Who owns the product data | Jay Roxe, CMO, inriver

About this episode

Product data used to be a back-office chore. Now it decides whether an AI recommends you, whether a customer can find a replacement part, and whether you show up in the consideration set at all. Most teams have no real picture of what is happening down in that foundation.ㅤFloyd Blaikie hosts this one solo while Matt Johnson is on vacation, going underneath the question part one left open: is it the platform holding you back, or the data beneath it?ㅤShe's joined by Jay Roxe, who runs marketing at inriver, and Willem Van Dijk, Pivotree's director of data platforms and services. Jay is the guy who thinks about the PIM. Willem is the guy who thinks about everything holding it up.ㅤBoth took the data side. The friction surfaced anyway, over who owns product data (nobody agrees) and how far you can trust AI with it (not far, yet).ㅤ👤 Guest BiosJay Roxe is Chief Marketing Officer at inriver, the PIM software company serving brands, manufacturers, and distributors. He came up through product and marketing leadership at Microsoft, GE, athenahealth, Rapid7, and HYPR. This is his second appearance on the show.ㅤWillem Van Dijk is director of data platforms and services at Pivotree, where he runs data audits, remediations, and MDM and PIM implementations. He spent years at Stibo Systems in roles spanning ANZ managing director and VP of platform strategy for product data syndication.ㅤ📌 What We CoverA disgruntled employee pushing bad content live because nobody controlled who input, reviewed, and approved publicationThe $250 million revenue hole caused by unpublishable replacement parts data, and the gray market that absorbed the demandWhy spare parts break first: fitment information, interchanges, and country of manufacture changing over a part's lifeThe information supply chain, and the layer teams skip, which is control over upstream people rather than technologyOwnership versus stewardship, and why IT and marketing both think product data is theirsTrust signals in a PIM: taxonomy, fill rates, outlier dashboards, and anomaly detection across correlated attributesWhat running on Excel actually looks like from the inside, and the third of manufacturers and distributors keeping more than 85% of publish-ready SKUs availablePIM plus an MCP server: distributors sending agents to shop for content, with no aggregator remapping taxonomies in the middleWhere human in the loop is still non-negotiable, and why launch-day clean is not the same as solid ㅤ🔗 Resources MentionedinriverPivotree, and willem@pivotree.comMicrosoft Excel, and ClippyClaudeMCP servers