Data to AI™ / Claude/Google Merchant Center
Find the feed issues that keep products off Google Shopping by asking Claude, instead of scrolling through diagnostics one product at a time.
Less tokens, better answers.
Claude
Which feed issues keep the most of our products out of Shopping right now?
Invalid GTINs affect 412 of 5,020 products (8.2%), more than price mismatches and small images combined (283).
| Issue | Item Level Issue Attribute Name | Products | Share of catalog |
|---|---|---|---|
| Invalid GTIN Product statuses | gtin | 412 | 8.2% |
| Price mismatch Product statuses | price | 186 | 3.7% |
| Image too small Product statuses | image_link | 97 | 1.9% |
Counted from the latest Product statuses run, which pulls every current product; the dataset has no date range.
Google Merchant Center holds the product listings that appear on Google Shopping. Dataddo extracts two datasets: Products, with feed attributes such as price and availability, and Product statuses, with approval status and item-level issues.
Group Product statuses by Item Level Issue Code, count the affected products and show the Item Level Issue Description for the top five.
A shopping marketer starts the day in Claude. The fix list begins with the issue that hides the most items, not with whatever sits at the top of the diagnostics page.
Query Products through the dataddo server and write every Offer ID with an empty GTIN and MPN to fixes/missing-identifiers.csv.
The team that maintains the feed script keeps the fix list next to the code that generates the feed, and reviews both in the same pull request.
For our promoted brands, list offers whose Sale Price has no Sale Price Effective Date, with Offer ID, Title and Price.
Before the promotion goes live, Claude checks the sale setup across the whole catalog, so missing or expired dates are fixed before launch day.
Data to AI™ is free while in private pre-release. We onboard teams in waves and shape the product with their feedback. At launch, it will be priced like the AI assistants your team already uses. Need tailored contracts or volume pricing? Talk to us about Enterprise.
Serve governed business data to Claude, ChatGPT and other AI tools over MCP.
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| Without Dataddo |
With Dataddo
|
Outcome for you | |
|---|---|---|---|
| Feed diagnostics in Claude | Someone downloads diagnostics, filters them by issue and pastes the counts into a chat each time the feed changes. | Claude reads Product statuses through the connector, with Item Level Issue Code, Attribute Name and Description as fields it can group. | Issues counted for you |
| What the fields mean | Columns such as Item Level Issue Servability arrive without definitions, so the model has to guess what each value implies. | The Dataddo semantic layer gives Claude the business description of each field, including Item Level Issue Servability and Destination. | No guessing at columns |
| Feed scripts in a repository | Developers export the catalog by hand to see which offers lack identifiers before they change the feed script. | Claude Code reads Products through the dataddo server inside the repository, so the fixes are written next to the feed code. | Fixes land in code review |
| Catalog snapshot timing | An uploaded export shows the catalog from some earlier day, and nothing in the chat says which day. | Every scheduled run pulls the full current catalog, and Claude can call data_status to report when that run happened. | A known catalog date |
| Token consumption | Claude spends tokens exploring raw Google Merchant Center columns, sampling rows and retrying until it understands the data. | Field definitions and relations are supplied up front, so the model skips the exploration and goes straight to the answer. | Less tokens per answer |
| Answer quality | Prone to wrong joins, invented fields and numbers that are hard to check. | Answers grounded in defined fields. In the Dataddo benchmark, 78.5% of questions were answered correctly, against 65.5% with plain CSV files. | Better answers |
The Google Merchant Center datasets marketing teams use most, with their real field names. Claude queries them by name through the Dataddo semantic layer.
List of curated datasets
Need a dataset, metric, or attribute you don't see?
Tell us what's missing and we'll add it to the connector.
Neither dataset uses a date range: every run on your schedule, for example daily, pulls all products and statuses currently in Merchant Center. The optional Dataddo Extraction Timestamp column shows when each row was read.
Google Merchant Center connector →We asked 43 pre-registered questions of three real datasets - Google Search Console, HubSpot deals and Google Ads - and delivered the same rows to the same model in four ways. Only the data layer changed.
of questions answered correctly - the best of the four delivery methods tested
fewer confidently wrong answers - 14.0% of runs against 24.0% and 26.3%
more correct answers on messy CRM data - better on 8 questions, worse on none
Same model, prompts and rows in every condition; 759 graded runs, ground truth frozen before any run. On Google Search Console alone, documented CSV files did as well as Data to AI™ - the advantage comes from messier data such as HubSpot deals.
Read the benchmark →Create two Google Merchant Center sources in Dataddo, one for Products and one for Product statuses, and attach them to a Claude destination or AI Model. In Claude, add a custom connector named Dataddo Data Access with the URL https://headless.dataddo.com/mcp-data and sign in. For Claude Code, run claude mcp add.
Yes, from Product statuses. Each item-level issue has a code, the affected attribute, its servability and a description, so Claude can group products by cause.
The datasets have no date range: each run pulls all products currently in Merchant Center. Claude sees the feed as of the latest run; data_status tells it when that was.
Yes. Run claude mcp add with the Dataddo URL and sign in with /mcp. Claude Code can then query Products and Product statuses while you work on feed scripts.
No. Claude reads extracted data only and can list what to change. The feed itself is updated by your own process.
Any plan supports custom connectors; Free allows one. Pro and Max users add Dataddo themselves, and on Team and Enterprise an Owner adds it once while members sign in with their own Dataddo account.
Yes, from the Products dataset. It carries Price, Sale Price, Sale Price Effective Date, Availability and Availability Date for each offer, so Claude can list mispriced or out of stock items.