Proof In Practice
Retail Solved in Practice
The obvious problem is rarely the whole problem.
More stores can look like growth while the wrong products are sitting on the shelf. A product can look weak when shoppers simply cannot find it. Sales can rise while productive distribution quietly disappears. And a perfectly accurate report can still point the team toward the wrong decision.
These are short examples of what happened when I looked past the obvious answer, found the missing shopper, retailer, category, shelf, data, or operating context, and helped turn that into a better decision.
Proof first. Then the problem it solves. Then the better next move.
Historical examples may be anonymized or recreated to protect brands, retailers, and confidential information.
Start with the problem
Which one sounds uncomfortably familiar?
You do not need another 40-page case study. Start with the retail problem that sounds like yours. Each story takes only a couple of minutes and ends with one question you can use immediately.
The brand had 16 SKUs. The shelf space wasn't the problem. The mix was.
Specialty flavors were taking shelf space before the brand had secured the category's highest-demand flavor profiles. The opportunity cost added up fast.
Category Strategy / Decision QualityThe report said remove 11 SKUs.
The retailer ultimately gave us four more per store.
Shelf / Merchandising / VelocitySales were growing. Shoppers still couldn't find it.
Better shelf evidence helped save and expand the distribution.
Growth / Distribution / ExecutionGrowth looked healthy. The core was eroding.
A decision system helped reclaim more than $25MM in opportunity.
Data / Shopper / Category ManagementThe database said “not stated.”
Rebuilding the category around the shopper exposed the hidden gap.
OPPORTUNITY
Assortment / Productive Distribution / Trade
The brand had 16 SKUs. The shelf space wasn't the problem. The mix was.
Trying to grow sales with the wrong assortment was making every other part of the business work harder.
The Pain
A growing CPG brand was gaining distribution, but retailers and brokers were building different assortments market by market. In some stores, specialty flavors had earned scarce shelf space while some of the category's highest-selling flavor profiles were missing.
The Better Question
Are we using each shelf slot for the products most likely to build velocity first?
Why this matters
Imagine the category's strongest flavor profiles are chocolate, peanut butter, vanilla, and cookies & cream. Those are the familiar choices many shoppers look for first.
Now imagine your five shelf positions include chocolate and peanut butter — but the other three slots go to specialty flavors like cashew, raspberry, and pecan while vanilla and cookies & cream are missing.
None of those specialty products are bad. They may be what makes the brand interesting.
But shoppers cannot buy a flavor the store does not stock. And every shelf slot has an opportunity cost: if a lower-demand specialty item takes the place of a stronger core item, the brand gives up the sales that stronger item could have produced.
The brand was treating new SKU placements as additive growth when some were really substitutions. Specialty products were replacing stronger core products instead of expanding a productive assortment.
That created problems well beyond weekly sales:
- velocity became harder to build;
- promotions had to work harder because the most broadly wanted items were not always on shelf;
- the shopper experience changed from retailer to retailer;
- brokers had no consistent core assortment to protect;
- forecasting became more fragmented;
- perishable inventory became harder to plan;
- trade spend was harder to align with the products most likely to respond;
- the brand learned less because every retailer was effectively running a different assortment.
What I Changed
I built the assortment around a simple rule: core first, specialty second. Protect the brand's products that align with the category's highest-demand flavor profiles first. Then layer in the specialty items that make the brand distinctive after the core is secure.
The Opportunity
When I modeled the sales the brand could gain by closing the missing distribution gaps on its strongest core items, the opportunity was roughly $15MM.
What the new strategy changed
The assignment stopped being:
It became:
That creates a much stronger foundation for retail growth. Familiar core products give more shoppers a natural way into the brand. If they like what they try, the specialty assortment has a better chance on the next trip.
It also makes promotions more productive. Trade can amplify products shoppers already understand and want. It should not have to compensate for a weak assortment.
The founder lesson
Shoppers cannot buy what the store does not stock. And getting another SKU onto the shelf is not automatically growth if it replaces a stronger one.
