How Data Can Create Meaningful Customer Experiences

Personalized experiences boost sales, engagement and brand loyalty.

Written by Kristin Foster
Published on Mar. 08, 2023
How Data Can Create Meaningful Customer Experiences
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When it comes to customer engagement, there is no shortage of research on the importance of creating meaningful and personalized experiences for customers. But what exactly does that mean? And how does it translate into actionable steps?

4 Benefits of Meaningful Customer Experiences

1. They save time.

2. They save money due to the discovery of relevant coupons.

3. They help customers find complementary products.

4. They boost customer satisfaction.

Today’s customers expect brands and retailers to understand their interests and needs and tailor experiences as a result without feeling targeted. Meeting those expectations requires a robust data and artificial intelligence strategy that is applied across the path to purchase to create a meaningful and personalized experience. While deploying a data and AI strategy that delivers end-to-end personalization may seem daunting, proven strategies make it possible.

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Defining Meaningful Experiences

In the past, creating a meaningful experience was based on instinct and broad research, if any. Strategies were aimed at selling customers on a product’s features with eye-catching packaging, discounts and advertisements. For marketers, creating a meaningful customer experience involved taking a broad brush to the shopper journey. 

Consider grocery shopping fifty years ago. Perhaps the grocer knew some customers by name, but the experience was largely impersonal. A typical experience back then consisted of browsing a limited selection of items at the neighborhood market and saving a few dollars with a coupon clipped from the Sunday paper.

Consumers today have more choices than ever in where, how, when and what they’re buying. Creating meaningful experiences now requires hyper-personalization at an entirely different level. These days, personalization is interlinked with meaningful customer experiences.

To stand out from competitors, a  retailer’s goal is to meet customers’ specific needs at any time, from their preferred channel (e.g., in-store, online or a combination of the two). Customers also expect to come away from any touchpoint — speaking with an associate, visiting a store, browsing a website, purchasing a product — with the sense that it was a worthwhile investment of their energy, time and money.

 

Why Meaningful Customer Experiences Matter

It’s unquestionable that personalized customer experiences pay off for shoppers, retailers and brands. From a shopper’s perspective, personalization saves time, as consumers can fill a digital shopping basket four times faster with personalized suggestions. It delivers more savings via relevant coupons, increases the discovery of complementary products and increases customer satisfaction.

Research from 84.51°’s Loyalty & Personalization Science shows businesses benefit from personalized experiences. A personalized build-your-cart experience, for example, has shown north of a 20 percent increase in sales compared to a non-personalized experience. It also increases brand engagement and loyalty. Simply put, meaningful customer experiences are good for the customer and business.

 

What Data-Driven Experiences Look Like

Depth and breadth of high-quality data form a foundation for achieving powerful actionable insights that drive meaningful experiences. But having data is only one part of the equation. You also need to unlock its potential. 

At 84.51°, data scientists work with first-party data sourced through the Kroger loyalty program, which includes 2 billion annual transactions from more than 60 million U.S. households. This scale allows 84.51°’s data scientists to build powerful solutions for inspiring shopper discovery, driving conversions, offering relevant promotions and more.

For example, imagine three customers — a first-time Kroger shopper, a price sensitive shopper and a gourmet shopper — with different preferences shopping for ingredients for Taco Tuesday. When they open the Kroger app on their phone, they are each served personalized item recommendations and offers via a personalization platform powered by 84.51° science.

The platform is composed of predictive and prescriptive machine learning algorithms that process thousands of deidentified first-party attributes sourced from opt-in loyalty card transactional data and other attributes such as the day of the week, online behavior, seasonality, basket size, modality and more. The platform scores those attributes to deliver an experience that is relevant and personalized for different shoppers.  

Based on what customers place in their digital cart, the app also predicts each customer’s unique intent and will surface relevant product recommendations based on that intent. For instance, when checking out, a customer who prefers fresh ingredients might receive a notification powered by the “forgot something?” algorithm asking if they would like to add organic avocados to their cart for making guacamole.

Combining shopper insights with data science and technology reduces customer effort and smoothens the path to purchase. Brands also win by getting the right product in front of the right customers at the right time  

Other examples of using data to power meaningful experiences include using similarity modeling and embeddings to find new audiences with similar interests as existing customer groups that are likely to engage in similar experiences. Engagement models can also help predict how select groups will interact with a certain channel, such as the likelihood that they’ll redeem a printed coupon versus a digital coupon, etc. This allows brands and retailers to engage customers with relevant messaging and communications tailored to their preferences and interests.

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How To Build Meaningful Customer Experiences

Forging meaningful connections with consumers in an omnichannel experience that is consistent and personalized begins with these foundational steps:

 

Focus on the benefit to the customer

Personalized touchpoints must genuinely benefit the customer, such as by saving time or money. While creating a strategy to create personalized and meaningful experiences, focus on the benefits to the customer first and foremost. Work your way through the entire customer journey to determine where personalization can be embedded to help the customer. What could add value to a touchpoint? What will save the customer time or create a more efficient experience? Are the promotions or offers relevant to customers?

 

Make it measurable

Tracking and measuring customer interactions and sentiment enables brands to make informed decisions for improvement. Measure the impact of changes along the shopper journey to understand what changed (positively or negatively) in behavior or engagement. Did customers engage differently with a new promotion or channel? Did changes made to underlying algorithms create a more efficient shopping experience?  

 

Enable personalization at scale

While personalization is not a new concept, advances in technology and artificial intelligence now enable retailers and brands to accomplish it at scale. This will require investment in high-quality data capture, technology and science in order to scale the personalized experiences that customers expect.

 

Make experiences more human with data

It is more difficult than ever for retailers and brands to differentiate themselves from competitors and hold shoppers’ attention. Consumers are bombarded with irrelevant messages, emails and ads that fail to deliver value. Data and AI strategies that enable personalized and meaningful customer experiences at scale are essential for breaking through the noise. It’s an opportunity to connect with customers in a way that, frankly, feels more human.

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