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When 5 > 600. How many products does the shopper really need?
-INSIGHTS · CASE 5/600After my talk at the Prodaja na policah conference, I often heard one sentence in conversation: “We’re cutting our range too.” Or: “We know we have too many products in our portfolio.” At a time when discounters are advancing relentlessly, in Slovenia too, that is understandable.
Yet cutting the range only makes sense if it lets the remaining products flourish. And if it frees up space for new successful products.
Cutting the range is not the end goal, but a lever for reaching the real one: a really good offer that shoppers like to come back to.Why are sales falling?
This case comes from a real store. A supermarket, a seasonal category, 1,259 products with sales. Sales value over the last twelve months: −7.3%.
Every organisation has a ready answer to a signal like this: a promotion, a lower price, a new supplier. Or, more and more often lately, a shorter range. We first looked at how the category was actually built.
Five hits and 600 products in the tail
The five best-selling products sell roughly as much as the 600 weakest ones combined. On average, one hit sells as much as about 115 products from the tail. The bottom 30% of products bring in only 6.2% of unit sales.
This is the insight that works like a key. It reveals the hidden potential for category growth. But it doesn’t yet answer why sales are falling. It shows how the category is built, not what to do with it.
The first reflex: cut the tail?
Faced with a picture like this, almost everyone has the same reflex. Pareto says the tail doesn’t work, so we cut it. In range management this is what a price cut is in sales: quick, proven, and often prescribed blindly.
Cutting blindly has a cost you won’t see in the spreadsheet. The tail also holds products that are the very reason shoppers come to you. Cut them, and it’s not the spreadsheet that misses them. The shopper does.
Where is the potential hiding?
So we put the data next to two other views. The store, seen through the shopper’s eyes, showed:
a) an extended range with very poor rotation, a dusty category tail (and dusty quite literally),
b) hit products in the wrong place,
c) poor visibility during the main season, when the category generated most of its turnover.
And in this category the shopper doesn’t decide from a list, but when looking at the shelf, mostly in a short seasonal peak.Only together did the three views reveal the real problem: the hits were invisible exactly when shoppers were looking for them. A problem worth solving first.
What did we propose to this retailer?
Not a single measure, but a set of four coordinated levers. A shorter tail frees up space. Stronger heroes fill it: more space, a second placement, reliable stock. A sell-through protocol with clear steps makes sure no stock is left once the season ends. And seasonal visibility makes the hits visible when the opportunity is greatest.
Each lever on its own would only do half the job. A cut without stronger heroes just empties the shelf. Heroes without the season go unnoticed. Only connected measures move the category.
What happened after the reset?
Fewer products, less stock, more sales. With 40% fewer products, sales grew by 10.4%. Sales per product rose by 84%, and stock fell by 70%.
The result matters, but the recipe isn’t universal. In this pilot the set of decisions worked because it was tailored to the role of this particular category at this retailer. A low starting level of order (the “dust”) also helped. That is exactly why the next question matters more than the result:
What if we looked at the same Pareto curve in a discounter, a supermarket or a specialist store? Would we make the same decision?
Note: Stock estimated from shelf measurements.
Would it work for every retailer?
Not necessarily. The same Pareto curve can justify three different right decisions for three different retailers. Picture the following:
The discounter cuts hard and bets everything on the heroes, while also making the most of the season.
The supermarket, as in our case, strengthens the heroes and trims the tail, but keeps its relevant part.
The specialist keeps the tail, because it offers certain kinds of products you won’t find elsewhere. Its risk is offering almost the same as the supermarket – and with that, losing its relevance for the shopper.Same data. Different shopping missions and strategies. And so, different decisions.
The data tell you where the problem is. Which lever to pull is a decision no dashboard can make.
And what about suppliers?
If the retailer’s strategy drives the decision, the supplier has to know that strategy before coming with a proposal.
The same supplier will propose fewer SKUs and stronger heroes to the discounter, heroes plus the relevant part of the tail to the supermarket, and to the specialist a breadth the shopper can see and understand. A proposal that would suit every retailer usually suits none.
When the retailer announces the cut
Picture a conversation between a retailer and a supplier.
Retailer: “We’re reducing the range in your category. We’re delisting 30% of the products.”
At that point, the supplier has two paths.
ADefend at any cost“Please keep our listings. We'll offer an extra discount and co-fund promotions.”→ It may work in the short term. In the long term it means price pressure and a devalued brand.BWhat is the most we can contribute?“We understand you want to free up space and cut stock. We propose 40% fewer of our products, two expanded heroes and moving part of the range online.”→ The outcome is a shared KPI, and perhaps an agreed pilot in 10 stores.Does the supplier’s proposal fit the retailer’s strategy and KPI?
