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The retail data landscape

  • Katelyn Ares
  • 4 min read

Personalised marketing is not the future. It’s the present.

Already, 71% of consumers expect their interactions with companies to be personalised, and 76% get frustrated when they aren’t, according to McKinsey research. And this translates directly into better business performance. The same McKinsey report also found that more than three-quarters of consumers surveyed said personalised communications made them more likely to purchase from a brand, more likely to recommend it, and more likely to buy from it again.

The challenge is that this sort of personalisation requires data. And, as we covered in my last blog post, the problem with data is that it’s unevenly distributed. The people who need the data aren’t always the people who have it. The dramatic growth of ecommerce sales from the pandemic has only accelerated this challenge for the UK retail industry. As retailers rapidly have matured their business online, the data disparity internally has only grown.

This is where many of the UK’s retailers currently find themselves. They might know about the data opportunity and they might have started thinking about how they can use the data they have. But they don’t know how to build a 360º data capability that allows them to derive insights, build audiences, activate at scale and measure media effectively.

First steps and first-party data

One of the things I talked about in my previous post was the initial steps retail marketers can take on this journey: 

  • Assessing the business’s goals and identifying where a lack of data is preventing those goals being reached; 
  • Building a wish-list of data;
  • Setting mini-milestones to help measure progress towards those business goals. 

Once you’ve done all this, you can start thinking about where the data you need is going to come from. 

The first thing to consider is what data you have today, and what you could collect in the future from your customers and prospects. This is usually known as your first-party data. To avoid confusion, it’s worth remembering that some organisations – notably Forrester – refer to first-party data as the data you collect from your customers’ behaviour on your website, your apps etc, and define the data that your customers “explicitly and proactively” share with you as zero-party data. 

Whichever definition a business adopts (here we will use first-party data), there are a number of things to bear in mind.  The first is that a number of different parts of the organisation will be collecting first-party data. For example, your web traffic data may be collected by IT, transactional data by an ecommerce team, complaints and returns by customer service, and so on. So when looking at your data wish-list, look internally first and assess if you can source that data from another part of the business where that data is being collected and stored already. 

The second issue is that, even if you source the right data internally, you may not be able to easily access or take action on it. In my first post, The Retail Data Opportunity, I talked about how businesses have typically started collecting different types of data at different times as technology, the organisation and the industry has evolved. The result is data stored in different places, in different systems that aren’t linked together, making internal data collaboration all but impossible without some investment from IT. Insert dreaded IT backlog memes here. 

Finally, what permissions have customers granted around the use of all these different sets of data? This is where legal and compliance teams and your DPO come into play. They are not your enemy. They are your friends! They are there to protect the business and marketing is there to drive the business forward. Close communication and collaboration here will make or break your data maturity journey.

Looking outside the business

So what do you do if you don’t have or have access to your wish-list customer data and are at the very beginning of the conversation with your DPO? This is where third-party data can be incredibly valuable, that is sourced from Premium Data Providers with robust privacy controls and governance of their data.

Premium Data Providers manage consumer datasets such as demographics, interests, persona, in-market buyer signals etc. It can fill the gaps in an organisation’s data, and enable marketers to leverage the right customer insights and make smarter marketing decisions. This enables marketers to rapidly build a foundational data strategy to enable customer intelligence and then validate those audience profiles through media activation & measurement tests. 

Finally, there’s second-party data. If you sell branded products other than your own, or you work with other complementary retailers or brands, data partnerships should be a win-win. This may be familiar to you already as Retail Media Networks have risen in the press lately. However, there is a simpler use case here. For example, brands Crocs and Disney already collaborate on a limited edition shoe collection, selling both in Crocs & Disney owned stores. What if Disney could, in a clean room environment following all necessary privacy requirements, share their customer data with Crocs to leverage for their Facebook advertising? What if the data collaboration could lead to a significant sales lift where both parties benefit equally?

Data privacy and compliance here is critical, but the technology now exists to allow data from two (or more) parties to be combined and activated. That way customer privacy is protected, but each brand benefits from the others’ data.

Once you’ve identified where the data you need is going to come from, you can start putting your strategy into action. In my next post, I’ll be outlining what organisations should think about and the questions they should ask themselves (and maybe their vendors) to have the best chance of success.