Prospecting

curl -X POST "https://app.tigalabs.com/api/v1/apollo-organization-search" \
  -H "X-Tiga-Auth: $TIGA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "organization_num_employees_ranges": ["50,200"],
    "organization_locations": ["United States"],
    "q_organization_industry_tag_ids": ["<apollo-industry-id>"],
    "page": 1,
    "per_page": 25
  }'

Full filter options: https://docs.apollo.io/reference/organization-search

3. Paginate through results (page: 2, 3, ...) until you have enough accounts or results thin out.

4. Create a Tiga list:

curl -X POST "https://app.tigalabs.com/api/v1/lists" \
  -H "X-Tiga-Auth: $TIGA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"list": {"name": "TAL - <ICP Name> - 2026-03-20", "object_type": "account"}}'

5. Create accounts from Apollo results (deduplicate by domain):

curl -X POST "https://app.tigalabs.com/api/v1/account" \
  -H "X-Tiga-Auth: $TIGA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "<org.name>",
    "domain": "<org.primary_domain>",
    "linkedin_url": "<org.linkedin_url>"
  }'

Handle 409 Conflict — account already exists; retrieve existing ID via GET /api/v1/accounts with search.

6. Add accounts to list:

curl -X POST "https://app.tigalabs.com/api/v1/lists/<list-id>/add-members" \
  -H "X-Tiga-Auth: $TIGA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"object_ids": ["<account-id-1>", "<account-id-2>"]}'

Workflow B: Prompt → Target Account List

Use when: You have a natural-language description of your target market but no structured ICP yet.

Steps

1. Extract ICP attributes from the prompt — Parse the user's description into:

   • Industry / vertical
   • Employee count range
   • Revenue range
   • Geography
   • Key technologies
   • Business signals (growth stage, funding, hiring patterns)

2. Run Apollo search using extracted attributes (see Workflow A, steps 2-3). Start broad, then tighten filters based on result quality.

3. Create accounts and list (Workflow A, steps 4-6).

4. Layer ICP validation signals — Create an ICP Fit Check signal to validate each account:

{
  "label": "ICP Fit Check",
  "is_computed_column": true,
  "type": "text",
  "computed_config": {
    "type": "gpt",
    "prompt": "Does {{.AccountName}} ({{.AccountWebsite}}) match this target profile: <paste ICP description>? Answer yes or no with a 1-sentence reason.",
    "is_account_insight": true,
    "can_use_web_search": true,
    "expiration_in_days": 30,
    "word_limit": 60
  }
}

5. Run signal on the list, poll to completion, and filter — keep only accounts where the signal returns "yes".

Workflow C: Seed Accounts → Lookalikes

Use when: You have a list of known best-fit customers and want to find more companies like them.

Steps

1. Create a Firmographic Summary signal:

{
  "label": "Firmographic Summary",
  "is_computed_column": true,
  "type": "text",
  "computed_config": {
    "type": "gpt",
    "prompt": "Describe {{.AccountName}} ({{.AccountWebsite}}) in terms of: industry, business model, employee count range, target customer, and key technologies used. Be specific.",
    "is_account_insight": true,
    "can_use_web_search": true,
    "word_limit": 100
  }
}

2. Run the signal across seed accounts — Create a list with seeds, attach the signal, run it, and poll to completion.

3. Synthesize ICP — Read all signal outputs and identify common patterns across seeds. Translate these into structured Apollo search filters (industry tags, employee ranges, keywords).

4. Search Apollo with the synthesized ICP (Workflow A, steps 2-3).

5. Exclude existing customers — Filter out domains already in Tiga via GET /api/v1/accounts with search.

6. Validate lookalikes — Run an ICP Fit Check signal (Workflow B, step 4) on the new accounts.

7. Create final TAL with validated lookalike accounts.

Workflow D: Conference List → TAL

Use when: You have a list of companies attending a conference and want to build a TAL from them.

Steps

1. Create accounts for each conference company:

curl -X POST "https://app.tigalabs.com/api/v1/account" \
  -H "X-Tiga-Auth: $TIGA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "<company>", "domain": "<domain>", "linkedin_url": "<linkedin>"}'

Handle 409 Conflict for duplicates.

2. Create a Tiga list:

POST /api/v1/lists
{"list": {"name": "Conference - <event name> - 2026-03-20", "object_type": "account"}}

3. Add all accounts to the list via POST /api/v1/lists/:id/add-members.

Workflow E: Scraped Page → TAL

Use when: You have company names/domains scraped from a web page (e.g., a logos section, a directory) and want to build a TAL.

Steps

1. Parse the scraped data — Extract company names and domains from the raw input.

2. Create accounts for each company (same as Workflow D, step 1). Use domain as the dedup key.

3. Create a Tiga list and add all accounts.

4. Optionally validate with ICP signals — If the scraped list is broad, run an ICP Fit Check signal (Workflow B, step 4) to filter down to relevant accounts.