Skill Details
Runtime
(gpt-6.1-sol)
Example user message
[userMessage]: Create a synthetic one-year cohort view: 100 acquired customers, GBP 20,000 net revenue, 50% gross margin, GBP 1,000 servicing cost outside gross margin and GBP 4,000 acquisition spend. No repeat-period evidence. Propose a retention experiment without invented future revenue.
Example agent response
# Observed Cohort Value and Retention Experiment
## Cohort basis
The unit is one acquired customer over the supplied year. There are 100 acquired customers; no active-customer count or later-year retention history is supplied. This supports observed contribution value rather than an unlimited lifetime estimate.
## Contribution and acquisition bridge
Revenue per acquired customer is GBP 20,000/100 = GBP 200. Gross contribution is GBP 10,000. Subtracting GBP 1,000 servicing leaves GBP 9,000, or GBP 90 per customer before acquisition. CAC is GBP 4,000/100 = GBP 40. Observed contribution/CAC is 2.25; after acquisition the cohort contribution is GBP 5,000.
## Interpretation
Do not label GBP 200 as profit LTV. GBP 90 is the observed one-year contribution measure. Acquisition payback timing cannot be calculated because purchase dates and cash timing are absent. Future retention remains unknown.
## Experiment and handoff
Proposed design: randomly allocate consenting eligible customers to a useful reminder or holdout. Retention lead should record repeat-purchase rate and incremental contribution over a pre-agreed window, including reminder costs and opt-outs. Stop messages to anyone withdrawing consent. Confirm sample size before treating a difference as reliable.
## Scope and verification
Provide planning estimates, not a valuation or investment recommendation. Historical cohort averages do not establish an individual's future behaviour. This is a worked synthetic example using the user-supplied material. Source authenticity, implementation and real-world outcomes have not been verified; proposed follow-up actions are not completed checks.
$6.99-25%
$5.24
SPECIAL PROMOTION — Offer ends 11 November
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GPT-6.1-SOL
Helps retention and acquisition teams estimate cohort contribution lifetime value, compare acquisition costs and design evidence-bounded segment experiments from supplied purchase and retention data.
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Added 20 hours ago
