# From ten customers to the whole market.

Take your best customers, count in Markets how many companies resemble them, and load only the sample that fits your ICP. With Claude Code your agent derives the criteria from your closed-won deals.

https://listplus.ai/en/gtm-workflows/lookalike-companies-total-addressable-market

## Inputs and connections

Ten to fifty closed-won companies (a domain is enough) and a sense of what they have in common. The agent reads them from the CRM or a CSV.

An agent with a key or sign-in. The people search takes the filter values from search_options.

## Steps

1. **Derive the ICP from closed-won** (Claude Code · by call). The agent reads the companies and proposes three to five shared criteria – industry, size, country, technology. You confirm.
2. **Count the market** (ListPlus · by call). count_companies counts how many companies match the criteria – broken down by country or industry. Counting costs no credits through the agent.
3. **Load a sample** (ListPlus · by call). 25 companies into a new list, charged per company. Similar companies to a template cost five times as much – so criteria first, similarity second.
4. **Score and decision makers** (ListPlus · by call). A score column sorts the sample; for the A-companies the people search finds the right roles – 2 credits per page of 25 people.
5. **Approve the list** (Your team · manual in ListPlus). If the sample is right, the list loads the rest page by page – without paying twice for anything.

## Expected sample result

12 closed-won companies → criteria software, 51–200 employees, United States → 41,300 companies counted, 9,870 of them in California. 25 companies loaded as a sample; people only after approval.

## Costs and boundaries

Counting costs no credits through the agent (in the app 1 credits per new count). Loading 25 companies: 6.25 credits ($0.22 on Pro); similar companies to a template 5× that. Finding people: 2 credits per page of 25.

A count is a market size, not a buying signal. The database counts exactly up to 100,000; the number of people a search matches is known only with its first page.

## Agent prompt

Read my closed-won deals from HubSpot (company, domain). Derive three to five shared criteria (industry, size, country) and show them to me. Count with count_companies how many companies match, by country. Then load 25 companies as a sample into a new list and tell me the price first. Do not search for people before I have seen the sample.

## Tools

`search_options`, `count_companies`, `load_companies`, `add_column`, `search_people`

MCP: https://listplus.ai/mcp
REST: https://listplus.ai/a/v1/{action}
API: https://listplus.ai/a

## Sample calls

These calls use fictional IDs. Use the IDs returned by your workspace.

```text
count_companies({
  "filters": {
    "countries": [
      "DE",
      "AT",
      "CH"
    ],
    "industries": [
      "Software"
    ],
    "employees": [
      "51-200"
    ]
  },
  "by": "countries"
})
load_companies({
  "filters": {
    "countries": [
      "DE"
    ],
    "industries": [
      "Software"
    ],
    "employees": [
      "51-200"
    ]
  },
  "limit": 25
})
```