to it.
    That’s why, in our team, we created the role of Conversation Designer. 
  • The conversational designer is half product, half tech.
    half product because she needs to deeply understand who the user is and how to talk to them, as well as having a taste for creating enticing scenarios, like if we were in hollywood :-)
    Half tech because the role is very technical manipulating elements such as variables, parameters and functions.
  • So this new role and this new stack allows is to translate and deploy Lara in more European languages.

  • Then we wanted to try something new.
    Having Lara on Google Home was very different than having Lara on FB messenger, because the conversation design doesn’t allow for buttons and needs very precise questions to get very precise answers from the user.
    So we developped totally new scenarios. []

  • Ok now what? We already developed new scenarios and we felt Lara was almost like a real dating coach. So we decided to push even further to scale her up to a full virtual dating coach chatbot.
  • She was already able to suggest profile, so we added icebreakers so….
    She was already able to give the right dating tips, but we added even more depth to the profile tips so she can actually help you fill out your profile.
    And we also added customer care. And we wanted to do all that for all Meetic users, for Lara to be at the heart of Meetic dating experience.
  • To develop this powerful Lara, we needed lots of focus. So we decided to stop Google Home, stop Facebook Messenger and stop all other languages than French and English, to fully focus on the dating coach Lara.
  • So we removed Google Home and Facebook, to be able to focus. We also removed other languages, to keep only Fr And En.
    We BUILD OUR own SDK in JavaScript environment for Meetic apps which allows only 1 development for all platforms
  • After a year of trials and errors, we arrived at a point when we could finally globalize our Lara.
  • So we deployed her again in 4 other languages, to reach 6 languages.

  • And finally, we help our Japanese colleagues launch their own Japanese Lara, as a service provider.
  • Our technical stack was ideal for that as we were able to only provide the conversation design service.
    The Japanese team had their own environment, so they were able to code their own middleware
    and they were also to create and connect their own Japanese NLP.  
    So we just provided them with the interpreter and the back office and train them to use both.


  • We have created a fully scalable dating coach, that can speak 6 languages, but could speak more and send about 2M messages each day.
  • Our tech is used in Japan for a Japanese chatbot and we can’t event understand what she says, but we enabled that
  • We’ve created a new type of jobs: conversational designer, that we know is a job of the future

  • But most importantly, every day we help singles discover other singles, talk to each others, and meet. And that’s the most important part. Because even if Lara is virtual, the love she helps the couple to feel, is, this time, for real.

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