E-commerce Catalogs
Adjust your commercial offer in real time and without technical friction. Take control of inventory by tracking your competition's stock.
What our clients say
Real results from companies using our platform
Automating competitor price and stock monitoring during Black Friday let us adjust our own promotions in real time and avoid stockouts on our best-selling SKUs.
Jenna F.
Head of E-commerce
Being able to monitor fluctuations in real time saved us from losing a 15% margin we weren't accounting for in external shipping costs.
Mark K.
Growth Analyst
Key features
Everything you need to succeed
Catalog coverage tailored to you
We work on the categories, brands or stores you define — no need to cover an entire catalog if your case doesn't call for it. We can start with a narrow subset to validate that the data answers your business question, and add categories as the use case grows.
Matching between your catalog and your competitors'
We define the matching key between your products and other stores': GTIN/EAN when it exists, or normalized title plus brand and attributes when it doesn't. Size, color or bundle variants are delivered as separate rows tied to the same parent product, so the comparison is exact.
Configurable frequency for your case
A large catalog does not need the same frequency as active price monitoring. We define the right cadence in the first meeting: daily or several times a day during events like Black Friday, weekly for catalog surveys, monthly for assortment analysis.
Delivery ready for your feed or your BI tool
CSV, Excel, JSON, via API, or direct import to your database. The schema stays stable across deliveries, so the file can plug directly into a Google Shopping or Meta Catalog feed, or your BI tool, without reprocessing every time.
What the e-commerce dataset contains
Every delivery arrives with a fixed schema, built to plug directly into your feed or database. These are the fields we usually deliver; the final set is agreed at kickoff based on your use case.
Fields delivered
- SKU
- Store's internal identifier, the key for tracking one product over time.
- Title
- Product name as published.
- Description
- Product description text, useful for content analysis or building your own catalog.
- Category
- Site classification, for aggregating and comparing by segment.
- Price
- Selling price at the moment of capture.
- Variants (size/color)
- Each variant as a separate row, linked to the parent product.
- Image URLs
- Direct links to the product photos.
- Stock
- Availability at the moment of capture.
- Brand
- Product manufacturer or brand.
- GTIN
- Universal code — when it exists, the most reliable key for matching across stores.
- Rating
- Score and number of reviews, when the site publishes it.
- Source URL
- Direct link to the product, to audit any figure against the source.
Sources we typically monitor
These are examples of the kind of source we cover; the actual list is built from your catalog and your competitive set. If a store matters to your category and publishes its catalog, we can monitor it, regardless of the platform it runs on.
- MercadoLibre
- Amazon
- Shopify (products.json)
- VTEX (Falabella, Éxito)
- Liverpool
How to know if you need to monitor e-commerce catalogs
If your team manually checks competitor sites to know when a price dropped or a product ran out of stock, and the finding arrives days after the promotion already hit your sales, you need this service. The problem is not a lack of attention — it is that no team can sustain the review pace a catalog of thousands of SKUs spread across dozens of stores demands. The symptom is easy to recognize: the assortment report is built on Monday with data from the week before, and by the time it circulates, three competitors have already relaunched their promotions.
How we help you
Our e-commerce mapping service navigates thousands or millions of product pages from the stores you define, comparing prices, stock and attributes to deliver structured, comparable data. The hard part is not reading a product page: it is making sure the product you are comparing is actually the same one, in the right variant, with a stock figure that is still valid by the time you use it.
You define which categories, brands or stores to monitor. We set up the extraction, including stores with anti-bot protections.
We deliver updated prices, stock and attributes at the frequency your case needs, in a stable schema.
We align size, color or bundle variants to the parent product so the analysis stays consistent.
When a store changes its site, we handle it before your feed arrives with missing data.
Boost conversions by integrating an invisible engine that monitors your catalogs
Tell us which categories and stores matter to your business, and we will show you what the dataset would look like before you commit to anything. Most projects start with a narrow category to validate the matching before scaling to the full catalog.
Frequently asked questions
Clarify your doubts about how our data process works.
Marketplaces and individual stores: MercadoLibre, Amazon, stores built on Shopify, VTEX or Magento, and retailers' own sites. We cover the list you define, not a generic catalog.
Yes. We can run the same survey across different countries and return each price in its original currency, so the conversion and comparison stays on your side with the exchange rate you use.
Each variant is delivered as its own row, linked to the parent product by SKU or GTIN, with its own price, stock and image where applicable. That way you can analyze availability by size or color without losing the link to the main product.
Both. We can deliver image URLs for you to use directly in your system, or download the files if your case requires it. We define this based on how you will consume the data.
Yes, it is one of the most common uses. We define the delivery schema to match the fields each feed requires (title, price, availability, GTIN, image), so you can connect the file without reprocessing it.
In many cases yes, within what is technically accessible and permitted by the source's terms. We evaluate this case by case in the first meeting before committing to coverage.
In normal periods, weekly or every few days is usually enough for a catalog survey. During events like Black Friday, we recommend running every 4-6 hours to capture price and stock changes in time.
CSV, Excel, JSON, via API, or direct import to your database. We define the schema and destination at the start.
Yes. When a store redesigns its site or changes how it publishes prices and stock, adjusting the extraction is our job, not an extra.
Yes, and it is usually the better call. Most projects start with one category to validate that the matching and the schema answer the business question before scaling to the rest of the catalog.
Need to add engineers to your team instead of receiving ready-made data?
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