COMMENTARY

If you can't measure in-store merchandising you can't make it better

Nov. 9, 2017

Photo: iStock.com

By Erik McMillan, founder and CEO, Shelfbucks

Legendary management thinker and author Peter Drucker is often credited with saying: "If you can't measure it, you can't manage it," meaning you can't know whether you are successful unless success is first defined and tracked. As logical as this lesson is, I am surprised that there are segments of the retailer/CPG relationship in which measurement is neither universally accepted nor applied.

Throughout the 1990s, for example, in the heydays of the dot-com boom, retailers and brands rushed to launch costly websites — and did so having no tools with which to track and analyze traffic or otherwise learn from their customers' online behavior. In the early 2000s, Amazon introduced web analytics and famously changed the retailer/CPG relationship with the phrase, "those who bought this, also bought these."  Today, of course, there is no such thing as a retailer or CPG manufacturer that doesn't employ advanced web analytics.

 

POP displays today are like 1990s websites

That's why I am surprised CPG companies spend billions every year on in-store merchandising campaigns with no intrinsic measurement capabilities. There is no comprehensive tracking of a display through the supply chain to the back of store, and eventually to the selling space in the front of store. Nor is it known if the display arrives after the campaign starts or even before it starts. It's been that way for decades, and the operational and economic fail points are astounding:

  • Fail Point: No cumulative sales lift measurement for display programs. Wouldn't it be good to stack rank all your display campaigns by percent or dollar sales lift? There has never been a comprehensive measurement of incremental sales lift by program.

  • Fail Point: No ability to identify why a program had below average sales lift or how to correct it. For instance, a display campaign that had high sales lift but poor delivery rates to the front of store may be dramatically improved by notifying individual store managers that they should move a display to the front of store because sister stores that placed that display in the front of store had high sales lift.

  • Fail Point: No ability to identify the best set of stores for each display program. Wouldn't it be good to know how to better select the set of stores that receive a specific merchandising display program by analyzing how sales are affected by type of store and geographic region?

  • Fail Point: Dozens (and sometimes hundreds) of programs per CPG have no interactive dashboard to optimize a CPG's portfolio of campaigns for the following year.

  • Fail Point: The overall effectiveness of a program may be adversely affected by SKUs with little or no sales. You could swap losing SKUs after testing a different mix and keeping new SKUs that demonstrated high sales lift.

The need for in-store merchandising analytics is not a new concept. Back in the early 2000s, the former Goliath Solutions, an early pioneer in radio-based technology platforms, was the first company to prove to the retail and CPG industry that automated measurement of in-store merchandising and marketing display execution, compliance and performance ultimately drives significantly increased product sales and gross margins. Fast forward to today and technology power with machine learning, data analytics can provide richer insights. And the cost of the technology is significantly lower.

Just last year, POPAI conducted a study that similarly showed the value of in-store merchandising analytics, particularly for execution compliance measurement. An article recapping this study stated:  "The study shows that 41 percent of stores audited had the planned — properly executed — display.  When displays wee compliantly executed, promotions received a 90 percent sales lift. The presence of a compliantly executed display corresponds to 21 percent of these 90 percent sales lift."

 

Despite industry acceptance of these facts, measurement of whether in-store merchandising displays are placed in the aisles, or for that matter what the cumulative sales lift for these displays, other than on a spot basis, is non-existent over the life of campaigns.

 

History shows in-store merchandising has always been effective for driving sales; however, we also know the practice is significantly flawed, much like those early websites. It's a sure bet that modern-day analytics will position in-store merchandising among the greatest opportunities for retailers and CPGs to reshape the industry and dramatically increase brick-and-mortar revenues.


Topics: Marketing, Merchandising, Retail - Analytics


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