personalization engine

AI Powered Personalization Engine –

Today’s consumer values a positive user experience as much as (if not more than) the cost of the products they’re purchasing. Naturally, they’ve come to expect personalized eCommerce experiences that place them, the customer, at the centre. These personalized experiences may well be a make or break factor. Personalization not only benefits the consumer through a more unique and relevent customer experience, but it also benefits companies by getting in front of the right customers, in the right places, at the right times, with the right experiences. The end result? Higher conversion, AOV, and greater customer retention.   

So how do retailers achieve this? We’ve got the answers in this week’s Your Retail Vue.

Step 1: Audience Segmentation

In order to be customer centric and deliver effective personalization, retailers need to identify which audience segments will bring them the greatest value.  The more meaningful the segments, the more effective your campaigns and business strategies.

This is why top retailers are turning to A.I. to use customer data in ways that result in business impact. A.I. uses behavioral data to create audience segments that are in line with business outcomes. AI generated audience segments can be based on:

1. Behaviour – like discount shopper or high value shopper
2. Attribute preference – like cruelty free (beauty), kosher (grocery), bohemian chic (fashion)
3. Context – like owner of abandoned cart or one-time shopper

What’s more, retailers can also add custom segments like loyalty club members, offline promotion shoppers etc.

Step 2: Dynamic Personalization

Once audience segments have been identified and campaigns have been designed, A.I. can personalize the content within each campaign for every single shopper – and in real time! Dynamic personalization engine takes cognisance of the fact that every shopper is different.

Their intentions are different, their preferences are different and their price affinities are different. AI-powered dynamic personalization takes into account their historical preferences and marries it with their actions in the current session to produce timely and relevant recommendations.  Even if it’s an anonymous shopper with no prior history, the A.I. can capture their behaviour in the current session to deliver the most relevant recommendations. And that results in greater conversions – and consequently – greater revenue.

Step 3: A/B Test

Did you know that retailers that run continuous A/B tests see 2X more growth than others? Constant A/B testing and optimization is key to determining the performance of any eCommerce strategy. A/B testing allows retailers to take decisions backed by data and not just gut-feel alone. 

What’s more, A/B testing helps identify patterns and gain deep insights into shopper behavior. Data-led decision making is the key to sustained growth.

VueX: A Single Platform That Can Power Every Strategy

VueX is the AI-Powered Retail Personalization platform for eCommerce. With VueX, you can build, test and scale personalized shopper journeys that drive retail growth. Whether it’s audience segmentation, dynamic personalization or A/B testing, VueX is a single tool that can power it all – and more!

With VueX, retailers can ensure every shopper sees products that match their preferences, no matter what journey they are on. It’s the greatest wingman eCommerce has ever seen! 


Personalize eCommerce experiences for every shopper with A.I.’s personalization engine helps retailers grow revenue multi-fold with the power of A.I. that constantly learns and re-learns customer behavior as it relates to their business needs.

Your own A.I. personalization engine allows every retailer to customize A.I. personalization models to work best for their business. The systems build nuanced shopper profiles for every shopper by learning from their actions on the site and mapping it to rich product data. Using this, the A.I. finds, and brings to the surface through the shopping journey, the products in the catalog that the shopper would most likely purchase.

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