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Proving the value of customer data

Proving the value of customer data and that it's worth investing in can be tricky. Quick wins and a SMART data approach help.

Proving the value of customer data: What stands in the way?

It can be hard for retail leaders to see the value of customer data and that investing in it is important. In our view this has a lot to do with the time it’s seen to take for benefits to materialise. According to one retailer interviewed in a PWC Global Master Data survey:

“Master data projects require an initial investment; we only see the results in the medium term”

Those in leadership need to deliver results quickly. This is why many retail leaders avoid tackling something on their watch, which may not obviously yield immediate returns.

Another challenge exists in the approach taken to leverage customer data. There's an increasing number technologies available which can house, integrate and analyse data. But the vast majority of these tools require skilled resources to know how to prepare, cleanse and even segment data before it is introduced to such tools. They also require knowledge of how to analyse this data once it's in the tools, to decipher patterns and insights that are meaningful and useful in driving commercial opportunities. There is no real discipline around how to analyse data commercially, the focus of the tech companies tends to be more about how to make data look nice in dashboards and reports. We've certainly come across a number of businesses, who have invested in BI technology, yet who still feel that they don't get enough value from their customer data.

So there are two issues: time constraints and capability constraints.

What needs to happen? 

To create stronger buy in from Leadership teams, they need to see how investing in customer data will deliver results. Developing a capability around customer data and commercial insight delivers incremental sales without question. Demonstrating value generation through focussed, "quick-win", proof-of-concept projects is a great approach to prove investment to an executive team. It gets around the issue of time constraints as results are delivered quickly.

Working in a focussed manner can also help getting around the issue of capability. It forces you to keep things simple and only about the specific data variables necessary to answer the problem - what we call a SMART data approach. So you start with the problem and work backwards to what data is needed, rather than starting with a forest of data and hope that something interesting will materialise as you trawl through it.

Gaining buy-in from the wider organisation

Gaining buy-in also comes when leaders can see how customer data can be of use to multiple functions within the business; not just Marketing, but buying/merchandising and store operations too.

Each of those teams need to have a simple, clear understanding of how they will benefit from the investment in customer data. If value has been proven with one team via a quick win project, then the approach is far easier to replicate across other teams who want to share in the success. It's a matter of getting these other teams engaged and thinking about how some additional customer knowledge would make their decision-making better.

A statement like this can help: "I'd do X better, if I knew Y about our customers”, where 'X' is a specific commercial decision they have to make that can impact the customer experience and sales. 'Y' is therefore the piece of information that would make that decision better. This tells you what data is needed in order to generate that information.

As these quick win projects continue, an integrated database can be built in parallel to provide answers to commonly-asked, important commercial questions on an on-going basis. This is an efficient and cost-effective approach to take, whereby sales are generated through quick win projects, buy-in develops from across the business and a data asset is developed which will increase the value of the business.

 

Article courtesy of the George Bailey Editorial Team, written by Will Young