CASE STUDY

How Tatvic Analytics reduced CPL for Royal Enfield on Facebook

client background

Client Background

Client Name: Royal Enfield
Client Domain: Two-wheeler Manufacturing Company
Headquarters: Chennai, Tamil Nadu, India
About the company: Royal Enfield is the oldest iconic motorcycle brand in continuous production. It’s an Indian multinational motorcycle manufacturing company, headquartered in Chennai in India.

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    problem

    Challenge

    • High Cost Per Lead on Facebook
    • Not able to receive an authentic target audience for campaigns
    approach to solution _ hypothesis

    Approach to Solution

    • To Optimize the Facebook campaign’s CPL, we passed fbp and fbc id data to the Google analytics ecosystem. The data flowed to BQ through that ecosystem.
    • On receiving the data in BQ we are mapping it with scored audiences of Lead Scoring and PredictN which will give us the propensity-wise bucket audience list of  Facebook Users.
    • After creating audiences, it was added to the client’s Facebook ecosystem. It helped create and utilize the FB audiences and use the same in order to optimize their CPL and campaign performance.

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    Results

    Results

    Tatvic Analytics team helped the RE team to gain wonderful results:

    • Compared the CPL for their Always-On Campaigns with Lead Scoring and PredictN campaigns for the same month (June)
    • Reduced CPL by 26% for PredictN campaigns and 39% for Lead Scoring campaigns
    • Created audience for RE with the help of scored data in BQ

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