Agentic Commerce: The Catalog & Product Agent
Why your Product Data is the foundation of Agentic Commerce
In the previous article I wrote about agentic commerce – the shift toward a model where software agents increasingly play an active role in product discovery, comparison and purchasing on behalf of customers.
There is one prerequisite that makes or breaks that model, and it is far less discussed than the technology around it: the quality, completeness and structure of your product catalogue.
Agents cannot work with incomplete data. Neither can search engines, marketplace feeds, or your own customers. And yet, for most e‑commerce organisations, the catalogue remains one of the most underinvested and manually maintained parts of the operation.
That is precisely where the Catalog & Product Agent comes in.
The problem most teams recognise but rarely solve
Ask any e‑commerce or category manager about their catalogue and you will hear a familiar set of issues: Products arrive from suppliers, ERPs or PIMs with inconsistent attributes, missing descriptions and no SEO structure. Translations are done manually, in batches, and are often out of date. Images are sized for one channel and not optimised for others. Cross‑sell and upsell relationships exist in someone’s head, or in a spreadsheet, rather than systematically in the platform. The team spends most of its time maintaining existing content rather than improving it.
The result is a catalogue that is always slightly behind. New products launch with thin content. High‑performing items miss relevant attributes. Marketplace feeds reject records because of formatting inconsistencies.
This is not a people problem. It is a process and tooling problem.
What the Catalog & Product Agent does
A Catalog & Product Agent is a set of automated capabilities that handles the repetitive, rules-based and data-intensive work of keeping a product catalogue accurate, complete and optimised – continuously, not in monthly batches.
In practice, it operates across five areas:
1. Automated catalogue creation and updates from source systems
Rather than manually importing or re-keying data from PIM, ERP or marketplace feeds, the agent monitors source systems and applies updates in near real time. When a supplier sends a new product file, or an ERP update changes stock status or pricing, the agent ingests, validates and maps that data to your catalogue structure automatically. It flags exceptions – missing mandatory fields, out-of-range values, duplicates – for human review, rather than silently creating bad records.
This reduces the lag between product availability and catalogue readiness, which has a direct impact on sales for new launches and seasonal ranges.
2. Enrichment of titles, descriptions, attributes, translations and SEO metadata
Thin product data is one of the most consistent causes of poor on-site conversion and low search visibility. The agent addresses this by enriching existing records: generating or improving titles and descriptions based on category context, brand guidelines and SEO requirements; completing missing attributes (colour, material, size range, technical specifications) from available data sources; producing translations into the required languages with local market conventions; and generating SEO metadata – meta titles, descriptions, structured data markup – aligned with how customers and search engines actually look for products.
This is not about replacing editorial judgment. It is about ensuring that every product in the catalogue reaches a minimum standard of completeness, and that the team’s time is spent on exceptions and high-value content rather than routine data entry.
3. Image optimisation and resizing for different channels
Product imagery is often one of the most time-consuming parts of catalogue management. Requirements differ by channel: your webshop, a marketplace, a retail media unit, a printed brochure or a social feed each have different dimensions, file size limits and background requirements. The agent handles the mechanical work: resizing, reformatting, compressing and delivering the correct asset to the correct channel. Where image quality is insufficient, it flags items for a reshoot rather than publishing poor assets automatically.
4. Cross‑sell and upsell relation tagging
Effective cross‑sell and upsell logic rarely makes it into production at scale. The relationships exist commercially – a tent should suggest a sleeping bag; a printer should suggest compatible ink – but implementing and maintaining those connections across thousands of SKUs is labour-intensive. The agent applies association logic based on category rules, purchase history patterns and attribute relationships, tagging products with relevant cross‑sell and upsell connections systematically. These can then feed directly into the platform’s recommendation engine.
5. Prioritisation: enrich high‑performing items first
Not all products are equal. A catalogue of 50,000 SKUs cannot be enriched overnight, and not every item warrants the same level of investment. The agent uses performance data – traffic, conversion rate, margin, return rate, search visibility – to rank the catalogue by enrichment priority. The items that drive the most revenue or have the most potential are addressed first. Long‑tail products receive a baseline level of content that meets minimum standards without disproportionate effort.
This prioritisation logic ensures that resource, whether human or automated, is directed where it has the most commercial impact.
Why this matters for agentic commerce
Return for a moment to the concept of agentic commerce. When a software agent is tasked with finding “a waterproof jacket for hiking in cold weather under €150”, it will query catalogues the way a structured database works: it looks for attributes, not stories.
If your jacket does not have “waterproof” as a validated attribute, a clear temperature range, and an accurate price and stock status, that agent will not surface it – or worse, it will surface it and fail on fulfilment.
The Catalog & Product Agent ensures that your catalogue is the kind of structured, complete, reliable data source that both human customers and software agents can work with effectively.
This is not a future concern. Search engines already parse structured data. Marketplace feeds already reject incomplete records. Recommendation engines already depend on attribute quality. Agentic commerce simply raises the standard further.
How Commerce Partners approaches catalogue readiness
At Commerce Partners, catalogue quality forms a core part of our platform selection and implementation work. When we assess a client’s readiness for a platform migration or a new commerce initiative, we look at the current state of product data across source systems and how it maps to the target platform; the gap between existing content and what is required for search, marketplace and agentic use cases; and the tools and workflows available for ongoing enrichment, and where automation can reduce manual effort.
We help clients select the right combination of PIM, product content and enrichment tooling for their catalogue complexity and team capacity. We also structure the data migration and enrichment process so that a new platform launches with content that is fit for purpose, rather than carrying forward years of data debt.
A practical starting point
Catalogue quality does not improve by itself, and a complete overhaul rarely makes sense as a standalone project. The more effective approach is incremental:
1. Audit your current catalogue against the requirements of your platform, your key channels and your search/discovery tool. Identify where the gaps are largest and where the commercial impact is highest.
2. Automate the routine work – feed ingestion, basic attribute mapping, image resizing – so that the team’s capacity is freed for content decisions rather than data management.
3. Prioritise enrichment using performance data, so that effort is concentrated on the products that matter most.
4. Build towards structured, agent-ready data as a standard, not as a one-off project.
Each step builds on the last. And each step makes your catalogue more valuable – for customers, for search engines, for marketplaces, and increasingly for the software agents that will play a growing role in commerce over the coming years.
If catalogue quality and product data are on your agenda – whether as part of a replatforming project, a marketplace expansion or a broader digital transformation – we are happy to share how we approach this in practice. Contact us at commerce-partners.com.
Originally published on LinkedIn
This article was first published in the AI in e-Commerce newsletter on LinkedIn. Read the original post and join the conversation.