Catalog management is broken. Here’s how AI is fixing it for agentic commerce.
Catalog management is broken.
Online businesses today manage product catalogs at unprecedented scale — from tens of thousands to hundreds of thousands of SKUs across their owned assortment and supplier networks.
And while catalogs grow in scale and complexity, many are trapped in old, manual processes that slow growth. As teams race to get new products live and update existing offers, they’re stuck in a game of back and forth.
For every product that requires a review, the typical team faces 10-15 correction cycles, as suppliers wait for feedback and products that should go live in days, are held up for months.
Add to that the urgency of the moment: Large Language Model (LLM) platforms that cannibalize site traffic and refuse to recommend businesses with poor product data.
As catalog management hits a crisis point, modern solutions provide a way forward that not only breaks down bottlenecks, but puts retailers and B2B businesses in position to win in the age of agentic commerce.
The cost of broken catalog management processes
Legacy validation simply cannot scale.
According to an internal analysis of Mirakl Catalog Platform users, retailers today are managing catalogs with hundreds of thousands of products that can balloon into the millions when third-party suppliers are added.
On the other hand, suppliers themselves manage up to 650,000 SKUs.
This mismatch creates a cascade of hidden costs:
Missed revenue: Delayed launches keep products offline during peak demand.
Low conversion: Inaccurate listings erode buyer trust.
Churn and friction: Operator burnout and strained supplier relationships stall long-term growth.
The breakdown in manual catalog management
Manual processes have reached a breaking point. Our recent global merchant survey confirms that this operational collapse manifests in three acute pain points that drain time, revenue, and competitive standing:
Technical integration nightmares: Integration hurdles topped the list of challenges. Connecting legacy in-house systems with diverse partner platforms creates data silos that stall time-to-market and bake errors into every handoff.
Communication friction: As the second most-cited frustration, teams are trapped in an "endless back-and-forth" across emails and spreadsheets. While operators play intermediary, products sit in digital limbo instead of on the virtual shelf.
Data inconsistencies: Rounding out the top three, varying channel requirements force constant rework. When every platform demands different units, taxonomies, and image counts, teams waste hours reformatting data instead of driving strategic growth.
What modern catalog management actually delivers
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The above chart shows efficiency gains by leveraging industry-leading technology to bolster catalog management. By industry, it shows the percentage of products Mirakl catalog management capabilities are able to validate on first pass, what percentage can then be self corrected by suppliers, and, finally, the remaining percentage that requires further review.
The shift from legacy manual review to modern catalog platforms isn't just an incremental improvement — it’s a transformation of the unit economics of eCommerce. Our analysis of real-world implementations reveals three primary drivers of efficiency:
Superior first-pass validation rates: Efficiency begins at the point of entry. While manual systems struggle to clear products on the first try, modern platforms achieve 60% to 75% first-pass validation rates. By ensuring products meet requirements on initial import, retailers can shift their focus from routine firefighting to strategic assortment growth.
Radical reduction in operator burden: Automation enables self-correction. By providing suppliers with actionable, real-time feedback, 20% to 34% of data issues are resolved by the suppliers themselves without human intervention. Combined with high first-pass validation, this can reduce manual operator review to as low as 2% of the total catalog.
Accelerated correction cycles: Legacy processes involve 10-15 correction cycles. Modern platforms leverage guided workflows to slash this to just 1-6 cycles — a 50% to 90% reduction in time spent validating. The result is a measurable improvement of 15% to 60%+ across time savings and error reduction, with over 30% of users reporting the experience is "significantly better" than marketplace alternatives.
Building the foundation for Agentic Commerce
Modern catalog management does more than solve operational pain. It also builds the infrastructure for an "agentic" future.
That’s because AI shopping agents rely on structured, complete and accurate data to recommend products. Without it, your items become invisible to the LLMs currently cannibalizing site traffic.
What AI needs from your catalog:
Standardized taxonomy: Machines must understand product relationships instantly.
Complete attributes: Every specification must be filled to power AI-driven comparisons.
Rich context: Descriptions must move beyond keywords to help AI understand use cases.
Two sides of the same coin
The systems driving high validation rates are the same ones that make your business "AI-ready."
By automating validation and enrichment, modern platforms ensure every product meets the high-quality threshold required for AI discovery.
Whether managing first-party or third-party assortments, you are transforming raw data into a competitive asset for the age of agentic commerce.
Modern catalog management in action: Decathlon's AI-first strategy
Decathlon, a global leader in sporting goods retail, demonstrates how modern catalog management builds the foundation for AI-powered commerce.
Thibaut Peeters, Global Lead Marketplace at Decathlon, says the company leverages AI for catalog curation to ensure product listings meet both internal guidelines and maintain a consistent global customer experience on their website.
And they’ve moved quickly to adopt these AI-powered enrichment tools.
"We made a beta test with Mirakl's Catalog Transformer, and we are now live,” Peeters said, “so some sellers start to use that to enrich their product data, their product descriptions and everything that will be useful to be seen online, to be searched online or to be chosen online."
A major focus for Decathlon in recent years has been on taxonomy and product data structure.
Peeters emphasizes that in partnership with Mirakl, they are able to "significantly enrich our first-party product data, especially for the international brands we distribute. This collaboration allows us to enhance our catalog quality and product information, ultimately delivering more value to our customers."
The competitive reality and the path forward
The winners in agentic commerce are being decided now.
As AI agents scan millions of products, high-quality, structured data is the only path to discovery. Poor data makes you invisible, regardless of your price or product quality.
By solving today’s operational bottlenecks — achieving up to 75% first-pass validation and 90% fewer correction cycles — you are simultaneously building the foundation for tomorrow. Whether managing first-party or marketplace assortments, the right platform transforms operational chaos into a competitive advantage.
Transform your catalog operations and build your agentic commerce foundation, by to learn how Mirakl Catalog Platform delivers measurable results from day one.
Source: Aggregated, anonymized analysis of Mirakl Catalog Manager customers and B2C Vendor Experience Survey (Mirakl), conducted in 2025. Data reflects performance across a pool of customers by industry; not all customers will achieve the same results. Percentages represent average or median improvements and may vary by use case, implementation and baseline processes. Survey included 30+ ecommerce merchants globally; not all respondents answered every question. Quotes are verbatim or lightly edited for clarity.
