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Case study · Market and competitive research

The research that reversed our own recommendation

A client with a very large catalog wanted to know whether to cut it. Everyone assumed the answer was yes. Ten years of their own order data, which nobody had opened, said the opposite — and the competitor analysis explained why.

1. The question was the wrong one

The brief was to work out why a very large product catalog was not converting on the web, and whether it should be cut back. Everyone involved assumed the answer was yes — that a catalog of three hundred thousand items was unmanageable and the sensible move was to prune it to a few thousand of the best.

Before recommending that, we went and looked at what had actually sold.

299,922products in the catalog
26browsable categories
~360categories the competitor ran
12,000products behind them

2. Read the competitor properly, not just their homepage

The obvious comparison was a direct competitor selling similar material at a similar price. Rather than glance at their site, we mapped it — every collection page, the three axes they organize on, the anatomy of a category page, their filter structure, their price bands, their channels, and the fact that they were mid-migration on product titles with two formats live at once.

Figure 1

The finding that reframed the whole engagement

Browsable categories per 1,000 products The competitor 30 categories The client 0.09 categories The competitor ran about 360 category pages against roughly 12,000 products. The client had 26 against 299,922 — a catalog 25 times larger behind a thirtieth of the doors.

Source: full crawl and enumeration of both catalogs, July 2026. The competitor organizes on format, geography and theme, with a written introduction on every collection page that doubles as its meta description.

Why this changed the brief

The competitor did not have a better catalog. They had roughly a twenty-fifth of it. What they had was doors — hundreds of browsable, indexable, written category pages that gave search engines and customers a way in. The client had the inventory and no way to reach it.

3. Ten years of order history, read as research

The client had a decade of marketplace order data sitting in spreadsheets nobody had analyzed. It answered questions the website analytics could not.

Figure 2

What people actually bought

Orders by theme, ten years of marketplace history City and place panoramas 1,063 Named-person portraits 746 Propaganda and recruiting posters 616 War and military 335 Sports 165 The best-selling theme in the company’s history had no category page on the website at all.

Source: analysis of 6,900 marketplace orders across a ten-year window, reconciled against a complete profit-and-loss log.

The gap this exposed

The best-selling theme in the company’s entire history — city and place panoramas, over a thousand orders — had no category page on the website. The categories had been built at some point, switched off, and left empty. Nobody had noticed because nobody had put the sales history next to the site structure.

4. The finding that reversed our own recommendation

We had been ready to recommend cutting the catalog. Then we looked at the distribution.

Figure 3

The long tail was the business

Where the revenue actually came from, 6,900 orders across 5,830 distinct images Top 500 Everything else 20.1% of orders 79.9% of orders 5,149 images — 88.3% of everything that ever sold — sold exactly once. Those single sales were 74.6% of all orders and 75.8% of all revenue. Which reversed the recommendation we had been about to make.

Source: order-level analysis of ten years of marketplace transactions, deduplicated by product.

Nearly nine in ten products that ever sold, sold exactly once. Those one-time sellers accounted for three quarters of all orders and three quarters of all revenue. Cutting the tail would have cut the business.

What we recommended instead

Keep the whole catalog on the marketplaces, where search retrieves the tail. On the website, do not cut the catalog — cut the index, and build the doors. Roughly 286 customer-facing categories in the language a customer would actually type, rather than the archival collection names the catalog had inherited.

5. What this case is meant to show

The usual approachWhat was done here
Look at the competitor’s homepageEnumerate their entire structure and count it
Trust the briefTest the brief’s assumption before acting on it
Use website analyticsUse ten years of order data the client already owned
Deliver the expected answerReverse our own recommendation when the data said so
The part worth stealing

The most valuable data in this engagement was already inside the company, in spreadsheets nobody had opened for years. That is usually true. Before buying a research subscription, it is worth finding out what the client already has and has never looked at.

Marketing Analytics Consultants

Want to know what your competitor is actually doing?

We map it properly — structure, categories, pricing, channels and change history — and set it against what your own sales data already says. Then we tell you what it means, including when it contradicts what you hoped.

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