Snowplow Launches AI Agent Event Collection and Analytics on the Snowflake AI Data Cloud

Snowplow announced at Snowflake’s annual user conference, Snowflake Data Cloud Summit 2024, the launch of AI Agent Event Collection and Analytics, which is Powered by Snowflake. The new application will enable brands to better understand the impact of Generative AI investments, such as large language model (LLM) customer agents, on the user journey and digital experience.

“GenAI offers exciting possibilities for optimizing the customer lifecycle via customer agents, but organizations are rushing to deploy a GenAI playbook without a clear roadmap for success. We’re thrilled to partner with Snowflake to create a radically new way for AI teams and product leaders to think about product analytics, moving from understanding the user journey through clicks to understanding the flow of the conversation between the user and the LLM,” said Alex Dean, CEO and Co-founder at Snowplow.

Building AI Agent Event Collection and Analytics on Snowflake’s AI Data Cloud has allowed Snowplow to use Snowflake Cortex AI to implement uplift modeling with LLM events and measure the incremental benefit of your LLM agents on customer conversion. This data allows e-commerce, media, financial services, and other industries investing in GenAI programs to effectively calculate ROI and identify optimizations.

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“As we enter a world powered by AI, it’s imperative that brands have a good grasp on how innovations such as AI agents are impacting customer behavior,” said Erin Foxworthy, Industry Principal at Snowflake. “It’s great to see partners such as Snowplow continue to invest in the AI Data Cloud to address these challenges faced by brands. We’re excited to see how their AI Agent Event Analytics helps customers see the potential of Cortex AI in making better-informed business decisions.”

With AI Agent Event Collection and Analytics, Powered by Snowflake, joint customers will be able to collect usage analytics for the AI agent and calculate sentiment analysis for the conversation. By measuring the effectiveness of the LLM experience and correlation between the AI agent’s intent and subsequent user behavior, customers can gain insights on how to improve the agent or determine when human intervention is required.

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.

SOURCE: Businesswire