Personalizing customer experiences for each individual across channels is a necessity for retail and CPG brands in this digital age

Hyper-personalized messages, cohesive customer experience, AI for personalization

Personalization Is No Longer Optional

The modern customer demands personalization. If they don’t get it from you, they’re more than happy to see what your competitors can give them.

This is a big shift from how things used to be, pre-internet. Customers didn’t expect experiences tailored to them; it simply wasn’t possible, for example, to print off a catalogue for each segment, much less each individual. And there were far fewer channels to manage. But now, customers crave special attention, immediate gratification, and a cohesive experience across web, social, and other channels.

The secret to this is personalization – and that’s no secret. But what many companies don’t realize is that true personalization is data driven. It’s also more complicated than you might think.

What Makes Personalization So Complicated?

Personalization is recognized, not as the Next Big Thing, but as the Thing We Really Need Right Now. And yet, few businesses are getting truly great results from their efforts. The reason why this is so lies in how retailers and CPG companies understand and prepare for personalization. For example, only a few have defined what personalization will do for their company and how they will go about achieving it. Others may know what their goals are, but they don’t know what technological capabilities need to be in place to bring these goals to fruition.

And even when these points are addressed, there is one more challenge to overcome: the data. Poor quality data, fragmented data, data that’s spread across various areas and locked into separate departments – any of these can hamper personalization efforts. To succeed at personalization, you must first have abundant, high-quality customer data. To get that, you must have a data strategy. It’s as simple as that.

For most companies, their data strategy will require augmentation from third-party sources. But rounding out their built-in customer views with additional info will only create a richer, more AI-ready pool of data. Of course, data sources need to be carefully and skillfully combined for personalization to be effective.

Given that most businesses don’t anticipate this amount of complexity, it’s understandable that their personalization efforts don’t bring the ROI anticipated, either. However, retail and CPG companies aren’t giving up.

CPG and Retail Personalization: Four Real-Life Examples

Smart CPG and retail companies are extending their personalization efforts, exploring and assessing different channels to find the most receptive. They’re also using advanced A/B testing to determine the best messages and offers. Let’s consider some brands that have conquered personalization.


It’s no surprise that this tech giant and mega-retailer also leads the way in personalization. Not only does Amazon have the tech specs, they have the data to power massive personalization efforts. And most of us have seen them at work; the company personalizes customers’ homepages, email offers, and recommendations; much of this is done in real-time, powered by algorithms that consider customers’ behavior, search history, buying patterns, and other data. And this is an effective strategy; 44% of customers make a purchase based on Amazon’s recommendations.

By partnering with Samsung to develop a digital health platform that will give customers personalized nutrition, lifestyle, and fitness recommendations, Nestle has levelled up their personalized nutrition outreach. This personalization effort started with their website; the section “Our Bakers Also Love” generated recipe suggestions based on the ingredients in the recipes users were already browsing. The “Recommended for You” section took things a step further, using an individual’s entire site history (including searches and views) to fine-tune recommendations even further. Nestle then used this data to create hyper-personalized email campaigns, which have led to higher consumption of their website content.

Mars – one of Europe’s most familiar food brands – is starting to put increasing focus on the cutting edge of CPG: personalized nutrition. By agreeing to buy a majority stake in foodspring, one of Europe’s largest and fastest-growing targeted nutrition businesses, it’s expanded the influence of Mars Edge, its own targeted nutrition brand. The personalized nutrition field is all about “the food I want and need, for my body” (to paraphrase the Edge website). In other words, Mars is moving away, at least a little, from the traditional “one-snack-fits-all” and moving towards personalized, data-backed food products. Not only is this an interesting application of data, it’s also projected to be quite lucrative; Grand View Research expects this area to grow 9% each year until 2025.

Under Armour
Under Armour is another brand that’s branching out from what might strictly be considered its product. While this brand primarily sells fitness apparel, casual clothing, and shoes, its app doesn’t focus on sales; instead, it promotes healthy food and fitness goals, makes personalized recommendations, and even analyzes workouts for their effectiveness. This not only provides a valuable service for Under Armour consumers, it keeps the brand engagement high.

These are four very different companies, and on the surface, we have four quite different personalization cases. But look closer. You’ll see that all of them are focused on personalization in one form or another – and in using that to propel their business forward.

AI-Powered Personalization as the Way Forward for Retail and CPG Companies

A recent study by BCG revealed that companies that employed advanced personalization methods could gain a 20% increase in their net promoter scores. Such retailers could also realize a 6-10% rise in productivity and 10% or more incremental revenue growth.

To do personalization properly, AI is a necessity. Satisfying today’s customers’ demands special personalization efforts, and these require processing an overwhelming amount of information at superhuman speeds – a task that AI can render vastly simpler, more efficient, and more effective. Once CPG and retail companies understand how personalization really works, they can choose the correct strategies to meet their aims. They can ensure that they’re getting the right mix of rich data. And they can begin harvesting the benefits of providing highly individual customer experiences.

Authored by Imran Saeed , Director Analytics at Absolutdata, and Promita Majumdar, Marketing at Absolutdata


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