PERSONALIZED TRAVEL RECOMMENDATION CHATBOT

Our journey

Our client is a Polish traveling marketplace, where travelers can get in touch with different travel agents from partnering agencies to select the best trip. The primary sales channel of the client was their website. But, with the recent trend of communicating with businesses via social networks, the company decided to use Facebook Messenger chatbot as an additional sales channel. Apart from providing a more personalized booking experience for travelers, Facebook Messenger chatbot also become an additional channel for monetization since the company offers the chatbot integration to partners who want to stand out from others on the list. 

The client hired us since they were inspired by AI Versus, a chatbot project we participated in. 

Project key facts

Setting Goals

To achieve the client’ business goals, we outlined the main requirements for the chatbot MVP:

• Integrate the chatbot with the client’s databases of partner agencies
• Create a chatbot flow to help travelers to search for trips
• Integrate search filters that will include the following parameters:

– Dates 

– Number of adults 

– Number of Infants

– Meal 

– Hotel stars

• Allow the chatbot to switch to a human agent

How we did it 

Step 1. Development of an authorization page for agencies

• We created the authorization page design and integrated the default Facebook authorization functionality for partnering agencies.
• We built a chatbot admin panel using Sonata and a guide for the client on how to use the admin panel. 

Step 2. Development of chatbot flow

• The main goal was to empower the chatbot with scripted answers for all possible questions since the MVP scope did not include open questions.
• Each change in the chatbot was carefully reviewed and tested by the Facebook development team since the social network’s main concerns were user security and privacy. 

Step 3. Integration with Data Service

• We integrated the chatbot with the client’s API Data Server to show relevant trip search results presented in the clients’ databases. 
• The Facebook team requested the client company registration documents and a chatbot MVP demo. 
• Then, the Facebook team gave us a list of changes to implement before the chatbot launch.  

Step 4.  Cloud server integration

• Our DevOps specialist created scripts for the project structure deployment to the client’s servers. 
• The clients could not estimate the workload to the server, which impacts the workload testing criteria and the client infrastructure for the project deployment, therefore, the server cost. Thus, we decided to use Amazon Web Service as a cloud hosting solution. 
• Finally, our DevOps deployed the app to the AWS client’s account.

Technical details 

• Facebook Messenger as a chatbot development platform 
• Amazon Web Service as a cloud hosting solution 
• MY SQL for chatbot localization  
• Sonata for chatbot admin panel 
• IBM Node-red powered by Node.JS as an orchestrator for microservices and bot flow logic 
• Databases from the customer’s side

The future 

Currently, the travel chatbot MVP is in the final stage of testing and soon we will launch it on the client’s Facebook Page. With time, the client expects to integrate the following business logic:

• More detailed search filters
• In-chat payment
• Scheduling the call with a travel agent.

Denys Vetriak

administrator