Where is your brand?
The wave of range cuts won’t stop. The question isn’t whether your retailer will cut, but how. And whether you’ll take part, to strengthen the category.
Don't cut before you know what you can strengthen.
● FREE WEBINAR
How to find the right lever for category growth?
The right diagnosis. The right levers. A big shift.
Retailers are cutting their ranges. But a category’s greatest potential may lie not only in the products we remove, but also in the ones we can strengthen. Using the real 5/600 case, we’ll show how data, a look into the store and an understanding of the shopper take us from KPI diagnosis to concrete levers and measurable results. What can your brands contribute?
Thursday, 26 November 2026 · 10:00 CET · 60 minutes · online Registration until 19 November
Leave your name and company in the contact form, mentioning the webinar -
How cutting 70% of category inventory increased sales?
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SITUATION
Cut Inventory. Increase Sales.
How data, shopper logic and decisive assortment action reduced stock without weakening category performance.
This is the case of a toy department in a grocery supermarket.
The case shows how decisive moves reduced category stock by 70%.
How much of this did we pay in falling sales? Zero. Stock reduction didn’t hurt the category sales.
On contrary. The sales increased.
It’s a real case. But not based on the classic optimization attempts.The starting point: a lot of shelf space for category
| Bay1 | Bay2 | Bay3 | … | Bay18 |
|———————————-|
TOTAL ≈ 22.5 mThe category position was good but highly underperfoming in terms of sales per m2.
Before any analysis or optimization, toy Category occupied 18 gondola bays — more than 22 meters of linear shelf space.
With over 1000 SKUs stock rotation was slow.
What Analysis Reveals?
We loaded the data into Sortimana (Omnibus Data Engine) and helped it get to some conclusions.
Despite wide assortment and heavy stock, profitability and rotation were poor.
Below you can see that more than 20% of high rotating stock generated 60% of sales …SKUs vs Sales Volume distribution (source: Sortimana by Omnibus)
… And there was more.
Even with a simplified dataset (1 category, limited attributes), the Data Engine logic revealed where performance truly lived:
- Sales extremely concentrated as the top 2% SKUs generate 22,4% sales volume
- The long tail fills disproportionate stock and space – the last 30% of SKUs bring only 6% of sales
- Seasonality amplifies the imbalance – stock inflates during peak season but never really decreases afterward, long-tail becomes wide and heavy, heavy
Aha insight
Shopper behavior insight: Parents and children buy impulsively; fewer SKUs make choice easier and increase the likelihood of conversion.
And that special superpower moment: if we cut the assortment, we don’t only reduce the stock and release the capital, but we actually trigger additional sales.
Shopper Logic applied
Neuroscientific shopper insights are essential part of Shopper Logic behind the model. Too much choice blocks. That’s called paradox of choice. Shoppers faced with abundant SKUs often feel anxious, delay decisions, or regret their purchase.
Role
Toys in grocery supermarkets are not a Destination category, but a Routine/Impulse add-on.
Strategy
Limit breadth and depth, focus on shelf productivity and impulse hit logic!
Shopper Logic
Parents and children buy impulsively; fewer SKUs make choice easier and increase the likelihood of conversion.
From Insight to Decision/Action
Sortimana Insight 1
Top 10 SKUs generate
55% of sales
Move 1
Cut the long tail
- rotation > 1
- share of sales > 0,5%
- stock clog removal
- match seasonality peaks
Sortimana Insight 2
Long tail items eat space & cash
- The huge long tail with almost 0 rotation
- 70% of stock sits at wrong place
- Low rotation kills profitability
Move 2
Expand the heroes
- more facings
- stronger visibility
- dual location & promo tie-in
- match seasonality peaks
Sortimana Insight 3
Seasonal spike but no exit plan
Move 3
Seasonal Exit protocol
- 0 stock rule post-peak
- 30-45-60 day liquidation windows
- automated monitoring KPI
Before
After
Shelf Space - Before = 18 bays
Shelf Space - After = 8 bays
OUTCOME
STOCK
-70% DOWN
SALES
+10,4% UP
Why this works?
This is not a toy story only. The logic applies to any category with
- strong SKU concentration
- seasonality
- long tails
- limited space
The Data Engine simply makes the logic visible – fast.
Think of household gadgets in hypermarkets, hand tools in DIY stores, toys for dogs & cats in Pet food stores, office accessories in stationery stores, gift books & illustrated editions in bookstores, and many, many more.
These categories don’t suffer from under-assortment. They suffer from unchallenged abundance or be it overstock.
Next sensible step if this resonates?
