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WAREHOUSE-NATIVE PRODUCT ANALYTICS

Build your best product

Get fast answers to any growth question without SQL or dependence on data teams. NetSpring helps you analyze all product and customer data, to build the most delightful and profitable products.

Product insights you can trust and act on

Instantly access product analytics reports. Visualize user journeys by any segment or attribute. Deep-dive to understand drivers for adoption and engagement. NetSpring works off your single source of truth in the warehouse to provide trustworthy insights that you can act on with confidence.

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Instant insights

Quantify and visualize user behavior easily, with a rich library of UI-driven product analytics reporting templates.

  • Quickly see key product metrics and trends over time
  • Breakdown metrics by cohorts and attributes
  • Easily test hypothesis around conversion, engagement, and churn

Answer the next question

Dive deeper from templated reports to self-service ad hoc visual exploration, to answer the next question in minutes.

  • Identify drivers of user behavioral patterns
  • Compare metrics for cohorts across any dimension from the warehouse
  • Get the answer to your follow-up question without SQL or dependence on data teams

Tie product features to revenue and support

Understand the true business impact of product features

  • Link usage or behavioral patterns with subscription tier, revenue, LTV
  • Understand the impact of new features on Support
  • Self-serve without waiting for custom reports from 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 and business intelligence
  • Build trust in numbers with analytics in the single tool working off the single source of truth – the data warehouse
  • Reduce TCO of managing multiple tools, data repositories, and data movement jobs

Trust in numbers

Have confidence in metrics to make business decisions based on them

  • Standardized and governed metrics for all product and customer teams
  • No fragmentation of analytics across product analytics and BI tools
  • Verifiable, trustworthy analytics (off the single source of data truth in the warehouse), that can be presented to the C-Suite

Model your business accurately

Flexibly model the complexity of your unique business.

  • Bring your own data model – natively and intuitively reflect your existing data model of business entities such as Account, Project, Workspace, Ticket, Chat, Document etc.
  • Go beyond canned metrics to compose custom metrics of arbitrary complexity
  • Study behaviors of any actor (not just User), and their events

Leverage the power of your data warehouse

Take advantage of all the rich data available in your secure, trustworthy, single source of truth – your data warehouse.

  • Natively reflect the existing data model of any relational schema in the warehouse, for deep and accurate analytics
  • Data mutability – changes to underlying records in the warehouse are automatically reflected for accurate analytics
  • Activate audiences directly from the warehouse for more effective context-rich targeting

Keep a pulse on your business

Track your business with continuous KPI monitoring.

  • Monitor and alert on customer experience degradations
  • Identify and alert on opportunities for upsell or cross-sell
  • Collaborate with team members to root cause and fix issues

Unlock more business value from your product and customer data

Learn why companies are upgrading their analytics platforms.

Read the Blog

Testimonials

  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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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