A client needing a clean, recurring product catalog data feed from several retailers and marketplaces, mapped to its own category taxonomy for AI shopping and content features.

Use Case

Product catalog data feed for AI shopping & content

Region

Multi-market

Sources

Several retailers and marketplaces

Number of sources

Multiple

Key metrics

Category Mapping – Client Taxonomy

Key metrics

Attributes – Normalised

Key metrics

Feed – Recurring & QA-Checked

Contact Sales

Key Takeaways

Actowiz Solutions delivered a recurring product catalog data feed for a consumer-tech company running an AI-powered shopping and content platform. We collected public product listings from several retailers and marketplaces, normalised titles, prices and attributes, mapped every product to the client's own category taxonomy, and delivered QA-checked files on a fixed schedule ready for search, recommendations and AI-generated content.

What did the client need?

The client's app answers shopping questions and builds product round-ups and comparison content, all of which depend on a broad, current catalog. Yet every retailer organises and names products differently and changes its pages often.

The team wanted one scheduled feed where every product already sat in the right node of its own taxonomy, so engineers could build features instead of maintaining scrapers.

What made this hard?

Many catalogue structures. Each source uses its own category tree, layout and naming.
Mapping to a custom taxonomy. Categories had to map to the client's own taxonomy, not a generic standard, and survive retailers renaming or splitting categories.
Messy attributes. Size, colour, material, capacity and specification fields arrive as free text, tables or variant selectors, in mixed units and formats.
AI-ready output. Empty fields, duplicates or wrong categories flow straight into the AI answers users see.
Recurring change. Products launch, sell out and disappear between runs.
Clear usage boundaries. Images were supplied only as public URL references, not as a licensed image dataset, and no personal data was collected.

How did Actowiz solve it?

We built a managed pipeline from collection to delivery, with mapping and QA as core steps rather than afterthoughts.

Approach

Source-by-source crawlers. Dedicated crawlers collected public product pages, variants and category paths on the agreed schedule.
Taxonomy mapping layer. A mapping table linked each source category path to a node in the client's taxonomy, with rule-based and model-assisted suggestions reviewed by our analysts before going live.
Attribute normalisation. Titles were cleaned, units and currencies standardised, and specification text parsed into named attribute fields in a consistent schema.
Change tracking. Each run flagged products as new, updated or removed versus the previous delivery.
QA before every delivery. Automated checks for field completeness, duplicates, price sanity and unmapped categories, plus manual spot checks on samples.
Agreed delivery format. Files or API delivery in the client's preferred structure.

Data Attributes / Fields

Field	Description
product_id	Stable Actowiz identifier for the product across runs
source_name	Retailer or marketplace the listing came from
product_url	Public product page URL
product_title	Cleaned product title
brand	Brand name, normalised to one spelling
source_category_path	Category breadcrumb as shown on the source site
client_category_id	Mapped node in the client's own taxonomy
price / currency	Current listed price and ISO currency code
attributes_json	Normalised attributes such as size, colour, material, specs
image_urls	Public image URLs as references only (no image files or licences)
availability_status	In stock / out of stock as displayed
change_flag / crawl_date	New, updated or removed since last run, and collection date

What were the results?

One feed instead of many sources. The client receives one consistent product catalog data feed in place of separate retailer formats.
Products land in the right category. Every delivered product carries a client taxonomy ID, so search, filters and AI-generated round-ups use the same structure.
Cleaner inputs for AI features. Normalised attributes and QA checks reduce empty or inconsistent fields reaching the platform's AI answers.
Fresh catalog every cycle. Change flags let the client add, update and retire products incrementally on each delivery.

Project at a Glance

Metric	Value
Use Case	Product catalog data feed for an AI shopping & content platform
Region	Multi-market
Sources	Several retailers and marketplaces
Metrics	Product details, prices, availability, normalised attributes, image URL references
Reconciliation / Method	Source category paths mapped to the client taxonomy; analyst-reviewed mapping; de-duplication
Cadence	Recurring (agreed per project)
Output	QA-checked feed via file or API

Client Feedback

“Actowiz delivered one recurring feed where every product already sits in our own taxonomy, with clean attributes and QA built in. Our engineers finally build features instead of maintaining scrapers.”

— Head of Product, AI Shopping & Content Platform

Frequently Asked Questions

Q: What is a product catalog data feed?

A: A structured file or API stream of product listings – titles, brands, prices, attributes, categories and image URLs – delivered on a schedule to keep a platform's catalog current.

Q: Can products be mapped to our own category taxonomy?

A: Yes. We map each source category path to your taxonomy, review the mapping with analysts and update it when retailers change their category trees.

Q: Do you deliver product images?

A: We deliver public image URLs as references. We do not supply licensed image datasets or image rights; usage of images remains subject to each source's terms.

Q: How do you keep the feed accurate between runs?

A: Each delivery passes completeness, duplicate, price and mapping checks, and change flags show what is new, updated or removed.

Need a Taxonomy-Mapped Catalog Feed?

Share your company email, target retailers and taxonomy, and we will scope a recurring feed with QA built in. Visit actowizsolutions.com to discuss your data requirement.

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