Driving Personalized Retail at Scale Through Agentic AI Transformation

Overview

A retail brand was facing a loss after failing to provide personalized options to the customers as their client base increased. Traditional recommendation engines were showing repeated items, missing context, and often confusing shoppers.  

And as traffic increased, the gaps became louder. Shoppers were bouncing off, carts were abandoned halfway, and the team kept trying to patch the same issues week after week. Even though the brand had already experimented with multiple personalization tools, nothing worked “in the moment.”  

This is when they reached out to us. Our Agentic AI development solution engine helped them move away from rule-based tools to a system that thinks on its own, understands user intent instantly, and responds with the most relevant action.  

Service
  • Agentic AI Personalization
1

Deep journey mapping across devices

We studied the full shopper path i.e. home page → listing → product → cart, to see where people were losing interest and what repeated patterns were affecting conversions.

2

Building behavior-driven customer states

Instead of treating every shopper the same, we classified them into live “states” based on micro-actions such as comparison mode, casual browsing, high-intent search, price-sensitive browsing, and more.

3

Setting up the Agentic AI loop

We trained our AI agents to detect signals in real time and respond instantly, whether by showing similar items, recommending bundles, or changing information based on intent.

4

Automating repetitive experience decisions

To take the load off the team, we automated tasks such as dynamic product re-ranking, offer placement, and suggestion generation allowing the brand to deliver hundreds of personalized journeys without manual intervention. 

The Problem

The retail platform was growing fast, but the personalization layer couldn’t keep up. Repetitive product suggestions, missed search relevance, and generic page layouts were causing poor engagement. Over time, the brand noticed a very sharp decline with their loyal customers and on the other hand a rise in left carts. Both of these signals showed that shoppers were struggling to find what they wanted. 

Our Role

  • Intelligent product re-ranking based on live intent
  • Dynamic content adjustments
  • Predictive bundle suggestions
  • AI-powered search tuning
  • Real-time decisioning to adapt journeys as browsing behavior changed

Project Challenges

Repetitive recommendations

Customers kept seeing the same products no matter what they searched for, which led to quick drop-offs and low engagement. 

Struggle with intent recognition

Generic tools couldn’t differentiate between a casual browser and someone ready to buy, making the experience feel disconnected.

Limited search relevance

Search results often missed the mark, displaying unrelated products, and causing frustration.

Heavy manual setup for every campaign

The marketing and merchandising teams spent hours adjusting product placements, offers, and suggestions since nothing worked on autopilot.  

The Shift We Achieved for the Brand

Once the Agentic AI system went live, the platform started behaving more like an attentive store associate — guiding, assisting, and nudging shoppers in a way that felt natural. 

41% lift in product discovery

Shoppers began interacting with more items as the AI surfaced with relevant suggestions instantly.

29% improvement in add-to-cart actions

Personalized re-ranking and intent-driven bundles help customers find suitable choices faster.

Reduced manual effort for in-house teams

Teams saved nearly 7–9 hours every week that previously went into reconfiguring layouts and recommendation rules.

What the Experience Looks Like Today

The brand now delivers very user focused and custom experiences to thousands of shoppers simultaneously without relying on manual rules or constant tweaking. Pages feel more intuitive, search results are more meaningful, and the AI agents make sure that every shopper gets a journey that matches what they are looking for in the moment.   

Facing a similar issue? Hurdles such as scattered journeys, low engagement, or personalization that feels more like guesswork, there’s always a better way forward with Agentic AI.