How to improve product assortment and identify ineffective store items

Assortment is the set of products a store or company offers its customers. People go to specific stores for a wide selection of goods and fresh products. However, not all items in the assortment are equally effective: some products bring stable profits, while others only take up shelf space and create additional costs.

Assortment analysis is the process of evaluating a product portfolio — by sales performance, profitability, and structure — to understand which products are working, which are dragging on results, and where the assortment doesn't yet match customer demand. It's closely related to two other terms that are often used interchangeably but aren't quite the same: assortment planning (deciding what to buy and stock before the season starts) and assortment optimization (the ongoing process of adjusting the portfolio based on what assortment analysis reveals). In practice, analysis is the diagnostic step, and optimization is the action taken on that diagnosis.

Assortment management is no longer just an operational tool, it's a way for businesses to compete and achieve their goals. The store's main focus is to sell the products it has purchased without excess spoilage or dead stock sitting in the warehouse, since unsold inventory freezes profit and margin for the retail chain. So, category managers build assortment management strategies, remove inefficient products, and revise SKUs.

To deeply analyze the assortment, a category manager needs a set of analytical reports that will allow them not just to see the numbers but also to identify patterns and relationships. They should be able to segment data by various criteria (category, brand, supplier), compare data for different periods, assess the contribution of each product to the overall results, and visually track the dynamics of key indicators.

Assortment Width vs. Assortment Depth

Before analyzing individual products, it helps to look at the shape of the assortment as a whole. Two dimensions describe that shape:

• Assortment width (breadth) — the number of different product categories or lines a store carries. A hypermarket carrying groceries, electronics, and apparel has a wide assortment; a specialty sneaker store has a narrow one.
• Assortment depth — the number of variants (sizes, colors, flavors, configurations) within a single category or product line. A sneaker store that stocks one model in 15 colorways and 12 sizes has a deep assortment in that line.

These two dimensions pull in different directions. A wider assortment appeals to more shopper needs in one visit but spreads inventory investment thin across more SKUs; a deeper assortment serves a narrower audience very well but risks internal overlap between near-identical variants. Most assortment analysis work is really about finding the right balance of width and depth for a given store, category, or cluster — which is exactly what the methods below are designed to measure.

Basic Methods for Estimating the Assortment of a Store Chain

1. ABC analysis — a method of classifying goods into three categories (A, B, C) according to their contribution to the business, typically measured by sales volume or profit. This method can be done on a store-by-store or chain basis. The main purpose of ABC analysis is to structure the assortment to highlight the most popular and profitable goods and categories.

Three categories of goods:

• Category A — priority goods. As a general rule of thumb (the underlying 80/20 principle), a relatively small share of SKUs — often around 20% — accounts for roughly 70–80% of sales or profit. The availability of these goods should be tightly controlled, and some stores intentionally hold excess stock for this category to avoid stockouts.
• Category B — ordinary goods, which typically account for a mid-sized share of the assortment and a smaller, but still meaningful, share of sales. These goods are also essential, but their availability is less critical than in group A.
• Category C — the least important goods, contributing a small share of profit relative to how much shelf space and inventory investment they consume. These items may be in low demand or unprofitable, and are the first place to look for cuts.

Benefits of ABC analysis:

• Identification of products that generate more profit.
• Assortment optimization.
• Identification of goods that sell well or poorly.
• Rational management of pricing.

2. XYZ analysis is a method of categorizing goods and resources according to demand stability, rather than profitability.

• Category X — goods with stable and predictable sales (everyday goods: milk, eggs, bread).
• Category Y — goods with slight fluctuations in sales, often tied to identifiable trends or seasons (olive oil, chocolate, seafood).
• Category Z — goods with the greatest fluctuations in sales and chaotic, irregular demand (holiday goods, exotic fruits).

Advantages of XYZ analysis:

• Demand forecasting and purchasing/production planning.
• Identification of category Z goods, which carry the highest forecasting risk.
• Optimization of marketing campaigns (additional promotions and discounts).
• Improving the efficiency of inventory management.

