What is Loops?
Leveraging proprietary causal inference models and generative AI, this platform moves beyond standard analytics to uncover the 'why' behind Key Performance Indicator (KPI) fluctuations. It automatically monitors KPIs, identifies trends and anomalies, and determines the root causes, such as changes in traffic, new feature releases, seasonality, or population shifts. The system analyzes numerous potential factors and ranks them by their impact, providing clear explanations for performance changes.
The tool enables businesses to understand complex user journeys and funnels that influence conversion and churn rates. It uniquely allows for measuring the impact of product changes or initiatives without requiring traditional A/B testing, simulating outcomes even with limited data. Furthermore, its AI assistant delivers concise insight summaries, alerts on performance shifts, root cause analyses, and recommended actions directly to team communication channels like Slack, MS Teams, and email, facilitating data-driven decision-making across the organization.
Features
- KPI Monitoring & Root Cause Analysis: Automatically tracks KPIs, identifies trends/anomalies, and provides ranked root causes for changes.
- Causal Inference Analysis: Employs proprietary causal models to understand cause-and-effect relationships and pinpoint high-impact opportunities within data.
- A/B Test Simulation: Measures the impact of actions and feature releases using causal inference, simulating A/B test outcomes without needing live tests.
- User Journey Analysis: Identifies and analyzes hidden user journeys and funnels impacting conversion and churn.
- Loops Assistant (Gen-AI Alerts): Delivers AI-generated insight summaries, KPI alerts, root cause explanations, and recommended actions via Slack, MS Teams, and Email.
- Explainability Scoring: Quantifies the specific influence of different segments on KPI fluctuations for deeper understanding.
Use Cases
- Identifying the root causes behind KPI increases or decreases.
- Discovering hidden growth opportunities within product usage data.
- Measuring the impact of new product features or marketing campaigns without A/B tests.
- Optimizing user conversion funnels by understanding key behaviors.
- Developing strategies to improve user retention based on causal insights.
- Prioritizing product development and marketing efforts effectively.
- Streamlining reporting and business reviews with automated insights.
