Send Datatrics the products worth showing.

Datatrics is a Dutch customer data platform (CDP) and marketing automation tool used by e-commerce and retail brands to personalize on-site content, email and product recommendations. It builds a 360-degree profile for every visitor by combining first-party data — website behaviour, purchases, email engagement — with external signals such as weather, search trends and economic indicators, and uses that profile to drive AI-generated recommendations, dynamic emails and on-site personalization.

To generate product recommendations, dynamic banners or personalized emails, Datatrics needs a structured feed of your product catalogue, similar to the feeds you already maintain for Google Merchant Center or comparison shopping sites.

Datatrics uses the product catalogue you import to match items against each visitor's behavioural profile, powering features such as personalized product recommendation blocks on your website, dynamic "recently viewed" or cross-sell content in emails, and abandoned-cart or browse-abandonment messages that reference real products, prices and images. Without a connected feed, Datatrics can still build customer profiles from behavioural data, but it cannot enrich recommendations or dynamic content with actual product details such as price, stock or imagery.

A feed that is complete, accurate and kept in sync with your live store directly affects the relevance of the recommendations Datatrics generates and the number of dead links or outdated prices customers see.

Datatrics offers two distinct routes for importing product data, and picking the right one depends on how close your existing feed already is to its expected structure.

1. Direct feed URL: if you already have an XML feed built to the Google Product Feed (Merchant Center) specification, you can paste that feed's URL straight into Datatrics' feed integration screen and it will fetch and import products immediately, with no field mapping step.
2. Custom Importer: if your feed uses a different structure, Datatrics' Custom Importer accepts either a CSV file upload or an XML file loaded from a URL. You specify the XML element that marks the start of each item, then manually map your feed's columns/elements to Datatrics fields and choose which field serves as the unique identifier. The same importer is also used for Conversions, Returns and Profile data, not just product Content.

For the direct connection method, Datatrics expects an XML feed built to the Google Product Feed / Google Merchant Center guidelines — the same schema most stores already generate for Google Shopping. Point Datatrics at that feed's URL and it parses it right away.

If your data doesn't already follow that structure, use the Custom Importer instead, which accepts .csv or .xml files. For XML files you must tell Datatrics the name of the repeating element that wraps a single product (for example <item>), and for both file types you then map each source field to a Datatrics field and designate one column as the unique product ID.

Datatrics documents the following fields for a standard product feed. The first group is described as required for a usable feed; brand, EAN and stock appear in Datatrics' own sample e-commerce feed as recommended additions that improve matching and filtering.

Datatrics also accepts additional custom fields beyond this list and will import them alongside the standard set.

Feedance can generate the exact feed structure Datatrics expects, so you don't have to hand-build or maintain an extra export.

1. In Feedance, map your product data to a Google Product Feed-compatible XML output, including id, name, url, price, description, image and category fields, plus brand, EAN and stock where available.
2. Publish the feed to the stable HTTPS URL Feedance hosts and keeps automatically refreshed.
3. In Datatrics, go to the feed integration screen at app.datatrics.com/integrations/feed/ and click Install to open the settings screen.
4. Paste your Feedance feed URL into the settings screen. Datatrics fetches the feed immediately and shows a success or failure confirmation.
5. If your catalogue needs a non-standard structure instead, use Datatrics' Custom Importer, specify the XML item element (or upload the CSV Feedance generates), map the fields, and select your unique ID column.

For feed-based connectors, Datatrics lets you configure an update frequency; if the feed's content hasn't changed within that configured window, items are left as-is rather than re-imported. Datatrics does not publish a single mandatory refresh interval for every feed type, so the right cadence depends on how often your prices and stock levels actually change.

As a general recommendation, refreshing at least daily — and more often for stores with frequent price or stock changes — keeps the product data behind your recommendations and dynamic emails accurate. Feedance can run refreshes on a schedule so the feed Datatrics reads is never stale.

