EPISODE 342 The Data Said Delete It. Here's Why That Could Have Been an Expensive Mistake.

Years ago, a traditional category management report could have told a retailer to get rid of one of the lowest-velocity, highest-margin items we sold.

The assortment math would have looked perfectly reasonable.
The item was small. It did not sell like the core items in the category. If you ranked the category by volume and drew a line after the items driving roughly 80% of sales, this item could easily fall below it.
Delete it.
Except that would have missed what the item was actually doing for the retailer.
That is a category management problem: the item ranking can be right while the decision frame is incomplete.
That is the lesson I want to talk about today, because we now have better data, faster dashboards, smarter algorithms and AI tools that can give us an answer in seconds.
That is useful.
It also makes one skill much more important.
Knowing when the answer is solving the wrong problem.

I’m Dan Lohman. This is Bulletproof Your CPG Brand, where every week I share an expensive retail lesson so you can learn it before your brand has to pay for it.

Now, Let’s roll up our sleeves and get started.

When I worked for a big brand, we sold one of the most recognizable brands in the world. One of out items was in a trial size package. You have probably seen a version of it near checkout. It is the little package somebody throws into a purse, backpack, glove box or suitcase.

From a traditional item-ranking perspective, it was not the hero SKU.

But when we looked more closely, the item was doing something the basic ranking did not show very well.

It was an entry point into the category.

It was an impulse purchase at the check stand.

It carried attractive an attractive margin.

It reminded shoppers of the brand and the category.

And our work showed that removing it could hurt the category because the item played an outsized role beyond its own unit sales. In fact, the item drove traffic to and profitable growth in the category

That is the difference between asking:

Which items sell the most?

and asking:

Which items make the category stronger?

Those are not the same question.

The original report did not have to be wrong. The math did not have to be wrong.

The frame was incomplete.

That is the danger I want you to recognize.

We tend to trust clean answers.

The ranking report says to delete an item.

The category says it needs the space for an item with better sales.

The retailer says velocity is weak.

AI gives you a recommendation with a very confident explanation that justifies deleting the item.

Any one of those answers may be technically reasonable while still being incomplete.

None of those answers ask the shopper what matters most to them and if discontinuing the item might cause them shop elsewhere.

When I look at an assortment decision, I want to understand at least three different things.

First is SOURCE.

Where does the item's volume come from?

If I delete it, does the shopper simply move to another item I already sell?

Do they move to a competitor?

Do they leave the category?

Do they leave the store all together to purchase the item at a different retailer?

Does the item bring a shopper into the category who otherwise would not have purchased?

Second is RETENTION.

What does the item help the retailer keep?

A shopper?

A trip?

A basket?

A need state?

A premium customer from shopping their competition?

A category entry point?

Sometimes a small SKU has strategic value because of the shopper it keeps in the franchise, not because it wins a raw velocity ranking.

Third is INCREMENTALITY.

What disappears if the item disappears?

That is the question a normal ranking can miss.

If the item is mostly cannibalizing another SKU, that is one answer.

If the item creates an additional occasion, a different shopper, an impulse purchase, a higher-margin transaction or a reason not to shop somewhere else, that is a very different answer.

And then I widen the frame one more time.

What does the retailer gain?

Retailers generally care about three things that show up in a hundred different forms.

They need a reasonable profit.

They need more shopper traffic and a higher basket value.

And they need a competitive advantage that gives shoppers a reason to choose their store instead of somebody else's.

So when you recommend adding, deleting, expanding or shrinking an item, I want you to ask:

Does this decision make the retailer's business better, or does it only make the item-ranking report look cleaner?

That one question has changed a lot of decisions for me over the years.

In another major retailer reset, the accepted recommendation called for removing 17 items. Eleven of them were ours. Across more than 2,500 stores, that would have taken out almost half of our business with that retailer.

The recommendation from the category captain looked convincing and every one of the retailers divisions accepted the new assortment. They were making room for their new brand.

I could not reconcile it with the shopper loyalty, category role and retailer performance I was seeing. Our sales were up and my division was outperforming the others.

So I asked a different question:

What would the retailer and shopper lose if these products disappeared?

We rebuilt the story around the shopper, substitution, retailer economics and category consequences.

The 11 recommended SKUs were not removed and I effectively demonstrated to the retailer that the category captains new brand would pull profitable sales from the category while alienating some of their most loyal shoppers.

The final outcome was four additional SKUs for our brand per store across more than 2,500 stores.

Same industry.

Same kind of data.

Very different decision.

This is what I mean by Retail Judgment.

It is not ignoring the report.

It is not trusting your gut instead of the facts.

It is recognizing what the obvious answer may be missing and then connecting the data, shopper, retailer, economics and execution before you make an expensive decision.

AI can help you do that faster.

A great analyst can help.

A strong broker can help.

A sophisticated category model can help.

Use all of it.

Just do not confuse the recommendation with the decision.

Here is the Retail Muscle rep I want you to try this week.

This exercise will also help you defend against a competitor initiative.

Take one recommendation your team is considering or being confronted with right now.

Add a SKU.

Delete a SKU.

Expand distribution.

Cut distribution.

Increase trade.

Raise price.

Whatever it is.

Before you act, write down four questions:

#1 What is this recommendation optimizing?

#2 What important context can it not see?

#3 What would the retailer or shopper lose if we follow it?

#4 What evidence would make us choose differently?

That last question matters.

If nothing could change your mind, you are not pressure-testing the decision. You are defending it.

The easier it becomes to get an answer, the more important it becomes to ask the right question.

If your team has the reports but still cannot agree on what the decision should be, that is exactly why I built Retail Clarity Decision Tools.

Bring me one retailer, one report and one decision. We can pressure-test what the standard answer may be missing and build the capability into your team.

Go to RetailSolved.com/DecisionTools.

The spreadsheet is not the product.

The decision is.

I'm Dan Lohman. Thanks for listening.

Learn the expensive lesson before your brand has to pay for it.

You can get the founder problem finder and the show notes at retailsolved.com/session342