NetSpring Launches Product and Customer Journey Analytics on the Snowflake AI Data Cloud

NetSpring announced at Snowflake’s annual user conference, Snowflake Data Cloud Summit 2024, the launch of Product and Customer Journey Analytics which is Powered by Snowflake. The new application will empower product-led companies with cost-effective and business-impactful analytics, leveraging all product and customer data in their Snowflake AI Data Cloud, to build better products and deliver superior customer experiences.

NetSpring ushers in the next-generation of analytics on Snowflake for product-led tech companies. Optimize your growth metrics with NetSpring’s Product and Customer Journey Analytics.

“Historically, product and customer analytics has been done in specialized systems that have their own siloed data stores, with copies of data disconnected from the central enterprise data warehouse. By building the next generation of such analytics platforms working directly on top of the Snowflake AI Data Cloud without any data silos, NetSpring is delivering enterprises massive gains in better cost, security, privacy, governance, and trustworthy analytics,” said Vijay Ganesan, CEO, NetSpring.

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Building Product and Customer Journey Analytics on Snowflake’s AI Data Cloud has allowed NetSpring to use Snowflake’s centralized storage and compute engine to deliver cost-effective, trustworthy, and business-impactful analytics to enterprises. Unlike traditional first-generation product analytics tools that work off copies of data outside of the enterprise’s central warehouse or data lake, NetSpring works natively on data in Snowflake, without making any copies. This results in lower TCO, as companies do not have to manage expensive and error-prone ETL and Reverse ETL jobs. Furthermore, NetSpring is able to analyze across all product event data and customer business data that is available in Snowflake, to be able to tie analytics to true business value across the entire customer journey. This results in a huge increase in the ROI of analytics initiatives.

“NetSpring is bringing a new class of event-oriented analytics workloads to Snowflake. It is proving that these workloads, that have traditionally been processed in specialized systems, can be served well on top of an enterprise’s single source of data truth – their data platform,” said Prasanna Krishnan, Head of Collaboration and Horizon, Snowflake. “This new generation of analytics products on top of Snowflake, such as NetSpring, enable companies to bring the apps to the data, eliminate data silos and gain a deep understanding of their customer’s end-to-end journeys by leveraging all the rich data they have in Snowflake.”

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With NetSpring’s Product and Customer Journey Analytics, Powered by Snowflake, joint customers will be able to:

• Standardize on the AI Data Cloud to be the central source of truth for all data including product instrumentation events, avoiding the need to send data out of their secure Snowflake to external SaaS services.
• Capture and store all raw event data in Snowflake in a cost-effective way. By leveraging the elastic compute capabilities of Snowflake, customers pay based on consumption, rather than paying by event volume in traditional systems.
• Overcome the limitations of existing first-generation product analytics that only provide simple, templated analytics on siloed copies of data from limited product-only channels. With NetSpring, customers can easily analyze across all their product and customer data in Snowflake that results in more business-impactful analytics. They can tie all customer experiences across all touch points to business outcomes such as revenue.
• Build trust in numbers by using a single tool, NetSpring, on top of the single source of truth, Snowflake. This gives users confidence to make business decisions based on the insights from data.
• Increase time to analytic insights avoiding repeated back-and-forth between business and data teams working on different tools. With NetSpring on Snowflake, business users can self-serve and collaboratively work with data teams to build analytics in the same tool working off the same data.

By building applications on Snowflake, product and engineering teams are able to develop, scale, and operate their applications without operational burden, delivering differentiated products to their customers, as well as provide builders with access to resources to help them design, market, and operate their applications in the AI Data Cloud. To learn more about how organizations are building next gen apps on Snowflake,