Proving The Value From Wi-Fi Shopper Insight

We are proving the technology, right?

There exists a huge misconception about what a wi-fi shopper insight proof-of-concept is proving.  Most people believe the collection of data about store visitors needs to be proven.  Frankly, there is not much left to be proven from a technical perspective.  Does it work?  Yes.  Can I get greater precision on location analytics?  Yes, spend more.  This is engineering.  We may need to account for ceiling height or building construction or store layout but these considerations are well understood.  Nonetheless, this tends to be the central topic of IT proofs. 

Most proofs of concept we see are IT proofs and they often fail to find value.  This is because of their inflexibility and their inability to spend time with the stores to learn.  This time spent  learning is required to adjust the approach and tune the technology, a technique we have found to be essential.  The Lean improvement discipline calls this "going to gemba," the place where the work takes place.  If your IT team is running a proof of concept from their cubes at headquarters you might want to adjust your expectations… downward. 

What needs to be proven?

What exactly needs to be proven?  3 things:

1. Will the data give us insight we value?

Wi-fi definitely gives you data.  But, is that data helpful.  For one client we needed to spend time in the stores to develop classifications of shopper behavior, we then implemented rules by which we could group shoppers by behavior and look at relative shopper counts by behavior by hour across stores.  The combination of this retailer's shopper patterns with wi-fi data gave us insight that was immediately actionable by the retailer's district operations manager.  We hear more stories of companies that fail to see value in the data than those that do.  This is a central proof point.  Fumbling here means a significant loss of value.  Nonetheless, the value of insight must be proven or these efforts tend to (and should) shut down.

2. Can we gain shopper cooperation?

The first objection we get to shopper data collection is about shopper cooperation.  I was in a meeting with an organization who wanted to grow in the millennials segment and all but one meeting attendee was a baby boomer.  Predictably the baby boomers (all male) had the typical list of reasons why shoppers would not cooperate.  Knowing that this was not an argument I could win, I turned to the millennial in the room and asked him.  He got a broad smile and said "of course we would join, I get notifications every time I drive by Starbucks and I want them."  Our experience is that there is no real barrier to shopper cooperation.  There is a value perception that needs to be met and that is what needs to be tested, understood and proven.

3. Can we increase sales, customers and or lifetime customer value?

There tends to be a lot of hesitation and consternation about wi-fi enabled shopper insight.  Yet, when one looks at the lifetime value of a new customer,  the hesitation looks more like procrastination.  Few retailers know who is in the store until the customer checks out and know nothing of visitors who do not buy.  We have seen several organizations where 80% of visitors who share information with us were not in the retailer loyalty system.  They were phantoms.  The lifetime value of a small percentage of this group is significant.  But, this value was not evident prior to the proof of concept.  It may or may not be the case for you, it needs to be proven.

The process is as important as the result

The need for proof should not be minimized even if you, the reader, are convinced.  The process of the proof of concept is essential for building consensus among executives.  It is a form of collective learning.  A CEB study found that organizations that gain consensus are more successful at achieving their goals.  We recommend the proof of concept because it builds stakeholder support for post proof adoption.  And, what is success for a POC if it is not adopted?

The reason x-ray technicians do not diagnose patients is because their expertise is getting a perfect image not diagnosing the human body.  IT proofs of concept get perfect images but they fall down when the interpreter of the image fails to make the proper diagnosis.  Producing the data is not enough and the stories we hear from years of helping clients indicate that the technology centric approach is a high risk operation.  Wi-fi enabled shopper insight requires a unique combination of technology and retail expertise which is why our customers choose us.  When our team combines with your team you have the complete package to structure and execute a valuable and objective proof.