Case study | 2 mins read

Omnichannel personalization for targeted revenue lift

Client:

A leading APAC-based SuperApp platform expanding into food and grocery verticals.

Challenge:

The client wanted to accelerate growth in its food and grocery verticals while expanding customer lifetime value beyond its core ride-hailing business. Although the platform had extensive customer data — including purchase history, journeys, promotions, and engagement — it lacked a unified omnichannel view and a systematic approach to personalized cross-sells or up-sells.

This created four key challenges: identifying the next best product for each user, leveraging ecosystem insights to drive penetration into new verticals, extending customer value across categories, and deploying scalable, automated personalization. Without solving these, the client’s communications remained generic, and the opportunity to maximize revenue per user was being lost.

Solution:

eClerx partnered with the client to build a Next Best Action personalization engine, tightly integrated with its Martech automation stack, to enable hyper-personalized engagement and measurable revenue growth.

We began by unifying behavioral data across all customer touchpoints, giving a holistic view of users with diverse buying and browsing patterns across multiple categories. Machine learning models were then deployed to analyze purchase and browsing behaviors, identifying which products and categories were most frequently bought together. This insight powered a recommendation layer that generated user-level personalized actions, ensuring precision in targeting.

To activate these insights, personalized communications were delivered seamlessly across multiple channels. These messages were tailored to individual preferences and behaviors, creating an engaging, omnichannel experience that drove both cross-sell and up-sell conversions. With this scalable framework in place, the client could now maximize the value of its ecosystem data and expand into new verticals more effectively.

Impact:

  • 12% higher conversions from personalized recommendations
  • 15% increase in campaign click-through rates
  • 10% greater penetration in the food and grocery verticals
  • 8% uplift in Revenue Per User (RPU)

By combining unified data, machine learning, and omnichannel activation, eClerx enabled the client to expand customer lifetime value beyond ride-hailing and accelerate growth in new verticals.

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