Sortimana will help you move from insights to impact
At Omnibus, we work with retailers and suppliers to turn data signals into actionable insights — and insights into actual category decisions.
This includes Sortimana (Data Engine), including New Wave Category Management programs, and hands-on workshops focused on real pilots, where theory is checked on-the-go.Frameworks, tools, and workshope designer for real retail impact.
A short conversation to see if a pilot or workshop makes sense.
Challenge. Learn & improve on pilot projects. Then scale for real impact.
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Assortment Optimization: The Power of Relevance
-Beyond a certain point, each additional SKU reduces overall sales and share—i.e., more choice undermines conversion.You’ve probably heard about the jam study, where with 24 varieties available, only 3% of people actually bought one. But when 6 varieties were available, almost 30 percent did. Too many SKUs don’t just clutter your shelves—they block your customers’ decision-making.
Barry Schwartz – The Paradox of Choice (2004)
Too much choice blocks. Shoppers faced with abundant SKUs often feel anxious, delay decisions, or regret their purchase.
Don’t overlook the book’s subtitle: “Why more is less?
In retail, more is not always better — abundance can lower conversion.Behavioral science informs us: “with so many options to choose from, people find it very difficult to choose at all” (a phenomenon Barry Schwartz dubbed “the paradox of choice”).
To cut through the noise, retailers should anchor category roles and strategies in shopper profiles of their customers – asking- why they come to your store?
- what they expect to find?
- how they prefer to decide?
WHICH PRODUCTS ARE REDUNDANT?
A common situation is a shopper walking store aisles of the grocery supermarket. On one shelf, six nearly identical yogurts from different suppliers. On another, dozens of energy bars, many duplicates, with slow movers shoved to the back. Shoppers glance, hesitate, and often walk away. Some don’t even come into the store – they walk straight across the street to the discounter with leaner assortment.
It’s only natural that a retail manager asks:
“Which products on these shelves are hurting me more than helping — and how do I know?”
Which SKUs deserve to live — and which are noise?
The path to clarity lies in connecting shopper logic with category purpose.
CATEGORY ROLE AND STRATEGY
Assortment optimization must begin with clarity of role and strategy, before SKU decisions.
When role and strategy are explicit, SKU decisions are less ad hoc and more systemic.
Pair that with shopper decision logic (as in the Customer Decision Tree), and your roadmap emerges: for each shopper mission, you know which sub-decisions matter (brand, pack size, feature, price), and which SKUs are indispensable.
Assortment Decisions based on relevancy
Shopper Profile
Key shopping mision?
Shopping motive that brings the shopper into your store. What are succesfully met expectations?
Category Role
Why a category lives in your store?
Destination
Routine
Convenience
Image
SeasonalCategory Strategy
How each category pulls its weight?
traffic attractor
margin engine
loyalty builder
convenience anchor
Assortment Decision
Rules for assortment optimization
Breadth
Width
Length
ConsistencyIn practice, you’d overlay a Role × Strategy matrix, then map the customer decistion tree nodes to that matrix to see which SKUs are critical. e.g.:
Category Roles with examples
Destination
Infant formula, baby consumables
must offer breadth and depth across trusted brands—its strategy is traffic & loyalty
Routine
cooking oils
might require fewer SKUs, emphasizing consistency, turnover, and margin — strategy is steady sales
Image
premium category
might trade breadth for curated selection, highlighting exclusivity or signature SKUs.
A CASE OF CHOICE PARALYSIS
Let’s revisit a Slovenian supermarket chain’s baby category (diapers, formula, accessories) — a category that originally aimed to be a Destination draw. Over time, it got bloated:
Choice overload: multiple near-duplicate SKUs every year, justified by supplier pushes.
Shoppers overwhelmed by choices; experienced parents sometimes turned to specialty baby stores.
Operational inefficiency: Store staff struggled with out-of-stocks while many slow movers clogged shelf space.
Low SKU productivity: Profitable SKUs got buried under the noise of marginal ones. Instead of being a beacon for parents, it became a hassle. The baby category lost its clarity.
That pattern, replicated across many categories, leads to:
- Lower turnover per SKU
- Hidden winners
- Shopper dissatisfaction, confusion, lost conversion
- Higher inventory & logicstics cost
Without role/strategy anchoring, each SKU decision is a small gamble. Over time, the bets stack against you.
STRATEGIC & SHOPPER CENTRIC SKU DECISIONS
When your team asks, “Does this SKU support our role-strategy-shopper logic?” the answer becomes obvious, not controversial.
- Destination → broad but anchored in your strongest tiers
- Routine → lean, reliable, no-nonsense
- Image → curated, premium, high-impact
And the clutter dissolves—not by random cuts but by sculpting around shopper missions.
