Introducing Houseware Metrics

Today, we are excited to announce Houseware’s foray into simplifying revenue experience at scale for our customers and community. We are launching Metrics by Houseware, intending to standardize revenue metric definitions as dbt code for the most common tools used by SaaS companies.

Over the past few quarters, we have been working with our customers in beta, and these metrics have been battle tested for multiple scenarios across industry context., In addition, these customers have used these metrics to define a semantic layer that separates data consumption systems from the revenue logic benefitting from the definition of a standard metric, removing redundancies and scaling processes. These metrics are built on top of the dbt metrics spec.

To fix this, we’re working on deep dbt Semantic Layer integrations with design partners focused on BI, Data Science, data loading, and other types of warehouse-connected data applications. In short, the dbt Semantic Layer is acting as the glue that binds these best-of-breed data tools together into a more unified, less fragmented stack. It’s a vision of the future that we’re tremendously excited about, but it will take time to realize it in its entirety. - Drew Banin, Co-founder, dbt Labs in Write once, query anywhere with the dbt Semantic Layer

Much has been written about metrics, with organizations like Airbnb, Microsoft, and Linkedin utilizing the power of metrics to scale their business. With Houseware metrics, our vision is to bring the power of metrics that leading data organizations enjoy with the ease of a few commands. The metrics are available as easy-to-use dbt packages that solve for the availability and calculation of the most common metrics used by your revenue teams.

Check out this getting started guide by Aryan Madhav Verma, who leads revenue experiences with our customers using Houseware Metrics.

We at Houseware believe in the power of a modern revenue function that has built the most successful SaaS companies in the last decade. The revenue function is highly efficient, yet the data for customers is spread across the favorite flavors of the SaaS tools used by each sub-function that comes under the revenue org. Sadly, “Divyansh Saini” is a different user in Stripe and a much different user in Salesforce.

This problem hasn’t been solved in the last decade of technological evolution. Instead, organizations have gone through several iterations and new names to solve the same challenge across industries. From Customer360 to setting up a CDP and, most recently, a modern data stack that empowers warehouse-native r-ETL. But why is this such a complex problem to solve?

Over countless conversations, we have seen the modern revenue function comprising six broad sub-functions:

• Sales
• Marketing
• Product
• Support
• Success
• Finance
  

With Houseware metrics, our goal is to automate revenue operations and get teams to boot their warehouse quickly to deliver an enhanced warehouse-native revenue experience. These metrics are open source, and we anticipate you, the reader, the guardian of the revenue experience in your organization to help us create a movement towards a new brighter future.

We’ve built the metrics to be easily used if you are using the two most common tools in the modern data ecosystem: Fivetran and dbt. Both teams have greatly inspired us in executing a hub culture empowering the community to re-use model logic for various tools. Soon enough, we plan also to enlist Houseware metrics on dbt hub.

The first version of Metrics by Houseware includes six tools that you start using today: Segment, Facebook Ads, Google Ads, Stripe, Intercom, Hubspot.

With Houseware metrics, Houseware users can enjoy a consistent definition of critical metrics and KPIs, use the Houseware ready-to-use templates, and get to a top-line impacting value much faster. For example, one of our customers could see the value of these metrics with a 5-minute PLG funnel loop that would have taken three weeks of effort from the data team and the implementation cycle of 1 month with the PLG CRM point solutions in the ecosystem.

The most exciting element of how Houseware sees the problem for our customers lies in our customer-built approach to defining their data apps on top of these metrics. We believe every organization is different in its execution and strategic style yet united by similar industry-standard metrics. With Houseware, they are not just limited to one use-case of using product usage data for sales but a flexible approach to empower their revenue experience.

A modern revenue organization’s foundation lies in a data-first approach. Houseware is here as the world’s first warehouse-native revenue experience solution to help accelerate your journey to a stronger revenue foundation.