What does the rest of your catalog actually do? A Pareto analysis in e-commerce rarely turns out the way you think. And once you know – it’s hard to look away from the tail.
What product_pareto measures
A classic rule, rarely a classic result
The Pareto rule says: 20% of products generate 80% of revenue. In e-commerce practice that’s only a starting point – the actual distribution depends on the category, the breadth of the catalog and the assortment strategy. The get_product_pareto tool in DataOrganizer not only shows this distribution but also splits the catalog into measurable segments: how many SKUs actually work, how many sit in the tail, and how many – though technically generating sales – consume more resources than they bring in.
I examined a store selling garden tools and accessories. 2,693 active SKUs, 90 days, EUR 2.32M in revenue. Before I get to the numbers – the classic 80/20 didn’t occur. 80/30 did. And that’s not an error.
For the period February 24 – May 24, 2026, all channels, currency EUR:
Total: 2,693 SKUs with sales · 2,323,803 EUR in revenue
The 80% point: reached by 798 products – that’s 29.6% of the catalog. The classic 80/20 didn’t occur – you have a long tail, an evenly distributed tail.
Top 20 products (TOP 1% of the catalog):
| # | Product | Revenue | Share | Cum. |
|---|---|---|---|---|
| 1 | Peat substrate [Pro, 12-pack] | 34,195 EUR | 1.47% | 1.47% |
| 2 | Granular fertilizer [Universal, 3 kg] | 22,155 EUR | 0.95% | 2.42% |
| 3 | Premium flower substrate [12 L, 12-pack] | 19,655 EUR | 0.85% | 3.27% |
| 4 | Multi-component fertilizer [Medium, 4 kg] | 17,131 EUR | 0.74% | 4.01% |
| 5 | Peat substrate [Senior, 12-pack] | 16,517 EUR | 0.71% | 4.72% |
| 6 | Granular fertilizer [Twin-pack 2×3 kg] | 15,525 EUR | 0.67% | 5.39% |
| 7 | Automatic irrigation system Gardena [Professional, 5 m] hidden gem | 15,081 EUR | 0.65% | 6.04% |
| 8 | Universal substrate [Pro Senior, 12-pack] | 14,800 EUR | 0.64% | 6.67% |
| 9 | Specialist fertilizer [4 kg] | 14,453 EUR | 0.62% | 7.29% |
| 10 | Vegetable seed set [4 varieties, multi-pack] | 14,007 EUR | 0.60% | 7.90% |
| → Top 20 total | 303,438 EUR | 13.06% | 13.06% | |
Note position #7 – the irrigation system: only 13 units, but 15,081 EUR (≈ 1,160 EUR / order). Sorting by quantity, it would be invisible.
Key result
An 80/30 rule, not 80/20. In this store 798 products (29.6% of the catalog) generate 80% of revenue. This is a “long tail” – the tail is long, but not exceptionally deep. The key question is: what does the rest do, those 1,895 products below the 80% threshold?
Four catalog segments
Stars, Working catalog, Long tail – and where the problems begin
Instead of a single top-N list, it’s worth splitting the catalog into four segments. Each has a different role in the store and different operational requirements. The data from get_product_pareto lets you do this precisely.
At first glance the Working catalog looks like the engine: 400 products, 35% of revenue, 815k EUR. This is the segment most often underrated – it’s not as flashy as Stars, doesn’t raise concern like Long tail, yet generates more than both combined.
But the number that should stop you is the one on the left of the bottom bar: 2,193 SKUs. That’s 81.4% of the active catalog, sitting in the tail below position 500. Together they generate 722k EUR – the same as the Working catalog, only with 5× more products.
A hidden gem in the tail
A diamond you don’t see when sorting by quantity
Let’s go back to position #7 from the mockup: the automatic Gardena Professional irrigation system. Over 90 days it sold 13 units, but generated 15,081 EUR – an average of 1,160 EUR per order.
I’m comparing the average order value (AOV) for selected products from the top 20:
| Product | Revenue | Units | AOV |
|---|---|---|---|
| Peat substrate [12-pack] | 34,195 EUR | 439 | 78 EUR |
| Granular fertilizer [3 kg] | 22,155 EUR | 226 | 98 EUR |
| Vegetable seed set [4 var.] | 14,007 EUR | 22 | 637 EUR |
| Gardena Professional irrigation system gem | 15,081 EUR | 13 | 1,160 EUR |
Observation: the irrigation system has an AOV 15× higher than peat substrate in a 12-pack. It’s a product of a completely different price category – bought once by gardeners for the season or on a specialist’s recommendation.
Risk: sorting by order quantity, this product drops below position 200. It’s easy to miss in regular reporting. It’s worth tracking it as a separate line in margin analysis.
get_product_pareto doesn’t measure that directly – but I can estimate the cost logic:
722,369 EUR in revenue from 2,193 SKUs over 90 days is on average 329 EUR / SKU = ~110 EUR / SKU / month.
Meanwhile, every active SKU generates indirect costs:
- GMC feed – every product with a low CTR lowers the Quality Score of the whole feed
- PMAX – the campaign can allocate budget to the low-converting tail instead of the Stars
- Store search – the long tail “dilutes” results for popular queries
- Inventory management – 2,193 lines to handle in the system
Key question: for how many of these 2,193 SKUs is gross margin > the sum of indirect costs? That requires combining with cost data from get_margin_segments.
An important nuance
The Long tail isn’t bad by definition. 722k EUR from 2,193 SKUs is real revenue – the question is whether, after indirect costs (feed, PMAX, assortment management), the balance is positive for each product individually. get_product_pareto identifies candidates for an audit. The decision requires margin data.
When to raise the alarm
Four signals that should trigger action
A Pareto analysis isn’t a ranking – it’s a map of tensions. There are places where the result is good, and places worth pausing at. Below are four signals worth reacting to.
How often to check
product_pareto isn’t a monthly report
Revenue concentration changes slowly – seasonality, new products, changes in advertising. A good practice is to check Pareto every quarter, with one exception: if you make big changes to the catalog (new categories, big promotions, changes in the GMC feed), take a snapshot before and after. The difference in segments will tell you more than any campaign metric.
It’s also worth watching segment movement between quarters – a product that moved from position 450 to 80 is a signal worth attention (it’s growing). A product that dropped from Stars to Working catalog in one quarter – needs an explanation.
Good practice
The combination: product_pareto + get_margin_segments + get_trending_products. Pareto shows where the revenue is. Margins show where the profit is. Trends show what’s changing place. Three tools, one full catalog map.
The main takeaway
80% of revenue from 30% of SKUs – and 2,193 products with an unanswered question
The 80/20 rule didn’t occur – 80/30 did. That’s not a problem, it’s the characteristic of a store with a broad, dispersed assortment. The engine is where you don’t expect it: the Working catalog (pos. 101–500) generates 35% of revenue from 400 products and rarely gets as much attention as the top bestsellers.
The real challenge is the Long tail: 2,193 SKUs, 81% of the catalog, 722k EUR in revenue. Each of these products lives in the GMC feed, can pull budget in PMAX and takes up space in the store search. For most, the profitability question stays open – until you combine Pareto with margins.
And the irrigation system at position #7? 13 units, 15,081 EUR, invisible in standard volume-based reports. That’s exactly what get_product_pareto is for.
DataOrganizer · MCP
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