If key specs live only in paragraphs, customers can’t find them – and neither can search, filters, feeds, or AI shopping tools. This article shows how to move facts into structured attributes, use PIM to govern them, and keep copy for persuasion. Expect better discovery, stronger SEO, fewer returns, and easier syndication
A PIM project fails or succeeds on people, not software. Learn the five core roles you need on your PIM implementation team, what each one actually does, and how they work together to deliver cleaner data, smoother integrations and real business value
If you mix up product attributes and categories, your navigation breaks and filters return “0 results”. This article shows how to design a clean taxonomy in PIM, avoid common modelling traps, and make it easier for customers to find what they want across all channels.
Supplier data onboarding is often the slowest step in getting products live. AI changes that. This article explains how modern PIM features and Start with Data’s SKU Launch reduce manual mapping, standardise messy inputs, flag errors early, and speed up approvals. Expect quicker launches, better consistency, and fewer late-night spreadsheet battles.
Complex products quickly overwhelm spreadsheets. Learn how PIM data models, inheritance and rules-based configuration tame variants, cut manual work and give customers clearer choices across every channel.
Moving product data from spreadsheets, ERP and homemade tools into a new PIM can feel like open-heart surgery. This article sets out clear, non-technical steps to audit, cleanse and migrate your product information so your PIM goes live clean, trusted, and ready for growth
A PIM implementation is not a switch you flip. Discover typical timelines, the phases you will go through, and the factors that speed things up – or slow them down – so you can set realistic expectations and still get to value quickly.
Data pools standardise supplier product data; PIM enriches and syndicates it. Together, they form the future of B2B data exchange. Discover how GS1/GDSN data pools, real-time APIs, and a modern PIM turn messy spreadsheets into a governed, automated network your trading partners can trust.
Choosing between custom and out-of-the-box PIM integrations is a strategic call, not just a technical one. This article explains how to weigh cost, speed, risk and complexity so your product information management investment actually pays off across ERP, ecommerce and channels
PIM holds your rich product content. ERP holds your stock, prices, and suppliers. If they are not connected, you pay for it in errors, rework and missed sales. Learn how to design a clean product data flow between PIM and ERP that actually matches how you trade
Manual product classification breaks at scale. This guide explains how AI-assisted classification works before data hits PIM, using rules, signals, and human oversight to keep taxonomy consistent, improve discoverability, and avoid spreadsheet chaos across every channel
Your catalogue does the selling. This guide shows how better product data structure and enrichment improves search visibility, reduces friction, and helps every channel perform better.
AI shopping tools don’t “browse” your site, they dissect it. Learn how AI actually reads your product pages, which signals it trusts, and how product information management (PIM) and high-quality product data help your catalogue stay visible in an AI-first search world
Are your category filters returning “0 results” and confusing shoppers? The problem isn’t your front-end; it’s your product data, taxonomy and PIM. Learn why filters fail, how poor attributes kill search and discovery, and what a modern PIM and better data governance can do to turn it around.
Stop spot-checking and start systemising. This guide shows how to audit your product catalogue like an AI agent, with clear goals, automated checks, human-in-the-loop, and continuous learning. That way, your PIM, SEO, and digital shelf performance all move in the right direction.
AI doesn’t need more product data. It needs the right layers of data. This guide reframes Kotler’s model into five practical data layers and shows how modern PIM, governance and onboarding make each one production-ready across the digital shelf.
AI is only as good as the product data behind it. This guide explains how to prepare product data for AI by cleaning, structuring, enriching and governing it before it reaches your PIM or eCommerce platform.
The digital shelf is where products compete online. In 2026, success means more than presence; it means optimised, enriched, and AI-powered content delivered consistently across channels. This guide explains what the digital shelf is, why it matters, and how to master it with PIM, onboarding automation, and AI content generation
PIM integration is no longer just about connecting systems — it’s about creating a seamless product data ecosystem. In 2026, that means AI-powered supplier onboarding, automated content generation, and flexible, API-driven architectures. This guide covers benefits, pitfalls, and success stories to help your business transform product data into a competitive advantage.
Product taxonomy is the backbone of eCommerce. In 2026, it powers site navigation, SEO visibility, and product data management. This guide explains what taxonomy is, shows real-world examples, explores common pitfalls, and shares best practices for creating scalable taxonomies that boost CX, conversions, and growth.