Consumer Behavior

How data analytics can drive retail customer engagement

Customer engagement research reveals some telling facts — organizations focused on customer engagement saw cross-sell revenue surge by 22% and upsell revenue by 13-51%.

Photo: Adobe Stock

May 9, 2025 by Raman Awal — SVP & Global Practice Head, Mastek

Customer engagement — it is the critical lifeline of success in any industry, and more so in the retail segment. And in today's digital landscape, data and its analysis are undeniable accelerators.

When it comes to getting to know your customers in this digital age, data analytics is the wellspring of success. It cuts out the noise, discovers and explores behavioral patterns, extracts insights for the right strategy and action — all of which boost customer engagement.

Forging the right customer connection for engagement

The digital era of retail has seen tons of data pour in from a wide variety of sources — online browsing and purchase, reviews, emails social media videos, comments and shares, calls to customer support, and more. Structuring and decoding this data dump with the right analytics tools is a great means of identifying and understanding what customers are thinking — and creating emotional connects with them.

Such an approach can enable retailers to unlock the following customer insights regarding purchase behavior:

What is the time they spend on their sites — and what do they search for?
What are their product page dwell times?
What are their shopping cart abandonment rates? And at what point do they drop off?
Do they use the guest checkout option or create an account? Important point, as when customers create accounts, there is a greater chance of returning
If they are repeat customers, what is their purchase frequency — and their average order value?

These are valuable metrics that can measure the extent of engagement and enable retail organizations to craft more personalized campaigns through the right channels, at the right time. Such metrics may also be used to empower sales and marketing professionals with the right conversations with customers and prospects — and further enhance their engagement. Rewards and loyalty programs can also be better designed for customer retention.

Most important, retail companies can differentiate themselves beyond sales transactions to gain a lasting competitive edge.

The multi-faceted dimensions of retail customer analytics

As early as 2021, a McKinsey research revealed 71% of consumers expect retailers to deliver personalized engagement and experiences. Plus, 76% experience frustration when this expectation is not met.

Here is where data and analytics play a critical role — to provide a 360-degree view of the customer journey across various interconnected touch points. Leveraging the right combination of analytics tools and multi-channel platforms can create immense customer lifetime value. And when we power them with artificial intelligence and machine-learning, it opens up immense possibilities to deliver winning insights that firmly cement customer engagement.

Customer behavior analytics unfolds a purposeful picture of customers' personas, their needs, their preferred interaction and shopping modes, etc. With predictive analytics, retailers can take a few steps ahead to forecast future behavior of their clients — and tailor products and services to increase the likelihood of purchases.

For example, Nike's 'Nike By You' platform offers custom sneakers and other personalized products to its customers. Sephora uses AI-powered analytics to personalize the consumer's in-store experience. Customers can scan products to get individualized recommendations based on their skin and hair types — as well as their past purchases.

And then we have text, speech, and sentiment analytics tools that dissect textual interactions (such as emails, social media posts and reviews), and voice interactions (calls, IVR, etc.) with the company. By analyzing the positive, negative and neutral sentiments reflected in such interactions, retailers can make the right corrective and reinforcing actions to protect and enhance their brand value. In the case of in-store engagement, video analytics can deep-dive into interactions in the store to throw light on buyer decision points and customer experience.

Armed with such insights, retail organizations can develop effective KPIs, align data insights with customer profiles and demographics, and design customer engagement strategies across different consumer segments.

Data storytelling, the way to go

When retailers can provide a compelling narrative to consumers with data that is customized to their needs and aspirations, it tremendously elevates the customer experience. Imagine a retail scenario, where every interaction feels personal and curated just for you.

You browse for say, shirts — and a pop-up shows you styles similar to those you explored. You abandon your shopping cart, and immediately you get a friendly message giving you a discount on what you were interested in.

This is the magic of data storytelling. It can

Aggregate real-time data from multiple sources — such as store data, websites, online applications and social media channels.
Clean the data, analyze it, and recommend 'next best' actions — using predictive and prescriptive analytics.
Deliver it to customers through attractive data visualization means and enriching user experience — in the manner that resonates with them, and at the time they need it.

Walmart takes an omnichannel data storytelling approach — through social monitoring they track the consumer reaction to a product, and use this insight to send targeted messages to customers, encouraging them to visit their stores for attractive discount offers.

The retail industry is closely connected to every consumer's daily life. Today, it is an experience-driven landscape, where customers crave for more than just a transaction to demand an authentic connection, and a sense of being understood.

Building strong customer engagement is thus a make-or-break reality for retailers. Data analytics empowers merchants to evolve and positively reshape their customer connects, enhance customer experiences, and drive significant sales and revenue growth.

About Raman Awal

Raman Awal, SVP and Global Practice Head at Mastek, brings over 25 years of expertise in building and scaling successful Data Analytics and AI (DA&AI) practices. He has demonstrated successful leadership through P&L responsibility for global data-focused practices, managing consulting, program delivery, partnership management, and ensuring client satisfaction.

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