Episode 6: Why Enriching Your Top Sellers First Is the Wrong Move

‍

If you've ever kicked off a product data enrichment project, chances are you started with your bestsellers. It makes sense on paper. Go where the commercial value is. Prioritise the products that drive the most revenue. Get the best possible content on the pages that matter most.

It's a logical approach. It also doesn't work.

The bestseller trap

When you enrich a list of products selected on commercial value, you're looking at your catalog through a business lens. The problem is your customers aren't using that lens. They're browsing by category.

They land on your site, navigate to a section, and start filtering. By brand. By size. By specification. By price. The entire discovery experience depends on consistent, complete data across everything in that category, not just the six products that happen to be your highest sellers.

So if you've enriched those six and left the other 34 in the same state they were in before, here's what actually happens. Your filters break. Your facets are incomplete. Your navigation produces results that feel random and thin. Customers assume something is wrong with the site, or that you don't carry enough range, and they leave.

You've done the work. The needle hasn't moved.

Patchy data is worse than limited data

This is the counterintuitive part. You might assume that enriching some products is always better than enriching none. But patchy data across a category actively damages the experience.

A customer browsing power tools who can filter by voltage, torque, and chuck size on six products but not the other thirty is going to notice that something feels off. The results look incomplete. The filters don't surface what they're looking for. They don't know why, but the experience feels broken.

That's a worse outcome than a category where nothing has been enriched yet, because at least then the experience is consistent.

The same logic applies to content tier strategies. Gold, silver, bronze sounds rigorous and commercially sensible. But six products at gold standard with the rest at nothing is far less useful than every product in the category hitting a solid bronze. Bronze with complete filter attributes beats gold with gaps, because bronze still lets customers actually navigate.

What works: enriching by complete category

The alternative is to pick a category and finish it before moving to the next one.

When every product in a category has its attributes filled out to the same standard, everything starts working properly. Filters return accurate results. Facets reflect the full range. Comparison tools function as they should, which matters a lot for technical products where buyers need to evaluate specifications side by side before committing.

You also start surfacing products that have never performed because they've never been discoverable. The long tail of a catalog often looks like it doesn't perform simply because it's never had the data it needs to show up in the right searches and filters. Category enrichment fixes that across the board, not just for the products you already know about.

And when you go back to your leadership team, the story you can tell is concrete. Here is a category before enrichment. Here is the same category after. Filter usage, conversion rate, search performance, average order value. That's a business case. A list of enriched bestsellers scattered across the catalog is much harder to tie to outcomes.

A real example

One customer came to us with over 200,000 product codes and very little data. They'd just come through a major ecommerce re-platform and realised on the other side that the data hadn't come with them. The instinct was to start with the top 500 products by sales rank and work through the list commercially.

We followed that strategy with them. Four months in, with several thousand SKUs enriched, the results just weren't there. The reason was clear when we looked at it: the enriched products were scattered across building supplies, plumbing, tools, and timber. No single category had been finished. Filters across the site were still broken. Navigation was still patchy. Nothing had actually improved for a customer trying to shop.

When we switched to a category-by-category approach, the results followed. The categories that had been fully enriched were seeing around 85% conversion improvement. The work was the same. The sequencing was different.

How to choose your first category

You don't have to start with your biggest category or your most problematic one. There are a few ways in to pick something that builds momentum quickly.

Where the data gap is costing you sales. If you know a category is underperforming and you suspect data quality is a factor, that's a strong place to start. You'll see the uplift clearly.

A strategically important category. A new season range, your highest-margin products, a category you're trying to grow. Full enrichment here signals intent and has commercial backing.

An easy win. Sometimes the data already exists but it's buried in long-form descriptions or supplier documents rather than structured attributes. One customer extracted data from their existing descriptions and went from near zero to 90% attribute completeness without sourcing anything new. Starting somewhere like this gets the category approach established and gives you a proof point quickly.

A category where your competitors are behind. If you can get ahead of the market in a specific category, the traffic and conversion benefits compound. It's one of the cleaner competitive advantages available in ecommerce.

The takeaway

Stop thinking about product data enrichment at the product level. Start thinking about it at the category level.

A fully enriched category is worth more than a thousand perfectly enriched products scattered across your catalog. Google might appreciate the individual product pages. Your customers cannot filter, compare, or navigate by them.

If you've already started an enrichment project and the results aren't showing up, it's worth stepping back and looking at how the work has been sequenced. Picking a single category and seeing it through to completion is almost always the thing that makes the difference.

‍