Sensors Data

Sensors Data

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Sensors Data is a Chinese user behavior analytics platform that turns event data into product, growth, and marketing decisions for large organizations.

Overview

Sensors Data provides the full chain from data collection and governance to analysis and activation. Client-side and server-side SDKs funnel user events into a unified behavioral data model, and the analysis layer supports funnel, retention, path, and cohort exploration alongside A/B testing for validating changes. A marketing automation module closes the loop by turning findings into targeted outreach — behavior-based segments, lifecycle campaigns, and triggered messages. The platform supports private deployment for industries such as finance and retail where data residency matters, and an AI assistant helps business users answer their own questions without SQL.

Key Features

  • Cross-platform event collection into a unified behavioral data model
  • Funnel, retention, path, and cohort analysis with segmentation
  • A/B testing and experimentation platform
  • Marketing automation and lifecycle campaign management
  • Private deployment options with data governance tooling

Pricing

Sensors Data sells enterprise subscriptions and private deployments priced by data volume, modules, and hosting model; evaluations are arranged with the sales team.

Who Is It For

Internet, finance, and retail enterprises practicing data-driven growth and fine-grained user operations at scale.

Typical adoption starts with instrumenting key business events and stabilizing metric definitions, then building funnel and retention dashboards to locate where users drop off. Segments discovered in analysis feed directly into marketing automation, so insight becomes action without export steps. The AI query assistant matters for smaller analytics teams: routine questions no longer queue behind a data engineer. For compliance-heavy industries, private deployment keeps data in-house while shared governance ensures every department reads the same metrics the same way — the precondition for trusting behavioral data over time. Experiment results feed back into the same dashboards, so teams can watch a validated change move the metrics it was designed to move.

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