In our Assortment Optimization Workshop retailers bring this to life: they overlay CDT maps on the categories, assign roles & strategies, and make SKU-optimization decisions in guided steps.
The result? Fewer SKUs, clearer shelves, better turnover, and stronger shopper trust.
LESS IS MORE – THE DRASTIC WAY
Take another real life example. During our assortment optimization workshop, we came to a conclusion: streamline toys department in a local supermarket from 19 bays to 6 bays. That’s 70% cut!!!
We could afford this because we applied the shopper logic.
The Toy category example from supermarket
Role
Toys in grocery supermarkets are not a Destination category, but a Routine/Impulse add-on.
Strategy
Limit breadth and depth, focus on shelf productivity and impulse hit logic!
Shopper Logic
Parents and children buy impulsively; fewer SKUs make choice easier and increase the likelihood of conversion.
Assortment Optimization Model (AI supported)
AI assortment Model
Cut relentlessly low-turning SKUS
-70%Outcome
Category Sales
+10,4% UP
Reduced complexity
Easier space management
Clearer presentation
ALVIN – OUR AI STRATEGIC ASSORTMENT MODEL
Over the years we’ve buil many optimization cases and trained our new AI test model named Alvin, with this data. Today, Alvin answers 3 key assortment questions:- Role → Why does this category exist in your store?
- Strategy → How is this category expected to deliver—traffic, margin, image, loyalty?
- Shopper Logic → How do shoppers actually decide within this category?
- Duplicated SKUs: products with overlapping roles (e.g. three nearly identical strawberry yogurts).
- Tail SKUs: items contributing <1% to sales and no unique shopper decision value.
- Overlapping formats: e.g. too many 1.5L colas in similar price bands.
Outcome
A recommendation list of potential cuts, clearly marked as low risk or high risk based on shopper logic
BALANCING BREADTH AND DEPTH OF ASSORTMENT
One of the central trade-offs in assortment optimization is between
breadth: how many different SKUs or variants you offer.
and
depth: how much stock or how many facings per SKU.
Let’s illustrate with yogurt by following highly successful discounters like Aldi and Lidl as an example: they cover breadth by offering key shopper missions—plain natural yogurt, fruit yogurt, Greek style, organic, lactose-free, even sheep- or goat-milk options. Each signals awareness of different shopper needs.
Alexander Chernev – When More is Less and Less is More (2003) Variety can be positive if it is organized and meaningful. Relevant, segmented assortments (good–better–best, clear missions) raise satisfaction and perceived freedom. But cluttered, random assortments undermine confidence and reduce buying likelihood.
But within each segment, they keep depth tightly limited. Instead of six strawberry yogurts across five brands in multiple pack sizes, discounters usually carry one carefully chosen SKU per segment—often their private label.
This creates clarity for shoppers and ensures every facing moves quickly.
The result is not just leaner shelves but also higher turnover and stronger negotiating power. With volume consolidated into fewer SKUs, discounters achieve lower costs, better margins, and the ability to offer aggressive price/value propositions. Shoppers learn they won’t drown in duplicates; they’ll reliably find what they need at the best price.
This strategy demonstrates that assortment optimization isn’t about cutting choice—it’s about curating breadth while limiting depth to make every SKU count. For categories like yogurt, it’s the difference between clutter and clarity, hesitation and purchase.
WHICH ONE MATTERS (IN THE EYES OF SHOPPER)
Assortment optimization is about curating the right mix that matters to your shoppers. The yogurt shelves showed how it works: cover the essential breadth of missions (from plain to organic), but strip away duplicate depth that clutters decisions. But that works as yogurt is a routinely bought category, a staple that reinforces the promise: “You can do your whole shop here.” for different shopper profiles, parents, kids, health-conscious shoppers. Thus it works as routine x traffic driver where traffic leads towards profit driver.
With role and strategy as your compass, assortment shifts from confusion to clarity.
Cluttered shelves slow shoppers down; streamlined ones build trust, turnover, and value. Done right, optimization doesn’t just tidy up your assortment — it becomes a driver of growth and loyalty.
At Omnibus, our workshop model helps teams apply this role–strategy–shopper logic directly to their own categories, using templates and live discussions to make tough SKU choices visible and practical. With Alvin as an AI support, you can test different assortment scenarios in real time—seeing which cuts streamline the shelf without hurting sales. Together, they turn assortment optimization from guesswork into a structured, data-driven, and shopper-aligned process.
Relevant (often leaner) assortments, higher turnover, stronger loyalty.
For more info, explanations & order of the Assortment Optimization Workshop fill the contact form or write me an e-mail simon@omnibus.si!
