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Drive Brand Loyalty with Analytics

In today’s times of evolving consumer preferences, surge in channels that offer similar choices and competitive pricing, retailers find it necessary to sharpen their customer-centric strategy and retain loyalty for brands.

Driving customer loyalty relies on the extent to which retailers can understand behavior, trends and competition and how they leverage insights at the right time. Our models are built to help retailers run powerful loyalty programs and take better decisions.

Our Approach

Our approach involves analyzing a wide range of customer data to extract insights and predict possibilities. The techniques are modelled to segregate customers into segments based on their buying history, their affinity towards specific products, feedback and opinion regarding the brand. The predictions help clients to initiate Customer Loyalty Programs with minimum risk and maximum returns.
Techniques used

Cluster Analysis

Deep Learning and
Deep Neural Networks

Robust Regression model
building and optimization

Customer Sentiment

Outcomes possible with Loyalty Analytics

Improved customer experience

Run focused loyalty programs across customer segments and geographies to personalize the end-to-end experience and improve engagement

Better ROI on transactions

Drive better customer engagement directed through Loyalty Programs for improved purchases at higher frequencies and increased spend per transaction

Higher LTV and referrals

Create rewards-based recommendation programs for increased Customer Lifetime Value (LTV), higher customer satisfaction levels and improved user endorsements for brands

Increase in brand stickiness

Leverage insights to run better offers, sales across channels for improved brand stickiness and customer retention against competitive offers

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