How Smart Retailers Use Data to Transform Customer Relationships

Retailers are finally getting smart. They realize they can't just rely on physical stores to gather data on what customers want and need — they are now taking advantage of customers' shopping habits in the digital space too. In this article, we'll look at smart data solutions and how brands create customer relationships using them.

What is ‘smart data’?

Smart data is a collection of information to provide insight into a customer's behaviour. This means that data collected from a customer's shopping cart or account is combined with other information, like their location and personal preferences, to give retailers a clearer picture of who their customers are and what they're looking for.

Smart data also uses technology to help extract and analyse this information. Retailers gather everything from POS, CRM and loyalty program data to understand how to target shoppers. This combination can reveal what is working within a complex retail business. For example, data may show that some regions are more sensitive to promotions than others. This helps businesses to understand the nuances of how their customers behave and react accordingly. 

What are the benefits of insightful customer data?

Brands across all industries face the same challenges - impenetrable data and a lack of understanding of it. Furthermore, many businesses have fragmented and siloed data split across multiple platforms. This makes it almost impossible to derive actionable insights. Enter: retailer loyalty programs. Retailers across the world are investing in apps to help with:

  • Understanding customers
    - Collecting customer data to learn what makes each audience go from sporadic purchasers to regular customers.
  • Predictive business analytics
    - Knowing what customers are going to buy and in what quantities helps retailers manage stock and the supply chain.
  • Effective marketing campaigns
    - Analysing what kind of messages work best by understanding which channel, method and timing brings the most ROI in marketing campaigns. 

Examples of retailers using smart data solutions and digital loyalty to improve customer relationships

So, what exactly are smart retailers doing? Firstly, they understand that data is a value exchange. Customers expect an improved shopping experience and retailers receive the insights to help with important strategic decisions around product ranges, pricing and promotions. 

The following brands are among the pioneers of retailers using customer data to increase loyalty, deliver personalized experiences and keep retention rates high. Such companies are no longer putting all their energy into attracting new customers - rather, they are directing their attention on the customers they already have. 


Marks & Spencer

A tough retail market hit Marks and Spencer’s profits in the past few years. But the introduction of a digital-first loyalty program is already paying off. Sparks loyalty attracted over 11 million customers, pulling in banks of data to help the retailer make decisions on product collections and marketing. This move has ultimately helped M&S weather a pandemic and cost of living crisis which is proving to be too harsh for some retailers. 

Unlike most retail loyalty schemes, the Sparks scheme is not based on collecting points to redeem rewards. Instead, the retailer rewards customers ‘unconditionally’ - with big and small rewards to “surprise and delight”. This strategy works to create a positive association for customers every time they shop. 


Supermarket giant Sainsbury's revamped its Nectar loyalty scheme to bring it in line with digital transformation. The loyalty platform provides a holistic view of customer behaviour, enabling the brand to make clear decisions and identify opportunities by analysing how customers engage across different product categories and channels. 

The depth of data collected via the Nectar platform also allows Sainsbury's to understand the patterns that customer preferences follow over time. As a result, the brand can more confidently predict future trends and apply these to business decisions. 

Do coalition loyalty programs still work in 2022?


Co-op's loyalty membership offering has also had an overhaul in the last 18 months. The retailer has taken a different approach by focusing on giving back to local communities. Their program accumulates 2p for every £1 spent in stores. The same amount is donated to local community causes. Customers also get personalised offers on Co-op products and discounts across the organisation such as insurance and funeral services. As a result, the app has seen a 400% increase in engagement. 



French multinational beauty retailer Sephora collects customer data from interactive quizzes and purchase history to create personalised recommendations. Whilst most businesses tackle personalisation on a channel-by-channel basis, Sephora harmonises its offerings across multiple digital platforms for each individual customer. Such strategies have attracted over 25 million members to its loyalty program, which has won many accreditations in the retail personalisation space. 



Online fashion retailer ASOS uses big data to gather a deep understanding of how customers interact with products. The brand analyses products that are purchased by the same customers often and identifies any matching features. This allows them to create very specific personalised recommendations. ASOS also uses machine learning tools to incorporate previous browsing patterns into these recommendations. Such tools empower the retailer to provide accurate upselling opportunities to customers based on their exact tastes and preferences. 

Gathering smart data using retailer loyalty programs

There are many different ways you can collect data via a loyalty program. Card-linked offers are a popular way for retailers with multiple locations to capture data and reward customers. Card linking captures real-time transaction data whilst rewarding customers in the easiest way possible. 

An interesting card-linking use case comes from a recent White Label Loyalty client launch called Tickit. It is a one-of-a-kind loyalty program in Dubai that uses card linking technology to allow consumers to earn and redeem as they shop and visit varied venues within the Emirates. All the app members need to do is link their payment card to an app and they automatically receive points as they shop. It’s a very simple yet clever way to connect with consumers and offer them more value without adding unnecessary complexity. 

Card-linked loyalty apps can also help drive footfall across locations by incentivising movement, which is perfect for retailers who want to bring back business to the high street.


How to get started with data and retailer loyalty programs?

How do you follow the success of smart retailers? Invest in a data and loyalty platform which gives you all of the tools and insights to deliver personalised messaging across the right channels at the right time. This is the foundation of a successful retail loyalty strategy as it gives you real-time interactions and data to build closer relationships with your customers. 

Thanks to the White Label Loyalty platform, rewarding customers for repeat business is easier than ever. No more physical cards and complicated reward fulfilment. Customers shouldn’t have to take extra steps to be rewarded for their loyalty. With the right tools, you can create a rewards program that is frictionless, engaging, and automated. 

Key takeaway

Access to customer data and intelligent marketing technology gives retailers a chance to create meaningful bonds with their customers. Combining this with digital transformation means retailers cannot afford to shy away from investing in digital loyalty. If retail brands don’t make use of this opportunity, their competitors will. 

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Helen Walker

Helen Walker

Senior Content Marketing Executive

Helen is our Senior Content Marketing Executive. She shares valuable information about the Future of Loyalty and will keep you up to date on the latest industry insights...

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Customer Data
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