GTM motion diagnostic
AI GTM workflow map
Decide which GTM jobs should be automated, assisted by AI, or kept human before you scale outbound across channels.
Motion readiness
39/100
Keep the founder close to signal
The system needs sharper ICP, proof, message, or reply signal before automation should carry the motion.
Inputs
Set where the motion actually stands.
List building and enrichment
Rules and data quality matter more than founder taste once the ICP is sharp.
ICP scoring
AI can rank accounts, but founders still need to define what good-fit means.
First-draft messaging
Useful for variants, dangerous if the core claim has not earned replies.
Multichannel sending
Scale only after the motion has enough evidence to avoid reputational waste.
Reply triage
AI can cluster replies, but ambiguous buying context needs human judgment.
Experiment review
The system can summarize signal. The scale decision still needs context.
First fix the target
If ICP is broad, automation should stay away from high-volume sending. Use AI to find sharper segments and account patterns.
Then test the message
Draft variants are cheap. Founder attention should go to the claim, proof, objection, and reply pattern.
Scale after signal
Multichannel sending is useful when the learning loop is instrumented. Otherwise it just makes uncertainty louder.
Want the real map for your startup?
Send your ICP, offer, current outbound message, and channels. We will map what should be automated, assisted, or kept human before you scale the GTM motion.