Augmented analytics and anomaly detection for next-generation eCommerce
Evaluate ROAS across ad networks • Identify trending products and categories
Keep an eye on margins and stock • Analyze product returns • Save hours of reporting time





Make data-driven decisions
Get a real-time view of all your shop’s relevant KPIs through pre-defined business intelligence dashboards that are easy to understand and navigate.

Spot anomalies and opportunities
Never get caught off-guard by using our AI-driven proactive notifications and alerts. Aqurate is your shop’s copilot, constantly monitoring all your KPIs, including ROAS, CLV, AOV, CAC, product and category margins, conversion rates, and estimated stock depletion dates.



Seamlessly integrate
all your data sources
Getting data from multiple sources and reconciling it is hard. Doing that continuously is even harder - so we do it for you! Hit the ground running with out-of-the-box no-code connections for all your shop, traffic, and ads data.

Designed for eCommerce
Aqurate is built by a team who truly understands eCommerce. That means that it works out-of-the-box for your shop and might even surprise you with some relevant new analyses and metrics you can use to better understand your shop.

AI-driven anomaly detection (alfa)
Proactive notifications and alerts are at the very core of Aqurate, so you can rest assured that we spot potential problems and opportunities early. Our AI-driven anomaly detection models look at all your data as well as seasonality to maximize relevance.

Reclaim your
time
eCommerce and marketing managers spend up to 190 hours per year gathering data and computing KPIs. Aqurate does the dirty work for you, so you can focus on turning data into business strategy and still have time for an extra cup of coffee or tea.
Trusted by some of the fastest growing
retailers and eCommerce players in Europe

“We learned a lot about our customers and their behavior. We are now able to better tailor our product portfolio and messaging.”
Radu Balaceanu
Co-Founder
