Marg Personalization Engine

Personalization Engine Description

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 relevant 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 are.

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 cognizance 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 engine takes into account their historical preferences and marries them 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 behavior in the current session to deliver the most relevant recommendations. And that results in greater conversions - and consequently - greater revenue.