Loops is a no-code analytics platform that utilizes causal inference models to identify the root causes of KPI fluctuations in real-time, enabling product and data teams to make informed decisions quickly. By automating the analysis of trends and anomalies, Loops helps users uncover hidden growth opportunities and measure the impact of changes without the need for extensive A/B testing.
Funding
$17.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Product and data teams often struggle to understand the underlying causes of key performance indicator (KPI) fluctuations, leading to inefficient decision-making and missed growth opportunities. Traditional methods for analyzing trends and anomalies can be time-consuming and require extensive A/B testing, making it difficult to quickly identify and address the root causes of KPI changes.
Solution
Loops is a no-code analytics platform that leverages causal inference models to automatically identify the root causes of KPI fluctuations in real-time. By analyzing various potential explainers, such as changes in traffic, new feature releases, and marketing performance, Loops pinpoints the most impactful opportunities hidden within data. The platform enables users to measure the impact of changes without the need for extensive A/B testing, allowing for faster and more informed decision-making. Loops also identifies hidden user journeys and funnels that lead to conversion or churn, providing a comprehensive understanding of user behavior and its impact on KPIs.
Target Audience
Loops is designed for product managers, data analysts, and growth teams who need to quickly understand the drivers of their KPIs and make data-driven decisions to improve business outcomes.
Features
- Real-time KPI monitoring and anomaly detection
- Automated root cause analysis using causal inference models
- Identification of hidden user journeys and funnels
- Measurement of feature release impact without A/B testing
- No-code setup and integration with existing data warehouses and analytics solutions
- Prioritization of hypotheses with a higher likelihood of success
- Simulation of A/B tests to show the impact of actions, even with minimal traffic