pog analysis

Just the Facts

“We made the best decision with the data we had the time”

Does this quote strike the same nerve or the same PTSD as me?

“Why didn’t you get MORE information?“

“Why did we wait so long to make decision? “

“Who told me this customer fully supported our recommendation?!”

There are very few things in business more frustrating for an Executive or Sales Leader than to make a decision or set direction based on bad or misleading data.  Unfortunately, decisions around trade funding, retail execution priorities or key customer focus are made every day with little, poor and/or misleading data.  Especially when it comes to how our brands are represented at store level.

“I shouldn’t have to rely on my “gut” to understand what’s happening at retail?”

Just the facts Ma’am

The most common problem I faced every year as an executive in the CPG industry was Planogram or (POG) analysis.  Sure, we GET, the planograms from our top customers, even mid-size retailers offer up their POGs after the reset.  Here’s the problem… Try recreating 1,200 unique POGs created by Publix in JDA from a PDF downloaded from their portal.

Who has the labor to do that? 

This needs to be done BEFORE any analysis on Publix can start! 

And now you want me to do this for AHOLD?  Compare AHOLD with PUBLIX? 

This will take our team weeks, even months to complete.  “Maybe I’ll just create “the most common” POG.  I’m sure that will be enough” you say to yourself. 

There is no “common POG”?  Ok, I’ll hire more analysts to help. 

“We have 20 jobs to fill ahead of you.” replies HR

And that’s how we get to…. “We made the best decision with data we had the time”.  ARRGH!

Today this excuse is simply unacceptable when it comes to POG analysis.

AI-Drive POGs from a Picture

This is blog 3/5 in “The Reset” series where I focus on how AI-Image Recognition technology can help better understand everything about the Planogram.  One of the most impactful applications is a product called PIC to POG from Maxerience (A part of
Visiongroupretail.com).  In a nutshell, this technology uses AI to develop an editable POG from a single photo or PDF downloaded from a customer portal.  Those 1,200 unique POGs your team of 6 analysts took 2 weeks to recreate in JDA, now takes an afternoon with AI.

Wash, Rinse, Repeat

As the AI machine automates the manual POG creation process, your team can now gather thousands, even tens of thousands of POGs as they get distributed by the retailer.  If you don’t get a PDF from a customer portal, no problem, take a picture of the PDF at store level or even a picture of the actual shelf.  Instantly the picture can be converted into an editable POG, ready for analysis.  PIC, POG, REPEAT.

Less Gatherer, More Hunter

“Hunting” for insights from data is a better use of your resources, than re-creating POGs.  Dimensions of “what” and “where” can be applied across a chain, channel, region or custom segmentation.  Business questions such as “Share of Shelf”, new to market innovation placement, category space allocation, competitive strengths, even your brands vulnerabilities.    Knowledge is not limited to conventional retailers as this technology can help with poorly measured channels such as Natural, Foodservice, Sporting Goods, Home Improvement and Independent Retail.   Freestanding coolers or permanent secondary location POGs can be captured and analyzed.  These are comprehensive insights that help make informed decisions.  “Just the Facts”, all of the facts.

Make your “gut” call about where you go to lunch, not about your business decisions.

Now that we have an AI Generated POG across your entire customer base in every store, we can leverage the same technology to measure the sales impact.  I’ll cover that over the next blog posts.


For more information on AI- Image Recognition, visit maxerience.com or contact Jason DeRienzo at jderienzo@maxerience.com..

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