Self-service analytics for everyone

Empower every business user to self-serve for ad hoc exploratory analytics. NetSpring is the single collaborative tool for shared, trustworthy metrics across all teams in the enterprise.

Make your analytics more business impactful

Get instant answers to any ad hoc analytical question using NetSpring’s self-service templates. Tie your analytics to business outcomes, by analyzing across product event streams and business state data in the warehouse.



Answer any question

Instantly answer every ad hoc question easily with a rich library of exploration templates.

  • Quickly see key product metrics and trends over time
  • Breakdown metrics by cohorts and attributes
  • Use visual drag-and-drop interfaces with no SQL or dependence on data teams

Consolidate analytics in a single tool

Avoid inconsistent, fragmented analytics in multiple tools on separate data silos.

  • Use a single tool for product analytics, marketing analytics, operational analytics, and business intelligence
  • Build trust in numbers with analytics in the single tool working off the single source of truth in the data warehouse
  • Reduce TCO of managing multiple tools, data repositories, and data movement jobs

Build analytic applications

Compose use-case and domain specific analytic applications without code.

  • Model your business accurately and easily, using a rich library of modeling templates
  • Author highly configurable and parametrizable reports and dashboards, without dependence on data teams
  • Securely share and collaborate on content with your team

Governed metrics

Build a repository of shared business metrics across the enterprise.

  • Use a point-and-click interface for composing metric definitions of any complexity
  • Organize metrics in folders with robust role-based access control
  • Tag metrics to indicate ownership, status, and usage guidelines

Reduce compute cost

Reduce data warehouse compute costs with query optimizations

  • Leverage an innovative query compiler generating optimized SQL for each data warehouse
  • Optimize cost-to-performance ratios with flexible data sampling
  • Auto-materialize commonly reused query fragments to avoid repeated query processing cost

Model your business accurately

Flexibly model the complexity of your unique business.

  • Represent business entities, their relationships, and semantics in a natural and intuitive form.
  • Reflect the data model of web pages, applications, chat, call center, store, loyalty programs, surveys, subscriptions, payments etc. for deep and accurate analytics
  • Employ flexible identity resolution, profiling, and attribution models natively in the warehouse that any application can consume

Act on analytic insights

Take actions on analytic insights to impact business outcomes

  • Publish results of any analytic exploration to the warehouse to trigger further actions
  • Activate audiences directly from the warehouse for more effective context-rich targeting
  • Receive notifications of anomalies and opportunities – in product or in tools like Slack

Pulse on your business

Keep a pulse on your business with continuous KPI monitoring.

  • Monitor and alert on anomalies in metrics
  • Identify and alert on business opportunities e.g. upsell
  • Collaborate with team members to resolve alerted incidents

Avoid fragmentation of analytics across multiple tools

Learn how companies are providing self-service analytics for all.

Read the Blog


  • Ergatta Logo

    NetSpring is the Holy Grail of product analytics. You don’t have to move your data anywhere.

    It sits directly on your data warehouse, looks across all data sets, and supports both traditional BI analysis and modern event-centric product analytics. It is also self-service, so you can expand the reach and impact to everyone in the organization, not just technical teams.

    And when it comes to cost, NetSpring is cost-efficient and scales with our business.

    Chang Yu, VP of Product
  • Bonfire Logo

    Relative to our peer Web3 companies, NetSpring gives us an important competitive advantage. With NetSpring working directly on our data warehouse, we now have a view into retention and activation others don’t have.

    We can track cohort-specific KPIs, then easily build and test hypotheses that are leading to improvements to our platform, especially around the first user experience. The ability to segment our creators by specific behaviors has helped us identify which segments matter most. This was a level of granularity previously hidden from us.

    Matt Alston, Co-Founder & CEO
  • Zoom Logo

    In subscription businesses, you have to closely follow the customer lifecycle. You may be looking at feature adoption or churn, at how to create more value, or how to make customers aware of new products. And internally, for sales, marketing, or customer support departments – providing insights.

    Basically with this cloud architecture we have an ability to look at product telemetry data as well as business transaction data. The magic is when we intersect these and do cohort analysis. We can slice and dice from many different perspectives, and that’s where the insights come.

    Awinash Sinha, CIO
  • MailChimp Logo

    You would think that if I handed you a product analytics platform, I would be excited PMs are looking at retention rate. But only half of the cancellations happened inside the product. The other half happened because somebody picked up a phone to cancel.

    No events were ever created, and as such, our retention curves were materially misstated. That immediately starts to undermine the credibility of any first-generation tool.

    John Humphrey, Former Head of Data Platform Product
  • Insta Cart Logo

    How can we make the experience of buying groceries on Instacart not just more convenient, but also more efficient and delightful than shopping in the store?

    To inspire product strategy, we spend a lot of time trying to understand patterns of shopping so we can build personalized experiences.

    Anahita Tafvizi, VP and Head of Data Science & Business Operations
  • Asana Logo

    Our product managers and growth managers rely heavily on data to see how customers are using the platform. How frequently are they using? What capabilities are they using? Which capabilities are resonating more or less them them.

    That informs our product roadmap.

    Saket Srivastava, CIO
  • Revifi Logo

    Cloud data warehouses like Snowflake, Redshift, BigQuery, Databricks, and Azure have become the de facto place where businesses pull data out and use it for a business purpose.

    So the more compute you push on the cloud data warehouse, the closer it stays to the ecosystem, and the easier it is for anyone to even consume such a system.

    Sanjay Agrawal, Co-Founder & CEO
  • Neon Logo

    Amplitude and Mixpanel are basically a time series database underneath, with a UI. Time series data tends to be write once.

    You need to take advantage of those techniques data warehouses are born with. It makes sense to put this into a data warehouse, rather than a custom database like Datadog, Mixpanel, or Amplitude. Plus you have additional benefits from it because you can cross reference that data with the rest of the business data.

    Nikita Shamgunov, Founder & CEO
  • Rudderstock Logo

    We want to look at product funnels and customer journeys, but then combine that with Salesforce data. But it was surprisingly hard to do with a lot of these cloud product analytics tools. They’re only designed to ingest a specific kind of data. And if you want to combine other data sources, it becomes really fragile and complicated to set up those data pipelines.

    Warehouse-native enables that and unlocks that set of use cases. Why do you need to ship everything to another vendor to do specific parts of your analytics? It just does not make good sense.

    Soumyadeb Mitra, Founder & CEO
  • Simon Logo

    True centralization aggregates data from all channels, not just what someone clicked on the website: offline, IoT, support, etc.

    Let’s have shipping and returns data, and everything else that is required to properly instrument a real business – put in a single place, which is governed, secure, complete, and accurate.

    Jason Davis, Founder & CEO
  • DCP Logo

    A core focus of DCP Midstream is our commitment to operational excellence.

    Leveraging NetSpring to analyze real-time data gives our team members key information to prioritize critical work, support quick response, and more effectively serve our customers.

    Rob Sadler, Group Vice President of Energy, Transition & Transformation

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