Why you need the Humanic PLG CRM to accelerate your PLG motion, even if you have Reverse ETL

Reverse ETL tools like Census and Hightouch have had a remarkable impact on SaaS GTM teams by revolutionizing the way they utilize data warehouses like Snowflake, BigQuery, and Redshift. These tools enable easy access to data stored in the data warehouse and activate it in downstream tools. Adopting a Reverse ETL solution is highly recommended as it empowers companies to make all their data accessible throughout the organization.

However, Reverse ETL is just one layer of the PLG GTM tech stack. While it facilitates data integration with best-in-class tools, it does not address the daily insights and workflows required by PLG companies to optimize their go-to-market teams. These include lead prioritization based on ICP fit and product usage, routing leads to the appropriate playbooks, and providing sales reps with contextual information about the best leads.

PLG companies today face the challenge of driving revenue growth when the product itself serves as a primary acquisition channel. This requires a shift in mindset for growth and marketing teams, as PLG data is often first-party generated and collected by the company itself. The data resides in different systems like CDPs and billing platforms, which are not directly accessible to the go-to-market teams unless explicitly sent to CRMs. Reverse ETL bridges this gap by piping data from the cloud data warehouse to the downstream tools used by sales and go-to-market teams.

Reverse ETL is crucial because without the comprehensive data it provides, go-to-market teams would rely on outdated strategies that worked well in traditional sales processes. The shift to a product-led sales approach, coupled with the rise of cloud data warehouses, necessitates a tool like Reverse ETL to leverage critical customer data stored in databases accessible to various downstream tools.

Reverse ETL offers several benefits in a product-led sales motion. Firstly, it helps in mapping customer data cohesively by building reusable models that resolve different identifiers from various sources. Secondly, it facilitates seamless data transfer from one tool to another, such as sending user sign-in data from Reverse ETL to Salesforce for enhanced customer context. Finally, Reverse ETL tools provide no-code builders for audience segmentation, allowing growth and marketing teams to perform analytics and experiments independently.

While Reverse ETL is valuable, it does not fulfill the specific requirements of go-to-market teams on a daily basis. This is where a PLG CRM like Humanic comes into play. Humanic complements Reverse ETL by combining data from multiple systems and creating a comprehensive view of customers, their behaviors, and propensities to buy. It enables prioritization and identification of leads through machine learning models and sends notifications to sales and customer success teams.

Using a CRM alone is insufficient for sales or customer success teams as they lack insights and analytics related to product usage and other important data. While some companies sync product data to CRMs, they are unable to extract the necessary customer insights from static fields or properties.

In practice, Humanic customers combine Humanic with Reverse ETL to power their product-led growth sales motion. They create models for customer data and leverage Humanic's machine learning capabilities to identify best-fit customers and prioritize leads. For product data, they create views of product event data to run last-mile calculations and perform no-code segmentation in Humanic.

In summary, Reverse ETL is a powerful tool that complements product-led sales strategies, but it is not designed to address the specific needs of go-to-market teams. By combining Reverse ETL with a product-led sales platform like Humanic, companies can scale revenue efficiently in the product-led growth paradigm.

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