3. "Marker Comparison" report (a report available in Datawiz). You can analyze the sales dynamics of products united by specific characteristics (lactose-free products, products for children). As a result, it is easy to evaluate the effectiveness of particular categories, optimize the assortment for each store, and make informed decisions for network development. This report allows you to:

• Control sales dynamics: compare the dynamics between two periods and trace the dynamics in advance.
• Analyze in detail at each level, from general categories to SKUs (specific products).
• Improve assortment management: personalize the assortment for different locations.
• Visually track the dynamics of specific indicators over a certain period.

A related technique worth combining with the above is market basket analysis — looking at which products are frequently bought together. It doesn't classify products by profitability or demand stability the way ABC/XYZ do; instead, it helps you spot cross-selling opportunities and avoid cutting a low-margin product that's actually driving purchases of a high-margin one alongside it.

Assortment KPIs and Formulas

ABC and XYZ analysis tell you which products to focus on; the formulas below quantify exactly how well a product, category, or the whole store is performing so you can act on that focus with numbers instead of intuition.

• Sell-through rate = (Units Sold ÷ Units Received) × 100%. Measures how much of the inventory received in a period has actually sold. Low sell-through on a product with high margin is a signal to promote it, not cut it; low sell-through on a low-margin product is a signal to cut it.
• GMROI (Gross Margin Return on Inventory Investment) = Gross Margin ($) ÷ Average Inventory Cost ($). Shows how much gross profit a product or category generates for every dollar tied up in inventory. A GMROI below 1.0 means the inventory is costing more to hold than it returns in margin — a strong candidate for reassessment regardless of what ABC/XYZ alone would suggest.
• Inventory turnover = Cost of Goods Sold ÷ Average Inventory (at cost). Shows how many times inventory is sold and replaced over a period. Low turnover paired with Category C or Category Z classification is a strong signal the product is dead weight.
• Weeks of Supply (WOS) = On-Hand Units ÷ Average Weekly Sales. Tells you how long current stock will last at the current sales pace — useful for spotting both overstock (WOS too high) and stockout risk (WOS too low), especially for Category A items where availability matters most.
• Stockout rate = Out-of-Stock Hours ÷ Total Available Hours. High stockout rates on Category A/X products (high profit, stable demand) point to a replenishment problem, not an assortment problem — the product itself is fine, the stock discipline isn't.
• Deadstock % = Units With Zero Sales Over X Days ÷ Total Units. The most direct signal of assortment bloat: products sitting with genuinely no movement, independent of margin or classification.

Used together with ABC/XYZ, these formulas turn a classification ("this is a Category C item") into a decision ("this Category C item also has a GMROI of 0.6 and 45 days of zero sales — cut it now, don't wait for the quarterly review").

How to Identify Unprofitable Products

A category manager should easily find and remove ineffective goods from the assortment. The main signs of unprofitable goods are:

• Low turnover rate.
• Low margins (or GMROI below 1.0).
• High storage costs.
• High level of returns.
• Seasonality that isn't being actively managed.
• Irrelevance to current customer demand.
• Cannibalization — when a product doesn't actually add incremental sales, but simply pulls sales away from a near-identical item already in the assortment. This is easy to miss with ABC/XYZ alone, since a cannibalizing product can still look profitable in isolation; it only shows up when you compare sales trends of similar SKUs (a "product family") against each other rather than reviewing each one independently.

An integrated combination of assortment evaluation methods makes it possible to optimize the assortment and increase the income of the store chain. This allows you to find products that are taking up shelf space but are not profitable or are selling erratically.

Step 1 — ABC analysis. Category C items generate the least profit relative to the shelf space and inventory investment they consume. Therefore, it is worth reconsidering the relevance of a product featured in the store but not very popular.

Tip: if the products have high margins but don't sell well, it is worth applying promotions and additional demand stimulation before cutting them.

Step 2 — XYZ analysis. The main focus should be on category Z products. They have chaotic and erratic demand that is difficult to predict.

