GTM Launch Readiness Assessor
Scores a launch across 6 readiness dimensions — positioning, messaging, channels, metrics, alignment, risk — from what you actually know today, not a generic checklist.
About this case study
Problem: launch checklists ask whether boxes are checked, not whether the launch will actually land — clear positioning, a differentiator that holds up, channels that match the audience, a metric that defines success. Most teams find out which of those was missing after the launch, not before. Approach: a single structured prompt to the AI, run against exactly what's typed into a short form — no company research, no scraping, no assumptions filled in behind the scenes. It scores 6 dimensions (positioning clarity, messaging & differentiation, channel readiness, success metrics defined, cross-functional alignment, risk factors), and where the input doesn't give enough to judge something, it says so instead of guessing. Result: this demo runs the same live assessment against whatever you type in — a real launch, a hypothetical one, or the curated example on the page — and returns a prioritized list of what actually needs attention before it ships.
Methodology Note
This runs on exactly what you type below — no company research, no assumptions filled in. Where the input doesn't give enough to judge a dimension, the assessment says so instead of guessing.
Example
Self-serve onboarding flow for our B2B SaaS product
The audience is clearly defined (mid-market ops teams in a stalled free trial) and the intent — driving activation — is implicit but understandable from that framing.
Recommendation: Make the 'why it matters' explicit in launch copy (e.g., tie faster onboarding to a specific pain point stalled users hit).
The '<10 minutes, no sales call, fastest in category' claim is specific and quantified, but no proof point (data source, benchmark, or comparison method) is given to back the 'fastest in category' assertion.
Recommendation: Add a supporting proof point — e.g., internal timing data, a customer quote, or a named comparison basis for the category claim.
Email and in-app plausibly reach existing trial users who've stalled, but Partnerships is typically a channel for reaching new audiences, not re-engaging users already inside a trial — the fit isn't clear from what's given.
Recommendation: Clarify what role Partnerships plays for this specific stalled-trial segment, or drop it if it's meant for new-user acquisition instead.
No concrete metric (e.g., activation rate, time-to-activate, trial-to-paid conversion) was named in the input.
Recommendation: Define a specific target metric, such as % lift in activation rate among stalled trial users within X days of launch.
This can't be confirmed from the form, but the inclusion of Partnerships alongside Email and In-app suggests coordination beyond core marketing (e.g., partner-facing teams) is likely needed — this is inferred, not confirmed by the input.
Recommendation: Confirm with whoever owns the Partnerships relationship that they're looped in and aligned on timing and message before launch.
The most plausible risk is the combination of an unproven superlative claim ('fastest in category') with a 3-week timeline that leaves little room to gather proof or validate the Partnerships channel fit before shipping.
Recommendation: Prioritize either softening the unproven claim or fast-tracking proof-point validation given the compressed timeline.
Priority next steps
- Secure a concrete proof point for the 'fastest in category' claim before launch, or soften the claim to something defensible without external validation.
- Define and confirm a specific success metric (e.g., activation rate lift) so the launch's impact can be measured.
- Clarify the purpose and readiness of the Partnerships channel for this stalled-trial audience, including who on that side is aligned.
Live access is available on request — I personally review each one.