GTM Engineering

Built on the karpathy/autoresearch loop pattern, this playbook applies autonomous feedback loops to GTM assets — emails, ads, landing pages, nurture flows — tested against revenue-linked metrics. Replace manual A/B testing with agent-driven loops that compound ICP-specific learnings across channels.

Build a unified revenue intelligence system that merges billing, CRM, product analytics, and enrichment data into a single account-level view — with AI-powered ICP scoring, churn prediction, and expansion signals. Replace fragmented dashboards with one system that tells you which accounts to save, grow, and acquire.

Most lead scoring is theatre. Sales ignores the scores because they do not trust them. This playbook builds a system that separates fit (who they are) from intent (what they are doing), validates against LTV, and routes leads with context. Top scoring leads convert at 5-6x the rate of bottom scoring leads.

Build scalable, search-led content hubs from structured data to capture long-tail demand without sacrificing technical SEO quality. Well-executed B2B SaaS programmatic hubs can drive 100-300% organic growth over months 7-12 when each page serves real intent with unique data.

Centralize and clean lead, product usage, and enrichment data into a single source of truth (Data Warehouse) to power precise targeting.

Turn incomplete lead records into complete prospect profiles automatically at lead creation. This playbook covers six enrichment patterns across hygiene, triggers, outbound waterfall, live enrichment, intent layering, and reverse ETL.

Automate competitor monitoring and battle-card updates so reps always get current, actionable intelligence in their workflow before competitive calls.

Use your first-party data (CRM, product, lifecycle, website) to train Google Search on pipeline and revenue outcomes, not form fills. Start with simple signal uploads, then progress to programmatic, server-side signal loops as volume grows.

Merge GA4, CRM, and Ads data into one integrated Looker/Data Studio dashboard without requiring a full data warehouse implementation.

Deploy AI agents to crawl websites and extract specific data fields that are not available via standard enrichment APIs.

Shift from keyword-only SEO to entity-driven optimization so AI systems can identify, trust, and cite your brand across ChatGPT, Perplexity, Gemini, and AI Overviews.

Automate sitemap updates and use the Search Console API to monitor indexing rates for new and updated pages.

Convert anonymous, high-intent pricing page visitors into qualified leads and route them to sales for immediate follow-up.

Build ICP fit scoring from realized customer value (LTV/NRR), not assumptions, so GTM teams prioritize accounts that actually become high-value customers.

Sequence enrichment providers by segment and field economics to improve match rates while cutting wasted credits and redundant lookups.

Use job postings as explicit buying-intent triggers, map roles to use cases, and launch personalized outreach while urgency and budget signals are fresh.

Build a signal-led ABM program that selects named accounts from verified purchasing behavior — import records, hiring patterns, permit filings, tech stack changes — instead of firmographic guesswork. Coordinate personalized, multi-channel outreach across the buying committee over 90 days with account-level measurement that tracks meetings and pipeline, not impressions. Replace $50K-$350K/year ABM platforms with a $3K/month stack that delivers 15-25% account-to-meeting conversion and 40-60% higher win rates.