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Building and Operating a GTM Motion for PLG Companies Product-Led Growth

Building and Operating a GTM Motion for PLG Companies Product-Led Growth

A Guide for Revenue Operations Leaders

Jeff Ignacio's avatar
Jeff Ignacio
Apr 25, 2025
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RevOps Impact Newsletter
RevOps Impact Newsletter
Building and Operating a GTM Motion for PLG Companies Product-Led Growth
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Product Led Growth (PLG) isn’t a buzzword anymore. It’s a core go-to-market (GTM) strategy, especially for SaaS companies looking to scale efficiently. But operating a PLG motion requires more than just offering a free trial and watching self-serve users convert. It demands a deeply integrated tech stack, cross-functional collaboration, and a RevOps function that can connect usage data to business outcomes.

This article outlines what revenue operations leaders must know to design, build, and operate a modern GTM system for PLG businesses.

The Core Metrics That Power PLG

Revenue Operations leaders must rethink traditional funnel metrics to accommodate the PLG model. Here's what to track:

  • Signups: The new top-of-funnel, replacing MQLs.

  • Time to Value (TTV): How fast a user reaches their "aha" moment.

  • Activation Rate: Percentage of signups that achieve meaningful in-product action.

  • Free-to-Paid Conversion: Core monetization metric.

  • Net Revenue Retention (NRR): Ultimate health indicator for expansion and churn.

These metrics are often reviewed at different cadences:

  • Daily/Weekly: Signups, TTV, Activation.

  • Monthly: Conversion, Product Usage Trends.

  • Quarterly: NRR, Expansion Revenue, CAC:LTV, Strategic Benchmarks.



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Another view of core metrics:

The Technology Stack That Enables It

To build a PLG motion, you need to collect behavioral data at scale, enrich it, and activate it across systems. Here is the typical stack broken down:

1. Product Analytics

Tools: Mixpanel, Amplitude, PostHog, Heap, Pendo

Outcome: Tracks feature usage, funnels, and retention cohorts.

2. Data Infrastructure

Tools: Snowflake, BigQuery, dbt, Fivetran, Databricks, Polytomic, Azure, Redshift

Outcome: A single source of truth for modeling product-qualified signals.

3. Customer Data Platform (CDP)

Tools: Segment, Hightouch, Census

Outcome: Identity resolution and syncing usage data to GTM systems.

4. In-App and Lifecycle Engagement

Tools: Pendo, Appcues, Customer.io

Outcome: Personalized onboarding, upsell nudges, and re-engagement campaigns.

5. CRM & Sales Tools

Tools: Salesforce, HubSpot

Outcome: Sales-assist motion powered by usage insights.

RACI: Who Owns What?

Standing up this stack requires collaboration. Here’s a quick RACI breakdown:

  • Product & Engineering: Own instrumentation and product analytics.

  • Data Team: Owns warehouse, modeling, and enrichment.

  • RevOps: Owns metric definitions, dashboarding, CRM integration.

  • Marketing/Growth: Own lifecycle and in-app orchestration.

  • Sales/CS: Act on product signals for upsell and retention.

Standing up a PLG system requires coordinated execution across multiple phases, with each team owning a specific piece of the workflow:

  • Instrumentation is typically led by Product and Engineering teams, who are responsible for defining and implementing the event schema, tracking key actions like “Signed Up” or “Used Feature X” to capture user behavior accurately.

  • Data Modeling & ETL falls to Data Engineering and Analytics. They ensure raw product data is moved into a centralized warehouse, cleaned, and structured so it can be queried and trusted.

  • Metric Definition & Dashboards are owned by RevOps and Product Analytics. This team translates usage data into actionable KPIs and builds dashboards in tools like Looker or Tableau to support decision-making across GTM teams.

  • Growth & Engagement is handled by the Growth and Lifecycle Marketing teams. They use the product data to personalize in-app experiences, trigger lifecycle emails, and run experiments to increase conversion and retention.

  • Sales & Success leverage product signals such as usage spikes or feature drop-offs to prioritize outreach. Sales, Customer Success, and RevOps collaborate to drive upsell, prevent churn, and support product-qualified leads.

Each phase builds on the last, creating a data-driven feedback loop that powers a scalable and efficient GTM engine.

Operating Cadence for PLG Success

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