Introduction

How OmniReach partnered with a major B2C ecommerce retailer to design and deliver predictive purchasing, seasonal trend modeling, and AI driven personalization, resulting in improved product discovery and measurable site wide revenue growth.

The Challenge

The retailer had strong traffic and a loyal customer base, but struggled to convert returning visits into high value purchases consistently.

Specifically:

• Product discovery relied heavily on rule based merchandising and static recommendations

• Repeat purchases were driven largely by discounts, reminders, or campaigns

• Seasonal demand and restocking needs were not predicted proactively

• Personalization was restricted to registered users and absent for guest shoppers.

• Merchandising teams spent significant time manually tuning rules to keep relevance fresh

 

As a result, many returning shoppers browsed without quickly finding what they needed creating friction, longer decision times, and missed revenue opportunities.

The retailer needed a scalable, context driven approach that could:

• Anticipate customer needs in real time

• Adapt to seasonality and buying cycles

• Personalize experiences for both guest and registered users

• Deliver measurable revenue impact without increasing operational overhead

 

The Solution

OmniReach partnered with the retailer to design and deploy a predictive AI personalization framework that moved beyond static rules and reactive merchandising.

The solution was built to understand customer behaviouravior, timing, and intent and act on it in real time across the site.

At its core, OmniReach implemented:

• Predictive purchasing models to anticipate restock needs based on historical buying cycles, consumption patterns, and seasonality

• Seasonal trend modellingeling to dynamically adjust recommendations as demand shifted throughout the year

• AI driven personalization that worked seamlessly for both registered and guest shoppers using behaviouralavioral and lookalike intelligence

The system continuously learned from live interaction signals, allowing personalization quality to improve over time while reducing operational effort for merchandising teams.

The Impact

The deployment of predictive purchasing and AI driven personalization delivered immediate and measurable business impact across the retailer’s ecommerce platform.

Key outcomes included:

• 35% increase in revenue driven by higher Average Order Value and faster purchase decisions

• Returning shoppers consistently built high value carts within minutes of landing on the site

• Improved product discovery reduced browsing friction and decision time

• Increased repeat purchases without reliance on discounts or campaigns

• Personalization at scale for both guest and registered users, expanding monetization of returning traffic

• Reduced dependency on manual merchandising and rule-based tuning

Across the site, OmniReach enabled a shift from reactive selling to predictive, intent driven commerce delivering experiences that felt natural to shoppers and profitable for the business.

Summing up

OmniReach helped the retailer shift from rule based personalization to predictive, intent driven commerce. By combining AI driven personalization with seasonal and purchasing intelligence, the solution delivered measurable revenue growth and scalable impact across the site.