Rank clients by LTV | Well skills

Rank clients by LTV

The skill sums every paid invoice by customer and sorts from your biggest down, with real currency amounts and an as-of date. To be upfront: this ranks revenue paid to date, not a predictive model of future value, because there is no churn or retention data behind it.

npx skills add wellapp-ai/skills --skill rank-clients-by-ltv

Who are our best customers?

Stripe leads at €412K paid to date, then Mercury at €288K, Qonto at €196

How the skill answers

Every step of the run, in order, with the card each one returns. A step that hands its work to another skill says which one.

  1. You ask

Who are our best customers?

  1. Pin the workspace

Workspaces

Pick the workspaces to work in.
  1. Confirm the connections this answer needs

Connect a tool

Pick a tool to connect it to Well.

  1. Verify the data itself has landed

  2. Resolve your own company

  3. Resolve the time window

  4. Query paid revenue by customer

  5. Normalize currency

  6. Sort and limit

  7. If any required step errors or returns unusable data

  8. You get

Companies

| Company Name | Total amount |
| --- | --- |
| Stripe | €412,000.00 |
| Mercury | €288,000.00 |
| Qonto | €196,000.00 |
| HSBC | €154,000.00 |

Stripe leads at €412K paid to date, then Mercury at €288K, Qonto at €196K, and HSBC at €154K. This ranks realized revenue actually paid, not a predicted future value.

Frequently asked questions

Is this really lifetime value? It is realized revenue to date, which is the honest version of the question. A true LTV model needs churn and retention data that invoices alone cannot provide.

Does it count unpaid invoices? No. Only invoices actually paid count toward the ranking, so the order reflects cash received rather than cash promised.

Can it rank by something else? Yes. Ask for a specific window, a currency, or a segment and the ranking recomputes.