Datatrics' documented feed issues are primarily about retrieval and structure rather than specific validation error codes:

1. Feed unreachable or invalid: when you submit a feed URL, Datatrics attempts to retrieve it and shows a success or failure popup; an unreachable URL or malformed XML results in a failed import.
2. Incorrect "Element" value in the Custom Importer: when importing XML through the Custom Importer, you must enter the exact name of the element where a single item starts (for example item). If this doesn't match your feed's actual structure, the import fails.
3. No unique ID selected: the Custom Importer requires you to designate which mapped field serves as the item's unique identifier before the import can complete.

The following are general feed-hygiene practices, not Datatrics-specific requirements:

1. Keep product URLs and images pointing to live, current pages so recommendations don't lead customers to broken or outdated content.
2. Populate brand and EAN where available — richer identifiers help matching and filtering logic produce more relevant recommendations.
3. Exclude discontinued or permanently out-of-stock items, or keep the stock field accurate, so personalized content doesn't surface products customers can't buy.
4. Keep category names and URLs aligned with your live site navigation so category-based personalization and content matching stay accurate.

Can I use my existing Google Shopping feed for Datatrics? Yes — Datatrics accepts XML feeds built to the Google Product Feed / Merchant Center guidelines directly via its feed URL integration.

What if my feed isn't in that format? Use Datatrics' Custom Importer, which accepts CSV or XML files and lets you manually map fields and choose a unique ID.

Does Datatrics support more than product data? Yes — the same Custom Importer is also used to bring in Conversions, Returns and Profile data, in addition to product Content.

How do I know if my feed connected successfully? Datatrics shows a success or failure popup immediately after you submit a feed URL, based on whether it could retrieve and parse the feed.

How does Feedance help with a Datatrics connection? Feedance builds and hosts a Google Product Feed-compatible XML (or a mapped CSV for the Custom Importer) and keeps it refreshed on a schedule, so you can paste one stable URL into Datatrics instead of maintaining the export yourself.

Datatrics is a customer data platform (CDP) that combines artificial intelligence (AI) and machine learning (ML) to help businesses personalize their marketing efforts. The platform was launched in 2012 and hails from the Netherlands.

Datatrics provides a suite of powerful marketing tools that assist companies in enhancing customer experiences, optimizing marketing campaigns, and improving overall business performance. The platform collects and analyzes data from various sources, such as websites, email marketing, CRM systems, and online advertisements, to derive valuable insights and create personalized customer journeys.

One of the key features of Datatrics is its personalization engine, which uses AI and ML algorithms to deliver dynamic content to customers based on their behavior, preferences, and predictive analysis. By capturing and analyzing customer data in real-time, businesses can tailor their marketing messages, recommendations, and interactions across multiple channels, including websites, email marketing, mobile apps, and more. This level of personalization enhances customer engagement, drives sales, and fosters long-term customer loyalty.

Furthermore, Datatrics offers marketers a user-friendly interface for creating and managing customer segments, defining marketing goals, monitoring campaign performance, and analyzing key metrics. Its intuitive dashboard provides a comprehensive view of customer behavior, allowing marketers to track conversions, measure engagement, and identify opportunities for improvement.

The platform also supports creating marketing automation workflows, allowing businesses to automate repetitive tasks, nurture leads, send personalized communications, and streamline marketing operations. This automation simplifies the process of creating, managing, and executing complex marketing campaigns.

While Datatrics is headquartered in the Netherlands, it serves clients globally across various industries, including e-commerce, retail, hospitality, banking, and more. Its platform has been adopted by numerous businesses seeking to harness the power of data-driven marketing to improve customer experiences and drive business growth.

In summary, Datatrics is an innovative customer data platform that was launched in 2012. Originating from the Netherlands, it integrates AI and ML technologies to empower businesses in gaining deeper customer insights, implementing personalized marketing strategies, and achieving better overall marketing performance.