Product Data Weekly

Most product pages still treat FAQs as an SEO box-tick. But AI models are answer engines, and FAQs are answers. If yours are missing or vague, the engines go and describe your products from someone else's content. In this episode, we break down how a heatwave, a paddling pool and a filter pump became the perfect example of what happens when compatibility questions go unanswered, why return reasons...

Supplier onboarding should be a solved problem by now. In this episode, Ben breaks down why supplier data arrives unusable no matter how hard you push suppliers or your own team, and why the real problem is the gap between how data is collected and how the business actually needs to use it. Ben also shares the 3 principles that fix it. If supplier onboarding keeps resurfacing as a problem you thou...

This is the first of our Product Data Doctor segment, where we take a real product data problem and break it down. This one's a shoe retailer moving 11,000 products from Magento to Shopify. Most teams start by exporting everything and rebuilding the same structure on the new platform. That's usually the mistake. You just move broken data into a nicer box. Episode Breakdown 00:00 – Introducing Prod...

Akeneo just acquired PricingHub, which got us thinking about why pricing has never lived in a PIM. This episode is about pricing, PIM, and why the two have stayed apart for so long. Episode Breakdown 00:00 – The Akeneo and PricingHub acquisition 03:13 – Reason 1: product data and price run on different clocks 05:41 – Reason 2: price isn't a content problem 07:33 – Reason 3: one product, many price...

Manufacturers and distributors think they're dealing with different product data problems. They're not. It's the same problem, viewed from opposite sides of the fence. In this masterclass episode, we focus on industrial solutions and electronic components, and the product data flow between manufacturers and distributors. We break down why the data nearly always exists but stays buried (in someone'...

You'd assume the biggest retailers have moved past spreadsheets by now. Most haven't, and it's not because they're behind. In this episode, we break down why massive businesses still run their entire product catalogue off one giant spreadsheet Sharon could break on a Tuesday, why spreadsheets survive because they're bad and not despite it, and why a PIM so often just replicates the same mess in an...

Most product data was written for humans. The buyers have changed. The new buyer is an AI agent: ChatGPT, Gemini, Perplexity, Claude. When someone asks for "an IP65-rated, 5–10kW three-phase motor for an outdoor conveyor", the agent matches that against structured data. If your attributes aren't there, you get ignored. In this episode, Ben breaks down the shift from descriptive data, to structured...

Most takes on the Australian e-commerce market assume it's just a smaller, slower version of the UK or US. That's half right, and the other half is where it gets interesting. In this episode, Ben's just back from two weeks in Australia and we unpack what's actually happening on the ground: the marketplace onboarding bottleneck nobody's solving, why the PIM vs DAM debate looks different over there,...

Most teams try to fix their product pages by jumping straight to descriptions or AI search tools. Which feels like progress but is usually why nothing improves. In this episode, Clare walks through the five layers of product data optimisation and why doing them out of order is the reason so many product data projects stall. We cover what each layer does, what breaks when you skip ahead, and where...

In this masterclass episode, Ben and Clare break down five silent leaks costing eCommerce and B2B businesses sales every day through bad product data. Most teams assume fixing product data means a 12-month PIM project signed off by the board, but each of these leaks can be tackled in a week. Drawing from real customer work at Start with Data, Ben and Clare walk through the issues that actually mov...

In this episode, we break down the two big myths about PIMs, where a PIM genuinely is the right call, and what most retailers and distributors actually need instead (or alongside it). If you're 3 PIM demos deep and still can't articulate the value, this will explain why. Episode Breakdown 00:00 – The two big myths about PIMs 03:23 – What a PIM actually does well 05:45 – Why brands and manufacturer...

Clare and Ben discuss the four essential steps teams should take before committing to a PIM implementation or e-commerce re-platform, focusing on product data readiness. They share practical insights on why so many projects run late and over budget, and how proper preparation around product data almost always costs less than fixing problems after go-live.   Keywords: product data, e-commerce, PIM...

Ben and Clare discuss the importance of investing in product data, focusing on five key areas: conversion, organic search visibility, return rates, operational efficiency, and cross-team collaboration. They share practical insights on how to justify data investments and measure their impact to drive growth and efficiency. Keywords: product data, e-commerce, conversion rate, organic search, return...

This episode explores the various methods of sourcing and enriching product data, highlighting their pros, cons, and practical considerations. It provides insights into manual processes, data scraping, data pools, AI-driven solutions, and internal reuse strategies, offering actionable advice for scaling and improving product data sourcing. Key Topics Product data sourcing challenges Manual data en...

Most product data enrichment projects start the same way. Which sounds like the right move but it’s usually why nothing improves. In this episode, we break down why enriching products one-by-one (based on sales) leads to broken filters, patchy categories, and a frustrating customer experience. We also share the approach we see actually working. If your enrichment project isn’t moving the needle, t...

Missing images are one of the most visible data quality problems on any eCommerce site, and one of the least likely to be treated as a data problem.  The result is grey placeholders that quietly kill conversion, suppress marketplace listings, and tell your buyers you don't care enough about the product to show them what it looks like. In this episode, Clare breaks down why this keeps happening and...

Supplier data is one of the biggest operational headaches in distribution, retail, and marketplaces. The data arrives late, incomplete, and in the wrong format. Teams spend weeks transforming it manually. And yet most businesses keep buying portals and templates that don't actually solve anything. In this episode, Clare and Ben get into why the problem keeps getting worse — and lay out the three l...

Generative Engine Optimization is the new SEO. In this practical episode, we share three simple changes that can dramatically improve how AI systems interpret and surface your products: Render core product data in static HTML Implement and validate structured product schema Write question answering content with real context These are small technical adjustments with outsized impact. If AI can’t co...

This episode explores the critical importance of category structure and attribute management in e-commerce. Hosts Clare Adams and Ben Adams discuss how proper product categorisation impacts data quality, customer experience, and operational efficiency, offering practical steps for improvement. Takeaways Category structures impact product data Incremental approach to category structure improvement...

Most product data problems don't show up as data problems — they show up as delayed launches, supplier headaches, and e-commerce teams drowning in fixes. In this first episode, Clare and Ben cut through the noise to ask the five questions that expose where your product data operations are actually breaking down. From manual reformatting at ingestion, to 3,500-entry brand lists nobody can navigate,...