Centralise all
marketing data
Marketing data is scattered across platforms, spreadsheets and dashboards that contradict each other. Datafy brings it together in a uniform model that is always up to date.
Fragmented data, conflicting figures
The average marketing department works with ten or more data sources. Ad platforms, analytics, the e-commerce platform, affiliate networks, email and offline media each deliver their own figures in their own definition.
Combining them often happens manually in spreadsheets. That costs time, is error-prone and produces figures that contradict each other. Every question from leadership becomes a research task.
The problem is not too little data. The problem is that the data is not connected.
How Datafy connects your data
Datafy normalises all your sources into a data model you can act on.
All sources connected
Ad platforms, analytics, e-commerce, affiliate and offline media come together in one model.
Normalised and validated
Sources are brought to uniform definitions and data streams are monitored and cleaned.
Data quality monitored
Discrepancies between spend and revenue above ten percent are flagged for analysis.
Always up to date
The data model refreshes automatically, so reporting and the model work from the same figures.
What it delivers
With a centralised data model, the manual work disappears and so do the conflicting figures. Reporting becomes faster and reliable, because everyone works from the same source.
More importantly: only on connected data can you build a model that forecasts and optimises. Data centralisation is the first step toward marketing intelligence. Data quality is a hard prerequisite for reliable outcomes.
Frequently asked questions
Which sources can Datafy connect?
Among others: Google Ads, Meta Ads, TikTok Ads, affiliate networks such as Daisycon, TradeTracker and Awin, Google Analytics 4, e-commerce platforms such as Shopify, WooCommerce and Magento, and offline media data.
Why do my current reports contradict each other?
Because each platform uses its own definitions and attribution windows. Without normalisation to uniform definitions, figures do not add up and sources appear to contradict each other.
What does Datafy do with poor data quality?
Datafy flags it. Discrepancies between spend and revenue greater than ten percent need to be resolved before analysis, because reliable data is a prerequisite for a reliable model.
Is data consolidation enough, or do I need more?
Consolidation is the foundation. The value is created when you build a model on that connected data that forecasts and optimises budget. Consolidation is the first step, not the end goal.
Stop dealing with figures that contradict each other.
Book a demo and see how Datafy brings all your marketing data together.
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