About GrowthCues: A More Personal Approach to Product Growth

The Challenge

If you're a GTM Engineer or a technical RevOps leader at a B2B SaaS company, you've probably felt this tension:

• The promise of the modern data stack: You've invested in a powerful data warehouse and Reverse ETL tools, believing they would unlock a world of automated GTM plays.
• The reality of your daily work: You're drowning in a sea of brittle, one-off SQL scripts. You've become a bottleneck for the entire revenue team, servicing an endless queue of tickets for "one more data pull" or "a small tweak to the PQL query."
• The infrastructure cost: Calculating stateful customer journeys and rolling 30-day usage trends natively in SQL requires massive window functions that actively burn through your Snowflake or BigQuery compute credits.
• The result: You were hired to be an engineer, but you spend your days maintaining expensive queries instead of building the scalable growth systems you know are possible.

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Why I Created GrowthCues

I was convinced there had to be a more resilient, scalable way to build product-led GTM intelligence without treating the data warehouse like a supercomputer for behavioral math.

That's why I built GrowthCues: a managed PLG Engine that frees GTM engineers from the tyranny of brittle SQL, offloads the heaviest compute from your warehouse, and turns raw events into activation-ready signals.

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What GrowthCues Helps You Do

• Stop Maintaining SQL and Start Modeling Journeys
  • Move beyond basic event counting. Model your entire customer lifecycle using No-Code Milestones and stateful, Multi-Step Customer Journeys. The GrowthCues PLG Engine handles the complex time-series math externally so you don't have to.
• Translate Complex Events into Clear GTM Signals
  • Deploy a Ready-to-Use B2B Metric Library: Stop manual modeling for standard KPIs. Get instant, warehouse-ready tables for DAU/MAU, Account Stickiness, and Session durations—all enriched with rolling trends and MoM aggregates.
  • We don't use "black-box" AI predictions. GrowthCues uses deterministic math to calculate actionable signals—like account momentum (7 vs. 30-day trends) and usage quartiles—so your GTM teams actually trust the data they see in their CRM.
• Empower AI Agents and Data Science Teams
  • Select exactly which signals write back to your warehouse to keep schemas clean. Every run automatically generates an AI-Ready Context file (schema.yml) for your LLM agents. For the Business tier, we export ML-Ready Parquet files directly to S3/GCS to feed your internal scoring models without the extraction headache.

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My Approach

I love product-led growth, and I'm obsessed with providing B2B SaaS teams with the tools they actually need to succeed. GrowthCues is not a faceless, VC-backed corporation pushing bloated software; it's a personal mission by a solo founder to build the exact infrastructure I wanted to use.

I believe in transparent math, protecting your warehouse compute costs, and keeping data governance pristine. I'm here to partner with you to make this engine indispensable to your workflow.

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How GrowthCues Works

• Secure 60-Day Footprint: It connects securely to your data warehouse and maintains a rolling 60-day buffer of your events using lightweight, incremental reads. This gives you exact current vs. previous-month baselines without hoarding years of historical data or spiking your daily warehouse egress.
• The Managed PLG Engine: It processes your complex GTM logic, No-Code Milestones, and Journeys outside your warehouse, saving you hundreds of dollars in warehouse compute credits.
• Enrich & Activate: It upserts clean, selectable columns and AI-ready context (schema.yml) directly back into your warehouse, ready for your GTM stack, Reverse ETL tools, and AI-agents to consume.