Guide

A GTM motion is how buyers buy: self-serve inside the product, a remote sales team, a field team, or someone else's channel. Many companies mix motions by segment (PLG for SMB, sales for enterprise). That is a portfolio, not confusion, if the metrics stay separate.

The four families

Self-serve / product-led growth (PLG). Users discover, try and pay inside the product. Sales is optional or "sales-assist" on high-intent accounts. CAC is mostly marketing + product time. Works when time-to-value is minutes, not months, and ACV can start low. See PLG vs sales-led.

Inside sales. Reps sell remotely (phone, video, email) into mid-market. Demos, trials and short POCs are common. Cycle lengths measured in weeks. Pair with inbound or light outbound.

Field / enterprise sales. Named accounts, onsite discovery, security reviews, RFPs, multi-threaded stakeholders. Cycles measured in months; ACV usually six figures+. Requires solutions engineers, legal, and a real founder-led phase before you clone the motion.

Partner / channel. ISVs, agencies, cloud marketplaces (AWS/Azure/GCP), OEMs or referral partners originate or close deals for a cut. Slow to build; powerful once a partner's distribution dwarfs yours.

Developer tools and AI

Developer tools often start PLG: docs, GitHub, OSS, sandboxes, time-to-Hello-World. Buyers are users first; economic buyers appear at seat thresholds or SSO. Community and open source are distribution, not just branding. Avoid enterprise packaging that breaks the self-serve loop before you have pull.

AI products add wrinkles:

  • COGS and usage pricing change packaging — seats alone may under-monetize heavy users. See API economics.
  • Evaluation burden is high — buyers want proof on their data. Paid pilots beat endless free POCs.
  • Trust and compliance (data retention, training opt-out, SOC2) gate enterprise earlier than for a pure UI tool.
  • Model commoditization means GTM must sell workflow, data advantage or distribution — not "we wrapped a model."

Trade-off

Demo-led AI sales win skeptical buyers but do not scale like PLG. PLG AI scales if the aha moment is immediate and cost controls exist. Many AI startups run PLG for individuals + sales for teams — instrument both funnels separately so blended CAC does not lie.

Common mistakes

  • Blending PLG and enterprise CAC into one number.
  • Enterprise packaging that kills self-serve before pull exists.
  • Selling "we wrapped a model" as the motion.

Check yourself

  1. Time-to-value is minutes and ACV starts under $5k. Which motion fits? Pure self-serve / PLG.
  2. Why split PLG and enterprise funnels on an AI product? Blended CAC hides which motion works. The eval and compliance path is a different machine.

Key takeaways

  • Four families: PLG, inside, field, partner. They map to ACV and complexity.
  • A motion portfolio is fine if metrics stay separate.
  • Dev tools lean PLG and community. AI adds eval, COGS and trust.
  • Do not break the self-serve loop with enterprise-only packaging too early.

Further learning

How ACV picks the motion: matching motion to ACV.