Trial to activation
Where signups stall before first value, which activation steps are manual, and whether anyone owns the handoff between growth and product.
Segment · B2B SaaS · 20–500 people
AI Operating Consulting for B2B SaaS
You have engineers, a roadmap, and more AI ideas than quarters. What you likely do not have is an independent, priced read of which operating loop is costing you the most — and which AI work is defensible to your board.
What we look at
Six loops decide whether a growth-stage software company scales cleanly: activation, onboarding, support-to-product, renewal, roadmap decision-making, and AI-in-product. We trace each one against a real quarter of your data and working sessions, then score candidate AI work against the friction we priced — not against vendor capability.
The six loops we trace.
Onboarding to first value
How long implementation actually takes versus what sales promised, and how much of it is one person re-typing the same context.
Support to product
Whether recurring support themes reach the roadmap as evidence, or arrive as anecdotes in a prioritization meeting.
Renewal and expansion
Which risk signals exist in the data already, who sees them, and how many days pass before anyone acts on one.
Roadmap decisions
How the quarter gets decided, how much of it is the loudest voice, and what evidence a board-level product narrative currently rests on.
AI in the product
Which AI features are worth building into the product versus into your own operations — and which are demos that will not survive contact with pricing.
Fit
Who this is for — and who it isn't.
Good fit
- 20–500 people, post-product-market-fit, growing but straining
- Multiple teams, several systems, and workflows nobody fully owns
- AI ideas outnumber the quarters available to build them
- Leadership willing to change process, not just buy tooling
Not a fit
- Pre-product-market-fit teams still searching for a first customer
- Buyers who want an implementation vendor to execute a fixed spec
- Organizations that want a tool recommendation without process change
- Anyone looking for a large delivery team rather than a senior operator
Common questions from SaaS leaders
What does an AI operating diagnostic look like for a B2B SaaS company?
It follows the revenue and delivery loops that matter in software: trial-to-activation, onboarding-to-first-value, support-to-product feedback, and renewal risk. The output is a scored map of where those loops leak time or revenue, plus a shortlist of AI opportunities scored against them.
We already have engineers. Why bring in an outside operator?
Engineering capacity is rarely the constraint. The constraint is usually deciding which of fifteen plausible AI ideas is worth your team's quarter, and being able to defend that choice to a board. The diagnostic produces that decision, not the code.
Do you work with our existing PM and data teams?
Yes. The engagement is designed to leave your team more capable, not dependent. Every artifact is handed over in a form your PMs and analysts can keep running after the engagement ends.
Start where it's cheapest.
Score yourself in four minutes, read the playbook, or book a free 20-minute call with Aiden Wayne.