AI Icebreaker Generator

Turn a batch of Google Maps place records into one hyper-personalized cold-outreach opening line per business. Bring your own LLM key (Gemini has a generous free tier). Two modes: base uses only fields already present on the place, enriched also fetches the homepage and folds a summary into the prompt.

Feed it the output of the Google Maps Scraper and get one ready-to-send opener per business.

What It Does

Given a Google Maps place record, the actor asks an LLM to write ONE sentence that:

• Is at most 200 characters
• References something specific about the business (rating, category + city, tenure, description, homepage detail)
• Matches the requested tone (friendly, professional, casual, direct)
• Is grounded in the input data. Never a generic template, never invented facts.
• Falls back to an empty string when the record has too little signal (no name, or missing category AND reviews AND description)

Modes

Base (default, zero-fetch)

Uses only fields already on the place record:

• title / name
• category, categories
• city, country (from complete_address)
• rating / review_rating, review_count
• description
• phone, website (reference only, not fetched)

Enriched (opt-in)

Set enableEnriched: true. In addition to base mode, the actor fetches the business's homepage, condenses it into a ~1000 character markdown summary (headings + tagline + prose paragraphs), and appends it to the LLM prompt. Falls back silently to base mode when the site returns non-200, redirects strangely, or trips an anti-bot challenge.

Input

Two shapes are accepted, and you can mix them in one run.

Flat places list (natural shape, just pipe the google-maps-scraper output):

{
  "places": [
    {
      "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4",
      "title": "Example Coffee House",
      "category": "Coffee shop",
      "website": "https://example-coffee.example",
      "rating": 4.8,
      "review_count": 1240,
      "complete_address": { "city": "Berlin", "country": "Germany" }
    }
  ],
  "tone": "friendly",
  "outputLanguage": "en",
  "geminiApiKey": "AIza..."
}

Companies shape (with a company_id passthrough for join-back to your CRM):

{
  "companies": [
    { "company_id": "acme-42", "place": { "place_id": "ChIJ...", "title": "Example Company Ltd." } }
  ],
  "tone": "professional",
  "geminiApiKey": "AIza..."
}

LLM Configuration

You must supply at least one LLM key. All three providers are supported:

Provider	Free tier	Get a key
Gemini	Yes (generous)	https://aistudio.google.com/app/apikey
Groq	Yes	https://console.groq.com/keys
OpenRouter	Pay-as-you-go, cheap	https://openrouter.ai/keys

Set llmProvider to pick the primary, fallbackProvider and fallback2Provider for the chain. Same-provider transient errors (5xx, timeouts) get one retry; auth/quota errors fall through to the next provider.

Output

One row per input place:

{
  "company_id": "acme-42",
  "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4",
  "name": "Example Coffee House",
  "icebreaker_line": "Noticed you are running one of the highest-rated (4.8 stars, 1,240 reviews) coffee shops in Berlin. Curious how you keep that streak going.",
  "icebreaker_enriched": false,
  "llm_provider": "gemini",
  "llm_model": "gemini-2.0-flash",
  "llm_tokens_input": 340,
  "llm_tokens_output": 45,
  "generated_at": "2026-07-17T10:30:00Z"
}

icebreaker_line is an empty string when the record had too little signal to produce a specific line. The actor never invents facts to fill the gap.

How To Use It

1. Run Google Maps Scraper to collect places for a niche and city.
2. Feed the dataset into this actor as places (or wrap each in companies for join-back).
3. Pick a tone, set your Gemini key, and (optionally) turn on enriched mode.
4. Drop the output into your outbound sequencer.

Pricing

Pay-per-result via Apify Pay-Per-Event billing:

Event	Price	Description
Actor start	$0.001	Charged once per run
Icebreaker generated (base)	$0.003	Charged per row in base mode
Icebreaker generated (enriched)	$0.005	Charged per row when enriched mode succeeded

Generating 1,000 lines in base mode costs about $3. Empty input rows and rows the model refused to write for (insufficient signal) are still counted as a result. LLM API usage is billed by your provider directly, not by this actor.

Related Actors

Discovery:

• Google Maps Scraper - collect places in bulk

Enrichment:

• GBP Completeness Audit - score Google Business Profiles for lead prioritization
• Website Email Scraper - pull emails and phones from company sites
• Website Contact Extractor - LLM-powered people extraction

Notes

• Empty input is free. No enrichment-start is billed unless there is at least one valid place.
• The proxy configuration is only used by enriched mode's homepage fetch.
• Language: set outputLanguage: "auto" to have the model match the business's country language.

Issues & Feature Requests

If the model keeps refusing lines for a class of business, or if you would like a new tone, open an issue on the actor's Issues tab and we will take a look.