Jan/San & Packaging has a product-data problem — and 2026 is when it starts costing deals

Jan/San and packaging distributors have run on the same product-data habits for two decades: a rep who knows the dilution ratio by memory, a spec sheet that lives in someone's inbox, an ERP field that says "case of 4" with no unit of measure attached. That worked when the buyer called the rep. It stops working when the buyer is a facilities manager typing a question into an AI assistant, or a national account comparing five distributors' websites before anyone picks up a phone. Here's what's actually broken in Jan/San and packaging product data, what it's already costing, and why 2026 is the year the gap turns into lost revenue instead of just an internal headache.

What's broken: catalogs built for phone orders, not readers

Most Jan/San and packaging catalogs were structured to move a SKU through an ERP, not to answer a buyer's question. A concentrate cleaner might have a name, a case pack, and a price, but no dilution ratio, no EPA registration number, no Safety Data Sheet link, no sustainability certification (Green Seal, EcoLogo, UL) surfaced as a searchable attribute. A packaging SKU might list "corrugated box" with no burst strength, no flute type, no recycled-content percentage. The underlying values usually exist somewhere, in a supplier spec PDF, a paper catalog scan, or a rep's head, but they never make it into a structured, comparable field.

This isn't a new complaint; it's the same channel-pressure story the industry has been telling itself for years. ISSA has flagged that "the traditional business model jansan distributors have followed... is coming to an end," with consolidation and e-commerce pressure forcing distributors to compete on service and expertise rather than product availability alone (ISSA). What's changed is the mechanism of competition: expertise now has to live in the catalog itself, because the buyer is evaluating it before a rep ever gets a call. Independent distributors describe the same pressure point from the other side, noting that national players are "investing heavily in AI and eCommerce" and that the equalizer for smaller distributors is a searchable, technology-enabled catalog rather than a bigger warehouse (Pepper).

What it costs: thin PDPs, wrong-SKU returns, invisible products

Incomplete Jan/San data doesn't fail with a bang. It fails as a series of small, compounding leaks:

A raw feed for a floor-care concentrate typically reads something like: "All-Purpose Cleaner Concentrate, 1 gal, case of 4." An enriched version looks like this:

The first version is a SKU. The second is an answer. That distinction is the whole game now, because the buyer asking the question has changed and so has where they ask it.

Why 2026 is when this starts costing deals

Three things are converging on the Jan/San and packaging channel at once.

First, the buyer generation has turned over. B2B purchasing is now dominated by buyers who default to self-serve digital research; Gartner's most recent sales survey found 67% of B2B buyers prefer a rep-free purchasing experience, and that AI tools are now a regular part of how buyers research and shortlist vendors before a seller is ever looped in (Gartner). A buyer who can't find dilution ratios, certifications, or spec data on your site doesn't call you to ask, they move to the next tab.

Second, AI answer engines have become a real discovery channel, and they're unforgiving of thin data. Analysis of B2B catalog behavior notes that distributors managing diverse supplier networks are chronically stuck with "inconsistent product data" and "incomplete specifications," and that the advantage now goes to catalogs that are structured enough for AI agents to parse and cite accurately (Lucidworks). Try it yourself: ask an answer engine "which floor cleaner concentrate is Green Seal certified with a 1:64 dilution ratio" and watch which distributors and brands surface. It's the ones with the attribute actually published, not the ones with the best chemistry.

Third, consolidation raises the stakes for distributors without the biggest e-commerce budget. As national players roll up independents and pour money into digital storefronts, a mid-size distributor competes by having the most complete, trustworthy catalog in a category, not by matching ad spend. Product data completeness has quietly become a competitive moat.

The mechanism, not the magic

None of this requires ripping out an ERP or a distribution management system, and it doesn't require a CRM overhaul either. It requires treating product data as a maintained asset: extracted from real supplier and SDS documents, quality-scored against what a compliance-minded or sustainability-minded buyer actually searches for, and kept current as formulations, packaging, and certifications change. That's a fundamentally different job than the one most Jan/San catalogs were built to do, and it's a job that's now visible every time a buyer, human or AI, goes looking for an answer instead of a SKU number.

This is the gap Anglera is built to close. Your PIM, ERP, or flat file stores the data; Anglera continuously scores, gap-fills, and enriches it, pulled from real supplier and spec documents rather than guessed, so a Jan/San or packaging catalog reads like an answer instead of a placeholder. It plugs into whatever a distributor or manufacturer already runs, reaches a usable state in weeks rather than a multi-year system overhaul, and can start from nothing more than a flat file. It's additive by design, and in a channel where the winning distributor is the one whose data a buyer, or an AI assistant, actually trusts, that's the part of the business worth fixing first.