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AI data analysis

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Loops

AI data analysis

Loops is an AI-driven data analytics platform designed to uncover undiscovered growth potential in product data and improve KPI performance. It can track KPI declines in real time, automatically identify trends and anomalies and analyze root causes, covering potential explanatory factors such as marketing, product performance, bugs, seasonality, demographic changes, and experiment impact, and rank them by impact size. Loops uses a proprietary causal inference model to simulate A/B tests without the need for A/B tests to evaluate the impact of actions, and it can be used even with low traffic; it can also show hidden user journeys and funnels that affect conversion or churn, and supports locating where the data is for analysis. It officially states that it can let one analyst do the work of five data scientists, increase experiment success rates by more than 80%, improve conversion, retention, and revenue metrics by 20%–200%, and achieve more than 80% accuracy in measuring product launch impact compared with real A/B tests.

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