Every brand needs its star players on the field first. Once the core is earning its shelf space, the rookies and specialty items can expand the assortment and make the brand more distinctive.
→ 4 MORE
Category Strategy / Decision Quality
The report said remove 11 SKUs. The retailer gave us four more.
A technically convincing recommendation was missing the shopper and retailer consequences.
The Pain
A major retailer was preparing for a category reset. The accepted recommendation called for removing 17 items. Eleven of them were ours — almost half of our business with the retailer across more than 2,500 stores.
The Better Question
What would the retailer and shopper lose if these products disappeared?
What I Changed
I rebuilt the story around shopper loyalty, category role, retailer economics, substitution, and the consequences of removing products customers were actively choosing.
The Outcome
The 11 SKUs were not removed. The final outcome was four additional SKUs per store across more than 2,500 stores.
The founder lesson
A report can be technically correct and still support the wrong decision when shopper, retailer, and competitive context are missing.
EXPANDED
Shelf / Merchandising / Velocity
Sales were growing. Shoppers still couldn't find the product.
A fast-growing item can still look weak when the shelf never gives the shopper a fair chance.
The Pain
An emerging snack brand had earned meaningful retail distribution and was growing quickly. But at one important retailer, placement was inconsistent and shoppers regularly struggled to find the item.
The Better Question
Are we giving the shopper a fair chance to buy it?
What I Changed
I connected distribution, velocity, category contribution, shopper feedback, competitive placement, and the opportunity for a more consistent permanent merchandising solution.
The Outcome
The work helped save the brand from discontinuation and expand its retail footprint. The full analysis and my work cost the brand roughly $8,000.
The founder lesson
A velocity problem is not always a product problem. Sometimes the shopper simply cannot find you.
RECLAIMED
Growth / Distribution / Execution
Growth looked healthy. More than $25MM of the core was missing.
Visible innovation and new distribution were hiding erosion in the business underneath them.
The Pain
Core items were quietly losing distribution across retailers while new products and expansion created a healthier topline story. Teams could see pieces of the problem, but not one national decision view.
The Better Question
Where has productive distribution disappeared, what is it worth, and who owns getting it back?
What I Changed
I built a Core Distribution Recovery System that organized gaps by retailer and item, quantified the opportunity, prioritized the most important losses, and assigned ownership.
The Outcome
The system helped the business reclaim more than $25MM in lost distribution opportunity. The opportunity had a value. The decision had an owner. The team could measure recovery.
The founder lesson
New growth can hide erosion in the business that made the growth possible.
“NOT STATED”
Data / Shopper / Category Management
The database said “not stated.” The shopper said “gluten-free.”
The sales data existed. The category structure hid the opportunity.
The Pain
A brand wanted to understand a better-for-you salty-snack opportunity. In one syndicated database, roughly 68% of the category was coded as “not stated,” “not applicable,” or a similar catch-all for the attributes we needed.
The Better Question
How does the shopper actually define and shop this segment?
What I Changed
I rebuilt the category item by item around shopper-relevant attributes and reran the analysis through that lens instead of accepting the default taxonomy.
The Outcome
The re-segmentation exposed a $146,927 gluten-free potato-chip opportunity gap in the historical account and revealed stronger growth in the relevant better-for-you segments.
The founder lesson
Data quality is not only whether the sales number is accurate. The structure of the database determines which opportunities you are capable of seeing.
The pattern behind the proof
The obvious problem is rarely the whole problem.
The same pattern keeps repeating. The report, sales number, distribution gain, promotion, or shelf result shows the symptom. The missing shopper, retailer, category, basket, economics, assortment, execution, or ownership context reveals the real decision.
Start with what hurts
You do not need every Retail Solved resource. You need the right next one.
Choose the path that sounds closest to the problem in front of you. Each one is designed to help you get a useful result before asking you to take another step.
Build Your Retail Muscle
Start with the problem in front of you.
You do not have to learn everything at once. Pick one problem, use one piece of proof to ask a better question, take one practical action, and build from there.
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