Your team supports the data and analytics needs of the business, spanning Product, Growth, Sales, and Customer Success.
Your team must deliver consistent results across business functions, especially as product-led growth has led to improved cross-functional alignment.
You directly support Product & Growth teams and are responsible for tracking and reporting on key product metrics that drive critical business decisions.
You are routinely asked to create new BI reports that require new data pipelines and new SQL queries to be written.
Vertically-integrated product analytics tools collect and ingest customer data outside your secure environment, creating security and privacy concerns. This silo also makes it difficult to provide a complete and consistent view of the customer journey.
Data is duplicated when event data is exported to the warehouse or when reverse ETL is used to move snapshots back. This leads to inconsistent data between BI and product analytics tools.
You are inundated by time-critical requests for one-off reports. Authoring new queries is time-consuming, especially for funnels. BI tools were never designed for event-oriented time series data.
You pay for product analytics based on event volumes, which is expensive and difficult to predict and budget. You even pay for the data you don’t use, but removing data limits the depth of analysis.
Leverage your data warehouse as the single source of truth. Get deeper insights by correlating product instrumentation data with all your customer and business data.
Query the data warehouse directly, so data is never ingested or duplicated into another analytics application. Always get consistent results for immediately actionable insights.
Support Product & Growth teams with governed, self-service product analytics. Business users can quickly answer most of their own questions through self-guided visual exploration. For the toughest questions, work in SQL from the same platform.
Pay a flat platform fee that is never tied to event volumes. There is no additional data ingestion or storage cost. Leverage the economies of the modern cloud data warehouse.