CASE STUDY

Increased User Engagement on Quikr Platform by 30% using Tatvic Analytics Cross-Category Recommendation Engine

client background

Client Background

Client Name: Quikr
Client Domain: Classified Advertising
Headquarters: Bengaluru, Karnataka

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    problem

    Challenge

    Quikr receives millions of user traffic in the form of sellers and buyers on their digital properties – majority visit their highly optimized mobile site followed by the Android app. The buyer segment views seller ad listings for different products and service categories like Cars, Jobs, Homes, Bazaar, Services, etc and contacts the seller for further stages of the purchase. Their challenge was to parse the huge user base and understand the preference of a buyer towards a specific category or group of categories. 

    To know more about the challenge, download the complete case study

     

    approach to solution _ hypothesis

    Approach to Solution

    Step 1: Tatvic Analytics created the solution architecture document for the cross-category recommendation engine (CCR) to be hosted on Google Cloud Platform. Tatvic estimated the number of concurrent recommendation requests to be handled at the backend server from the number of users visiting the Quikr platform in real-time in Google Analytics 360. This was necessary to choose the right mix of data ingestion, storage, processing and serving Cloud products for the CCR. 

    This solution is in 5 sequential steps that we have detailed in the Case Study document. Please download the case study to read about the steps that followed.

    Results

    Results

    • 12% Average Session Duration
    • 30% Increase in CTR (avg. across all sections)

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