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Introducing the Revenue Data Platform

Our evolution from a Product-Led Sales Platform to a Revenue Data Platform to democratize data for the entire go-to-market team.

Alexa Grabell
April 17, 2023
Introducing the Revenue Data Platform

It’s a big day for Pocus. 

Pocus’ vision has always been to accelerate revenue using data. We’ve been fortunate to bring that vision to life with some of the fastest-growing SaaS companies like Miro, Webflow, Loom, Linear, Superhuman, and our community of 2.5K+ members. 

We’ve seen firsthand how the best teams use data to fuel their go-to-market motions, from enabling self-serve to Product-Led Sales to outbound. As we dug deeper, we learned that go-to-market teams were eager for more data and Pocus’ use cases grew beyond helping sales understand where to spend time prospecting - and in turn our product evolved alongside. 

Today we’re excited to announce the launch of Pocus’ Revenue Data Platform, a purpose-built tool for GTM teams to analyze, visualize, and action data about their prospects and customers without needing engineers. It’s the next evolution of our product and the next step in our mission to unlock data for every team. 

Democratizing data for go-to-market teams

The best go-to-market teams are data-driven.

They rely on product usage, company profile, and marketing intent data to optimize the customer experience and journey. Go-to-market (GTM) teams - sales, marketing, customer success, growth, and community - rely on data to inform who they should reach out to, when they should reach out, and with what message. GTM teams need access to data to efficiently prioritize accounts, plan territories, and experiment with new customer segments.

Go-to-market teams increase productivity and accelerate revenue from consuming data. Yet, they are underserved by existing data platforms that have been built for more technical teams. BI Dashboards, Reverse ETL, and CDPs have been game-changing for data and analytics teams; but, they lack critical features for go-to-market workflows. Because of this, companies are forced to hack together DIY solutions that take years to build and maintain… and still don’t quite hit the mark. 

Go-to-market teams don’t just need access to data, they also need a way to visualize and action data… without relying on the data and engineering teams.

Pocus: The Revenue Data Platform

Pocus’ Revenue Data Platform is purpose-built for GTM teams to analyze, visualize, and action data about their prospects and customers without needing engineers. 

The product's core is the Revenue Data Graph (more on that below) - the data engine powers the entire platform. 

Key components of our updated platform include: 

  • Revenue Data Graph: Break down data silos by combining data from various sources into a unified model optimized for go-to-market use cases.
  • 360 Insights: Cut through the noise. Surface top opportunities and go from insight to action quickly. 
  • Playbooks: Build, test, and run go-to-market workflows powered by product usage insights. 
  • Reporting: Reliably hit your goals. Get visibility into what playbooks are performing well and how individual reps perform so you can tune playbooks and coach reps for more repeatability.   
  • Automations: Keep your data in sync across tools and automate workflows based on product usage triggers.
  • Pocus Predicts: Tune your playbooks in real-time with AI-powered recommendations.  

Revenue Data Graph - Pocus

New features to accelerate revenue  

This update includes a ton of new features (below) and huge improvements to existing features that level up the platform. 

Revenue Data Graph

At Pocus, data management is central to our mission of unlocking data for all go-to-market teams. However, in today’s product-led world, this has become more challenging.

Data about prospects, users, and customers lives in a data warehouse (Snowflake) and may never reach the CRM (Salesforce), creating two sources of truth for go-to-market teams. This creates data silos and an incomplete picture of customers and prospects for go-to-market teams. 

To add to the complexity, product-led businesses organize their workflows around data models that are specific to their business and product. Product-led companies care about users, workspaces, domains, teams, and accounts, a data hierarchy CRMs can’t handle. This means data engineers must fit complex data types into rigid lead and account models, making it impossible for go-to-market teams to generate meaningful insights.

To solve this, we created the Revenue Data Graph as the underlying engine of the Pocus Platform. 

Pocus’ Revenue Data Graph combines data from different sources, defines associations between custom objects, and performs calculations with ease.

Pocus - Revenue Data Graph

For the data nerds reading, you’ll love the control and governance we give you to make sure GTM teams don’t create data silos. 

“We have more control over data and better data governance consumed by the go-to-market team. All with less work from our team, freeing up our time to work on other mission-critical tasks.” - Aaron Bannin, Analytics Engineer, Miro

For sales teams, this means you can see rich insights at the user, workspace, domain, and account levels instead of the simple aggregated insights you would typically see in Salesforce. 

Learn more about the Revenue Data Graph here.

Pocus Predicts 

AI is often overhyped as a solution for everything. At Pocus, we believe AI is useful for tasks like analyzing data for patterns and finding signals that indicate conversion. However, you still need qualitative feedback from your sales team to determine which signals are truly predictive. It's important to balance art and science to build trust in AI systems.

For example, relying too heavily on AI can cause issues. If a rep is presented with an "excellent" lead without any context, and that lead doesn't convert, trust is lost. Instead, presenting the signals that informed the score can help the rep identify misleading information and provide feedback to the team.

Relying solely on black box models without access to usage data can also lead to distrust in the output. We kept this in mind when building Pocus Predicts.

Pocus scoring flexible data model AI recommendations

Based on product usage and customer fit signals, Pocus Predicts recommends the best playbooks for the go-to-market team to run. The AI algorithm analyzes your historical data to identify signals that are most predictive of conversion. This feature allows you to confidently pick the right playbooks to run and iterate over time based on a continuous feedback loop.

Pocus Revenue Data - AI recommendations

Go-to-market teams use Predicts to spend their time on the best playbooks and use data to iterate on them over time. 

Pocus Predicts helps answer questions like: 

  • What playbooks should your team run to more effectively convert users from free to paid, upsell existing paid accounts, or prevent churn? 
  • How do you know which signals are predictive of your desired conversion goals? 
  • What thresholds should be set for key signals like ‘number of invites sent’?

Reporting 

Last but not least, we're launching Reporting, a feature for leaders to assess playbook health and team performance. Reporting tracks how playbooks perform against conversion goals (i.e. free to paid conversion) and how reps execute those playbooks. This visibility allows leaders to identify which reps are following playbooks and driving consistency and reliability.

Reporting - Pocus Revenue Data Platform

Experimentation is critical with changing macroeconomics and buying dynamics. Reporting gives leadership visibility into high-converting playbooks to double down on, missing playbooks to develop, and low performers to sunset.

The journey to the Revenue Data Platform

In the early days of Pocus, describing what we built was hard. At the time, every investor wanted to call us a PLG CRM (and some still do), but we eventually landed on the Product-Led Sales (PLS) Platform.

We chose the name to reflect the primary use case for customers: to run their Product-Led Sales motion. Customers used Pocus to equip sales teams with product usage insights to prioritize leads and close business from the existing pipeline of users.

Over the last year, as our customers continued to find new use cases for Pocus and our product evolved, the name became less tied to who we are but rather what we enable.

Product-Led Sales is still a use case we enable in addition to a broader set of use cases unrelated to PLS. Our customers have told us this explicitly - Pocus runs their go-to-market, not just their Product-Led Sales motion. 

Pocus - Miro - ROI

🪄See it in Action

Ready to use data to accelerate revenue? Schedule a demo to see it in action. 

Alexa Grabell
Co-Founder & CEO at Pocus
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