Using auto ML and cloud NLP ,this leading travel experience provider is improving customer engagement by creating a personalized experience.

Introduction

The client is a leading travel provider aiming to provide a truly unique experience for every traveler. Based out of Kolkata, India they are working to shift traveling experiences from a one-itinerary-fits-all to creating a personalized itinerary that fits the user’s individual needs. Whether the users are looking for a family vacation or a romantic escape to a popular or off-beat destination or standalone service – the client wants to deliver exactly what the user wants.

Why We Chose Pluto7

This client looked to Google Cloud and Pluto7 to leverage the power of their data and provide a truly personalized travel experience to every single one of their users. With the right blend of Google Cloud solutions and Pluto7’s expert Machine Learning support, this Travel Experience provider was able to deliver a dramatic upgrade to their user’s experience by providing interest-based and more relevent content.

Solution

Travel is a very emotional decision. Travelers don’t want to only go to the place they have chosen personally, they want the whole experience from fooding & lodging to local destinations to be catered to exactly what they want them to be. The client being a travel company aimed at doing just that – providing a 1:1 personalized experience but at scale. The client also recently introduced a new platform for its users to post updates about their own travel experiences in front of the whole world.

The goal of the project was to build a Machine Learning driven recommendation engine which took into account the user’s interests and their likelihood of enjoying a particular experience. To do this the first thing that needed to be done was correctly tag the thousands of posts with relevant experience-related labels. Pluto7 team used Google Auto ML Vision API and cloud NLP to build a solution for classifying all of the existing posts into addressable labels depending on Intent, location and features and Google BigQuery to store all of the information in a near-real time, serverless environment. The second step was to deliver these posts and travel experiences to the relevant users at the right time.

Pluto7 Team used GoogleAuto ML Vision API , cloud NLP and Cloud DataStore to create a personalized (but dynamic) cluster of posts for each user to populate their feed without having to access the full collection of posts – dramatically reducing load time while maintaining a truly personalized experience for every user.

Results

Following the successful POC, Pluto7 began building the data pipeline to manage user experience at scale and also deliver tailored insights to the analytics team.
With Personalized experience for every user and the internal management having full visibility on what’s working and what’s not – the client is aiming to monetize the platform by personalized social travel experiences.

 

Industry High-tech

Solutions Marketing-ml

Challenges

  • No existing data to recommend experiences via logic based rules
  • Fitting the recommendation response with sub-second latency
  • Data maintenance and storage as there was no devops team

Results

  • Increased Customer Engagement .
  • Removed Manual recommendations done by Travel Advisors.
  • Improved Load balancing of generating high-value content in user’s feed.

Products Used

  • Google Cloud Platform
  • Google BigQuery
  • Google DataStore
  • Google Recommendation AI
  • Elastic Search

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