The two analysis methods should be combined to select goods for removal more accurately:

• Goods of group CZ (unprofitable + irregular) should be excluded from the assortment.
• Goods of group BZ (average profitability + irregular) — adjust your marketing strategy and add promotions or discounts before deciding to cut.

Getting rid of unprofitable goods should be done in stages to reduce losses. The ideal scenario is to apply discounts and unique placement in the store for a quick sale.

How to Prevent New Unprofitable SKUs

• Optimize purchases. Reduce the purchase of products with questionable demand and consider seasonality and demand for products in different locations.
• Use ABC/XYZ analysis regularly. Performing the analysis once a quarter will allow you to see sales dynamics and prevent significant losses — though fast-moving categories or highly competitive ecommerce assortments often warrant a monthly or continuous review instead.
• Test new products before significant purchases. A strategy of test sales in several stores will allow you to understand if there is demand.
• Analyze trends and seasonality. Irrelevant products often become unprofitable.
• Edit marketing strategy. Additionally, it stimulates demand for goods with low turnover.
• Group products into families before adding new SKUs. If a new item shares most of its attributes with something already on the shelf, check whether it will genuinely expand the assortment or just cannibalize an existing product.

Competitive Assortment Analysis: Comparing Your Range to the Market

Everything above looks inward — at your own sales and inventory data. But assortment analysis also has an external, competitive dimension: comparing your product range to what competitors carry, to spot gaps, overlaps, and opportunities.

This typically involves:

• Gap analysis — identifying high-demand products that competitors sell but you don't.
• Overlap and exclusivity mapping — seeing where your range duplicates competitors' versus where you carry something they don't.
• Brand-share analysis — understanding which suppliers or brands dominate a category across the market, not just in your own stores.

This kind of analysis is typically built on catalog data collected from competitor websites, marketplaces, and distributor listings, and it answers a different question than internal ABC/XYZ analysis does: not "is this product performing for us," but "are we even offering the right products in the first place." Retail buyers use it during range reviews and supplier negotiations; brands use it to check how widely and prominently their products are actually being carried.

FAQ

What's the difference between assortment analysis, assortment planning, and assortment optimization?

Assortment analysis is the diagnostic step — evaluating what's currently in the assortment and how it's performing. Assortment planning happens earlier, before the buying season, when you decide what to stock, in what depth, and where. Assortment optimization is the ongoing action taken based on what analysis reveals — adding, cutting, or repositioning products. In practice the three feed into each other in a loop rather than happening once.

What's the difference between assortment width and assortment depth?

Width (or breadth) is how many different categories or product lines you carry. Depth is how many variants — sizes, colors, configurations — you carry within a single line. A store can be wide and shallow (many categories, few options each), narrow and deep (few categories, many options each), or anywhere in between; there's no universally "correct" balance, only the one that fits your customer base and space.

How often should assortment analysis be performed?

A quarterly cadence is a reasonable baseline for most brick-and-mortar retail. Categories with fast-changing demand, or ecommerce assortments competing in crowded marketplaces, generally benefit from monthly or even continuous monitoring instead — waiting a full quarter can mean carrying a dead SKU for months before catching it.

Can assortment analysis reduce excess inventory?

Yes — that's typically its most direct financial payoff. By combining ABC/XYZ classification with KPIs like GMROI, deadstock %, and weeks of supply, category managers can identify and remove products that tie up capital without generating meaningful returns, before they turn into markdowns or write-offs.

Why does competitor data matter for assortment analysis?

Internal analysis (ABC/XYZ, GMROI, sell-through) tells you how your current products are performing, but it can't tell you what you're missing entirely. Competitive assortment analysis fills that gap — surfacing products or categories that are in demand and already being sold by competitors, but absent from your own range.

Is a low-selling product always a candidate for removal?

Not automatically. Check GMROI and cannibalization first: a low-turnover product with strong margin (high GMROI) may be worth keeping and promoting rather than cutting, and a product that looks weak on its own might actually be supporting sales of a higher-margin item through market-basket effects. ABC/XYZ tells you where to look; the formulas and cross-checks above tell you whether to actually act.