Tag Archives: store marketing

The Uses of In-store Customer Journey Data – Store Marketing

I’m working my way through the broad uses of in-store customer journey optimization. I started with Store Layout and Merchandising optimization – which is really the foundational analytic capability that this type of data provides. Today, I’ll tackle a use that’s nearly as fundamental – optimizing in-store promotions. For those of you from the digital world, you can think of these two applications as parallel to site optimization and digital marketing optimization.

Promotion Planning

In-store promotion planning is one of those constant grinds in the life of retail analysis. You never stop planning promotions and you never get good enough. With PoS data, it’s pretty easy to measure the single most important aspect of a promotion – how much it sold. It can be a lot harder, however, to answer questions about why something worked or, as is often more salient, why something didn’t. In-store measurement can fill in the gaps around performance measurement AND help develop new promotion and display strategies.

With in-store journey measurement, you can track how and whether a promotion shifted behavior. Did a promotion steer visitors to a section? Did it keep them there longer? Did it drive key milestones like staff interaction or dressing room decisions? With only PoS data, you can easily misunderstand what drove a promotion’s apparent effectiveness. Almost as important, in-store journey measurement provides unique insight into how a promotion cannibalized shopping behaviors and generated new opportunities. When you change navigation patterns in the store, you ALWAYS cannibalize some behaviors and you nearly always disadvantage some sections/products. You also create new opportunities and traffic corridors that might present additional optimization or promotion opportunities. Understanding how cannibalization and redirection worked and whether or not their impact outweighed the promotion benefits is essential to developing sound long term strategies.

And it’s not all about the customer. In digital analytics, we didn’t have to worry much about compliance issues. What you pushed to the website is what was on the website. With dozens, hundreds or thousands of stores to manage, though, pushing content and making sure it’s consistent and correctly deployed is no joke. In-store customer journey measurement provides a strong behavioral compliance check. When a promotion drives specific patterns of behavior, it’s easy to see which stores are roughly following the pattern and which aren’t – given you near real-time feedback on potential compliance issues.

 

Questions you can Answer

  • Why did a promotion work better or worse than expected?
  • How did promotions localize and were there stores that didn’t “play along”?
  • How much opportunity did promotions have to influence shopping?
  • How successful were shoppers who were exposed to the promotion?
  • Did the promotion create new “impulse” opportunities?
  • Did the promotion cannibalize other areas/products and to what extent?
  • For a potential promotion, what are they placement areas that will drive exposure to the right shopping segments?
  • Were there stores that didn’t deploy or correctly implement a promotion?

Next up? A really powerful and oft-neglected aspect of customer journey measurement – staff optimization.

What is in-store customer journey data for?

In my last post, I described what in-store customer data is. But the really important question is this – what do you do with it? Not surprisingly, in-store customer movement data serves quite a range of needs that I’ll categorize broadly as store layout optimization, promotion planning and optimization, staff optimization, digital experience integration, omni-channel experience optimization, and customer experience optimization. I’ll talk about each in more detail, but you can think about it this way. Half of the utility of in-store customer journey measurement is focused on you – your store, your promotions and your staff. When you can measure the in-store customer journey better, you can optimize your marketing and operations more effectively. It’s that simple. The other half of the equation is about the customer. Mapping customer segments, finding gaps in the experience, figuring out how omni-channel journeys work. This kind of data may have immediate tactical implications but it’s real function is strategic. When you understand the customer experience better you can design better stores, better marketing campaigns, and better omni-channel strategies.

I’m going to cover each area in a short post, starting with the most basic and straightforward (store layout) and moving up into the increasingly strategic uses.

 

Store Layout and Merchandising Optimization

While bricks&mortar hasn’t had the kind of measurement and continuous improvement systems that drive digital, it has had a long, arduous and fruitful journey to maturity. Store analysts and manager know a lot. And while in-store customer journey measurement can fill in some pretty important gaps, you can do a lot of good store optimization based on a combination of well-understood best practices, basic door-counting, and PoS information. At a high-level, retailers understand how product placement drives sales, what the value of an end-cap/feature is, and how shelf placement matters. With PoS data, they also understand which products tend to be purchased together. So what’s missing? Quite a bit, actually, and some of it is pretty valuable. With customer journey data you can do true funnel analysis – not just at the store level (PoS/Door Counting) but at a detailed level within the store. You’ll see the opportunity each store area had, what customer segments made up that opportunity, and how well the section of the store is engaging customers and converting on the opportunity. Funnel analysis forever changed the way people optimized websites. It can do the same for the store. When you make a change, you can see how patterns of movement, shopping and segmentation all shift. You can isolate specific segments of customer (first time, regular, committed shopper, browser) and see how their product associations and navigation patterns differ. If this sounds like continuous improvement through testing…well, that’s exactly what it is.

Questions you can Answer

  • How well is each area and section of the store performing?
  • How do different customer segments use the store differently?
  • How effective are displays in engaging customers?
  • How did store layout changes impact opportunity and engagement?
  • Are there underutilized areas of the store?
  • Are store experiences capturing engagement and changing shopping patterns?
  • Are there unusual local patterns of engagement at a particular store?

Next up? Optimizing promotions and in-store marketing campaigns.