How Curate Turns SKU Rationalization Into Store-Level Tradeoffs You Can Defend

When You’re Told to “Cut 15% of SKUs,” but No One Shows the Consequences

There’s a moment most category managers know too well. Someone up the chain decides the category needs to “tighten the range,” and suddenly you’re staring at a SKU list with red marks all over it. The deadline is tight, and the retailer wants clarity, brand teams want room, and leadership is asking for “simplicity.”

The part people rarely talk about is the uncertainty behind every cut. You can remove a slow mover and accidentally pull volume away from the whole category. Or keep a duplicate SKU because it looks safe on paper, then watch it clutter shelves for months. Even worse, you might get asked in a review meeting why your new product selection is missing the exact item shoppers actually buy.

It’s no wonder SKU rationalization feels more like a pressure test than a tidy process.

That pressure gets worse when the team can’t see how one change affects everything else. If you can’t see how demand shifts when a SKU disappears, your plan becomes a collection of hopeful guesses.

Why SKU Cuts Backfire Even When the Logic Seems Solid

Most SKU rationalization challenges come from overlooked tradeoffs:

Confusing variety with duplication derails your plan

If you pass by a beverage cooler, you’ll likely see four pack sizes that all serve the same mission. Two flavors that shoppers treat interchangeably. SKUs that show up differently in reports but behave almost identically once you analyze how they really move.

These duplicates are fighting for the same inch of space, which looks harmless in reports but wrecks balance on the shelf.

One wrong cut can shrink the entire basket

Every category has items that hold it together. Remove one of those too quickly and you’ll feel the dip in more than one line. Shoppers don’t behave predictably when you add or remove variety. Sometimes they pick the “next closest thing,” and other times they walk away entirely, especially in categories with high brand loyalty or limited substitutes.

That’s the part that rarely shows up in tail-cutting exercises. The impact is, of course, missed revenue. But it’s also the follow-on products that never leave the shelf because the anchor product wasn’t there.

Retailers don’t trust SKU cuts they can’t see through

This is also where shelf reality sneaks in. A plan that looks clean in Excel rarely survives a tight aisle or a legacy cooler. If you’ve ever had to “fix the set in the field,” you already know how fast those inconsistencies add up.

Even when the logic feels correct, you still have to justify the move in the language of their stores and their clusters.

The Four Questions Every SKU Decision Should Answer

Category managers make better calls when they treat SKU rationalization as a series of adjustments instead of a math exercise. These are the questions seasoned category managers ask before they touch the shelf.

1. Does this product bring real variety, or just more noise on the shelf? 

Some SKUs don’t add anything new to the shelf. Others hold an entire segment in place. The trouble is that duplicates often hide inside good-looking numbers, and you only see the overlap once you zoom out far enough.

A good rationalization workflow separates the SKUs that genuinely expand the set from the ones just repeating what you already have.

2. If this SKU goes away, where does the volume move?

This is the question that stops most teams in their tracks, because they don’t have the tools to see the impact cleanly.

When a SKU leaves the shelf, its volume doesn’t vanish. It flows somewhere. It might consolidate into a related item. It might shift across pack sizes. It might leak out of the category entirely. These shifts rarely behave the way logic says they should. You only catch them when you look at how the category actually moves.

Without visibility into this flow, SKU rationalization becomes a roulette wheel.

3. Does this product actually fit the shelf in each store or cluster?

Everyone has lived through a gorgeous planogram that only worked for the first ten stores. After that, space constraints and odd fixtures forced teams to improvise. That improvisation introduces new problems, especially when it reshuffles facings or pushes core items out of eye level.

You can’t evaluate a SKU in a vacuum. Once you get into real stores, the shelf tells its own story.

4. Can I explain this change in one slide to the retailer?

If you can’t defend a SKU cut in one clear explanation, you already know the plan won’t hold up under retailer scrutiny. They want simple stories grounded in their own stores and their own shoppers. If your rationale requires a lengthy appendix, something isn’t right.

How Curate Shows What Happens Before You Change a Single SKU

Curate doesn’t tell you what to cut. It shows you what each cut does.

Most teams start by loading the data they already trust. POS. Movement. Store attributes. Planograms. Whatever they usually use to build or defend a set. Once that’s in, Curate’s AI model begins simulating how shoppers behave based on patterns learned from your historical movement.

A SKU that looks unimportant nationally might be the anchor in a handful of high-volume stores. Curate surfaces those pockets so you don’t accidentally cut a SKU that holds a region together.

Seeing where the volume goes when a SKU disappears

Instead of guessing how shoppers will react, you can watch the model simulate the shift. Maybe a slow mover props up a niche segment. Maybe two variants behave like siblings. Maybe a SKU you thought was safe turns out to be holding traffic in the category. Patterns like that surface quickly because the simulation isn’t working off averages. It’s using the relationships it learned from real stores.

Further reading: How Machine Learning Helps Retailers Shift From Batch Planning to Adaptive Assortments

Checking if the “perfect plan” fits real shelves

Curate also checks the shelf the way a rep or reset team would, spotting the gaps that only show up once you're in the aisle. If the set doesn’t fit a specific store’s shelf, the scenario won’t pass the test. This prevents the usual scramble where a promising assortment gets broken during rollout because a shelf is two inches shorter than expected.

Comparing scenarios you can stand behind

Most teams compare Scenario A to Scenario B with manual tweaks and a few assumptions. With Curate, you compare three, four, or ten variations and see which ones hold up under your own rules. Because the model already understands your constraints, exploring ten scenarios takes minutes. You can look at revenue impact, volume movement, space constraints, and the one thing partners always care about: the story behind the choice.

What SKU Rationalization Looks Like When You Test It First

Here’s a simple version of what plays out in live projects.

A category team needs to reduce a set from 120 SKUs to something closer to 90 across their top retailer. Normally that would spark long debates about pack sizes, slow movers, and regional flavors. Instead, the team loads their data into Curate and starts testing.

Two pack sizes show nearly identical behavior. Their cannibalization rate is high, and shoppers switch between them freely. Keeping both drains space that should go to the item shoppers reach for first. Meanwhile, a high-performing core SKU keeps losing facings because the planogram hasn’t been updated in two years.

The team builds a scenario where the two duplicates are consolidated and that space shifts to the core item. The model projects a lift, and the new set fits the shelf across all clusters. The team tests a few more variations to make sure the gain isn’t a fluke. When they walk into the retailer meeting, they show the scenarios, the tradeoffs, and the projected impact.

This is the same dynamic Clorox saw when they ran store-level assortment simulations with Curate. They uncovered a way to reallocate space within the same planogram structure and projected a two percent volume lift and a one and a half percent revenue increase. Small adjustments, strong footing. The kind of story you can tell in one slide.

Want to Run These What-ifs on Your Own Assortments?

If you’re staring at a SKU-cutting mandate or prepping for a tough line review, you don’t have to guess what’ll happen when a SKU moves, grows, or disappears.

Schedule a demo and we’ll walk you through a few live simulations and show how these tradeoffs play out.

FAQ: SKU Rationalization With AI