Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+22 moreClaude CodeCursorCodex CLIMuseDots
OpenClaw
Manus
Grok
Grok Bot+18 agentsCustomer Value Intelligence — Understand What Buyers Are
Analyze customer and cohort economics using revenue, margins, refunds, servicing costs, retention and acquisition evidence.
$9.99
Customer Value Intelligence — Understand What Buyers Are
Example session with this skill installed
Illustrative scenario: For a supplied one-year cohort of 10 customers, net revenue after refunds is $2,000; COGS $800; variable fulfillment/service costs $300; acquisition cost $500. No future purchases or retention data exist. Calculate observed customer economics, define cost scope and explain what cannot be called lifetime value.
- Read your context and instructions
- Compiled the customer value intelligence
Customer economics brief — illustrative one-year cohort
Scope: 10 supplied cohort customers over one year; net revenue already reflects refunds. Assumes all costs belong to this cohort and period, with no overlap. Identity, tax treatment and attribution need verification.
Observed net revenue: $2,000 total, $200 per customer. Gross profit: $2,000 − $800 = $1,200, or $120 per customer. Contribution before acquisition: $1,200 − $300 = $900, or $90 per customer. Contribution after stated acquisition cost: $900 − $500 = $400, or $40 per customer.
CAC under this supplied scope: $500/10 = $50 per acquired customer. Ratio of observed one-year pre-acquisition contribution to CAC: $90/$50 = 1.8. This is not a forecast LTV:CAC ratio. Fixed overhead and any omitted variable costs are not included.
Payback: cannot determine timing from annual totals. Require dated acquisition and contribution flows; a positive annual total does not establish the month when CAC was recovered.
Lifetime value: unavailable. No retention, repeat-purchase trajectory, future margin, discount rate or forecast horizon supplied. Historical one-year value must not be relabeled lifetime value.
Next evidence: reconcile orders/refunds and costs, verify cohort identity and acquisition attribution, compare cohorts on equal observation windows, obtain retention and dated contribution series, then model scenarios with sensitivity and explicit uncertainty if appropriate.
Execution notes: no private data accessed or forecast generated. No causal channel effect or guaranteed future profit claimed.
Connects securely to your tools. The creator never sees your data.
About this skill
Customer Value Intelligence helps businesses measure what customers, cohorts and channels are economically worth. It distinguishes historical revenue, gross profit, contribution value, expected or forecast value and acquisition economics rather than inflating lifetime value.
Its VALUE-24 workflow defines scope, identity and observation rules, normalizes revenue and costs, compares cohorts, studies retention and repeat purchases and evaluates CAC, payback and uncertainty where evidence exists. Refunds, discounts, fulfillment and variable service costs matter; new cohorts have shorter observation windows and long-range forecasts require caution.
Use authorized order, subscription and cost evidence to identify value drivers and testable commercial opportunities. Modeled future value is never presented as realized value, and correlations do not establish causal effects. No data, attribution, margin or future purchases are invented, and no forecast guarantees profit.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
Reviews
No reviews yet
Be one of the first to try it. Every listed skill passes our trust checks below.
Security scanned
Passed our 8-point scan before listing
Fresh listing
Recently published to Agensi
Money-back guarantee
Doesn't do what its page promises? You get your money back.
Trust & safety
Security scanned
Verified clean 8 days ago
- Passed all security checks, Safe to install