Successfully using data to deliver on business goals is never just a matter of data.
Leveraging data also means thinking about everything that sits around it, from how it’s collected and stored, to the organisational changes needed to support its use, to the tools and technology required to realise its value.
In previous posts, I’ve outlined the opportunity to leverage customer data to accelerate business objectives (The Retail Data Opportunity), how to take those first steps towards building the right foundation (The Retail Marketing Data Foundation), and what the sources of that data might be (The Retail Data Landscape). In this post, I’m going to look at the questions retail marketers should ask themselves – and maybe their data and technology suppliers – in order to set themselves up for success.
As a framework for this, think about the three things you need in order to deliver your business objectives:
- Ability to mine data for insight to make better, more informed decisions;
- Make data actionable to influence the customer journey across multiple media touchpoints;
- Use data effectively to measure business outcomes
Derive Insight
As I’ve stressed throughout my posts, almost any data you have can yield valuable insight into the behaviour of your customers, and almost any data you can add will either increase the value of those insights, or enable new ones. I saw a really simple – but great – example from an online jewellery brand just before last Mother’s Day.
This brand was keen to push their range of Mother’s Day gifts to people who’d opted in to their emails. But they also realised that, for many people, Mothers Day is a sad occasion, for a variety of personal reasons. So the emails they sent leading up to the day included a simple opportunity for those consumers to choose to opt out of Mother’s Day communications. Those that did opt out didn’t feel alienated by the retailer sending them messages they didn’t want. Nor will they next year, or the year after. And, as a bonus, the brand’s relationship with all the other customers receiving that email is boosted by their perceived thoughtfulness.
Make it actionable
There are three questions marketers need to ask themselves here:
- Can I leverage my data for activation?
- Can I scale activation across as many channels as are important to my customers?
- How am I identifying my customers across those channels, so that I can deliver the right message to the right person at the right time?
I’ve touched on the question of permissions around data in a previous post, but it’s important to remember this doesn’t just apply to the data you collect yourself. You need to be certain any data coming from third-party data suppliers or second-party data partnerships has been collected in compliance with GDPR, so that you can use it the way you want to.
The other important aspect to consider is the impending demise of the third-party cookie. Starting in January next year, Google’s Chrome browser will stop supporting these cookies. Marketers will no longer be able to track customers and prospect across the internet via cookies. Like everybody else in media, retail marketers need to be preparing for the cookie-less future. The good news is that this fits neatly into the development of a 360º data strategy that I’m describing here.
Retailers that hold data based on third-party cookies only have a narrow window of opportunity to connect that with the rest of their customer information. Once third-party cookies have gone, the data associated will be unusable, so the time to future-proof what’s already been collected is now.
How far can you go?
Turning to scale, this is where we step beyond data and start asking questions about the business’s marketing technology. Is the data collected compatible with all the technology in the martech stack? In other words, can it be used to identify the business’s customers and prospects across all the channels they use, and deliver the relevant message at the appropriate time?
If the answer is no, remember that the approach we’re discussing here is one of small steps. A retailer in this situation should work out which channels are affected, then prioritise fixing them in order of how well-used they are by customers.
Making it count
The final area to think about is closing the loop. This process is based on helping the business achieve its goals, so it’s vital to know what results each action is having, learning from those results, and trying again. This is the other side of defining those goals; working out how progress towards them will be measured, and what data needs to be collected to do so. In many cases, this will be transactional data, but once again it may well need to be supplemented.
For example, if one of the business goals is to sell to more affluent customers, simply knowing sales have gone up isn’t enough. A way needs to be found to break down sales by purchaser worth, which might come from your own first-party data showing which credit card was used. Or it might come from third-party data showing where customers live, or which supermarket they shop at.
Putting it together
The benefit of adopting the sort of iterative approach I’ve described is two-fold. You’re only making small changes, so the investment required should be small. And because you’re constantly optimising, you should be able to start showing value quickly. This means the process should become a virtuous circle, where better results drive further investment, which in turn drives better results. And it can all start with a few baby steps.