How can you make better use of your data?

Businesses do love their data — and we in the marketing sector perhaps love it more than anyone. But no matter what your intention, when it comes to all those lovely ones and zeros, the first step is to understand the data you actually possess and what you can use it for. I’m often surprised by just how few organisations can answer that pretty simple question.

Yes, it’s a broad church. The data we alone deal with at Wunderman might cover everything from customer surveys to social content to transactional data on what, where, when and how your customers are buying your products – as well as digital interaction data showing how and when they visit your website, download your app or click on your offers.

So maybe you need to start by taking a step back. What key business questions do you have that data will be able to answer? Is it how your business is performing? Is it what customers think of you? And once you know what data you’re looking for, how can you refine it and act on it in a way that adds value? Can you, for example, identify your best customers and understand how that segment behaves and what motivates them?

Show me the data: How organisations can make best use of their most precious asset

How can organisations make the best use of their data to drive business transformation; with insights from Simha Sadasiva, co-founder and CEO at Ushur. Read here

Unifying the data silos

Perhaps the most common challenge we’ve run into when speaking with businesses about their data is their inability to combine and integrate different sources to realise the most valuable insights. The data sits in silos across the business. There may be a wealth of Net Promoter Score/customer satisfaction information in one team, but there’s been no effort to attach it to known customer groups.

And yet that’s where the best results emerge. Do you know if your best advocates are also the ones who buy the most products? Only when you have the more granular, integrated information at your fingertips can you understand which customer segments need a satisfaction push, and which product areas need the most love.

Similarly, joining the dots between data silos is the only way to get that clearer picture of customers that any business needs. Are, for example, the customers who visit your website also using your call centres? Do certain customer types prefer one channel over the other, or do they traverse them for different needs in a broader journey?

Or, if the goal is to understand what customers think of you, there is data outside the business that probably needs to be combined with the information you already possess. Ask yourself who dominates particular content topics online and on social platforms, and ask where the white spaces are that your brand could fill in and take the lead.

Business intelligence crucial in unlocking valuable data and insights

In an age where information overload is commonplace, it is crucial that organisations implement business intelligence effectively to utilise valuable data and insights. Read here

Measure what matters

Hand in hand with the data silos, unfortunately, we often find different parts of the organisation using their own individual data streams to measure success in a way that’s not in keeping with the overall goals of the business. Just because a department shows an uptick in their chosen metrics, that doesn’t mean it’s doing what customers want. Perhaps your customer service centre managers are patting themselves on the back for low call volumes, when really the phone number is not visible to frustrated customers in their moment of need.

The business’ metrics might not be your customers’ – and for any brand, the ensuing lack of customer-centricity might be a death knell.

Avoiding the pitfalls

Many companies, thankfully, have realised these potential issues and taken steps to counteract them. We’ve seen more and more adopting a chief data officer: the person/team accountable for unifying data from all parts of the organisation, to better enable it to answer those vital business questions by providing clear access to information in an easily digestible way.

It’s important that your ‘data guru’ be impartial, not just a marketing or product person with a new title. Because they will have to be able to bypass organisational barriers to reach the silos and get what the company needs.

That way, brands can avoid the problem of potentially valuable data left sitting in fiefdoms across the business – and the equally common issue of churning out masses of data with no idea of what is meaningful and what is not. It’s about providing the right data at the right time to the right person, not presenting them with an impenetrable rockface of information and hoping they’ll be able to spot the seam of gold.

5 ways to improve a data strategy

How can CIOs ensure their big data projects avoid common pitfalls? Read here

Find the human context

Perhaps the best way for businesses to make genuinely effective use of their data is to understand from the start that there has to be a human context.

Let’s say the data shows that people spend, on average, twenty minutes on your website. To one part of the business, that might demonstrate that their content strategy is a roaring success; while to another, it might show that people are spending a couple of minutes selecting a product, and then another fifteen or so trying (and failing) to buy it, thanks to an appalling e-commerce checkout system.

Even with all the advances in automation, ‘big data’ and AI in recent years, data benefits from a human pair of eyes. It also needs businesses willing and able to overcome their organisational barriers to identify and combine disparate datasets into a single, harmonious and insightful whole.

Written by David Lloyd, head of data and insight at Wunderman UK
Written by David Lloyd, head of data and insight at Wunderman UK

Editor's Choice

Editor's Choice consists of the best articles written by third parties and selected by our editors. You can contact us at timothy.adler at

Related Topics

Big Data
Data Silos