With a changing privacy landscape, understanding and connecting with customers in a meaningful, relevant and timely way will depend on retailers having a strong first-party data strategy, and building capability to leverage AI and machine learning to activate that data at scale. 

The ever-increasing criticality of having a first-party data strategy is more challenging for some industries, particularly those that don’t ‘own’ the relationship with the end customer. 

But retailers are in a much stronger position than most. They already have access to a fantastic wealth of first-party data in the form of transactions and customer intent. 

Such high-quality data is fundamental to anticipating - and not just reacting to - evolving and very individual customer needs.  

So how should retailers make sure that they can make the most of the considerable assets they possess? There are four key guidelines to bear in mind.

The quid pro quo

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The first is presenting customers with a clear value proposition for their personal data. In other words, what’s the quid pro quo? 

As consumers have become more aware of their data being harvested, they have hardened their attitudes. Often, this is not so much about privacy concerns but more the irritation they experience when bombarded with irrelevant communications or offers. A degree of cynicism has undoubtedly crept in. 

Yet there are numerous services for which consumers are more than willing to trade their data in return for the value they get. Think, for example, of location data for a mapping app, a loyalty scheme that enables consumers to jump the queue at a coffee shop or early access to sales and special offers.

The more personalized a data set is, the more valuable it is. So to the greatest extent possible, everything a retailer gathers has to be linked to an individual. 

This should extend to anything and everything that it’s possible to catch about a customer. For example, I visited a grocery store that allows customers to use an app and pick up the items they want and walk out without having to wait for a till or cashier. 

What struck me most was not the convenience that most people have commented on, but how it was now possible to join the customer data from the virtual world (online) and the physical world about an individual customer’s buying behavior, a truly holistic view of customers’ interactions with the retailer.  

Squeeze every drop of intelligence from your data

Next, focus on turning data into intelligence. The richness of data that retailers can access is the envy of many other industries. But to make the most of it, they must use machine learning to understand patterns of behaviour and predict what a customer may do next, and then automation to activate customer next best action at speed and scale. These technologies, and more, are going to be vital to succeed in the era of predictive marketing.

Craft, and deliver on, customer propositions that resonate

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Finally, insight is not just for marketing. Having a deep and nuanced understanding of the often very individual needs of your customers will allow you to craft retail propositions that really resonate.  

Not everyone will value the same things equally. Different customers will have very specific needs that need to be met and can make all the difference in building lifetime relationships. 

One great example: a major European cultural institution had been trying to encourage more regular attendance by their most loyal customers, through discounted pricing for advance booking. This had very little impact on bookings.

However customer insight – quantitative and qualitative – revealed that all the most valuable customers craved behind-the-scenes tours and access.  

In the 1990s Virgin Atlantic, in its battle with British Airways for the transatlantic business class market, focused on creating experiences that were valued by business-class customers like collection by limousine and onboard masseuse. They moved the battleground from price to experiences that stressed executives would ‘value’.

The external forces shaping the customer data landscape should not present retailers with a challenge. Instead, it’s an opportunity to take customer relationships to a whole new level. 

They already have rich data to work with, and with the right approaches and tools, they can keep augmenting it and growing its value. 

Getting up close and personal with every customer is the goal. Those retailers that act now will be more than amply rewarded. 

The global technology leaders influencing retail

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Innovative thinking. New ideas. Investing ahead of the competition. These are all requirements if retailers want to stay agile in these changing times. So, who are the individuals leading the charge?

Retail Week’s annual Tech 100 index celebrates the people shaping the new digital retail ecosystem and who will continue to do so in the months and years ahead.

Read Tech 100 today to discover:

  • Developments and trends setting the direction of travel for the industry
  • Which women are leading the digital revolution including Marcia Kilgore of Beauty Pie, Jessica Anuna of Klasha and Jo Graham of Boohoo
  • The start-ups that you may not have heard of – yet – but will want to familiarise yourself with