/apify-ai-search-visibility-tracker

name: apify-ai-search-visibility-tracker
description: Track whether a brand and its competitors get cited or mentioned across Google AI Overviews, Google AI Mode, ChatGPT Search, Perplexity, Microsoft Copilot, and Google Gemini for a defined set of prompts, on a recurring schedule. Use when user asks to track AI visibility, monitor brand mentions in AI search, track ChatGPT citations, do AI search SEO tracking, GEO tracking (Generative Engine Optimization), AEO tracking (Answer Engine Optimization), monitor Perplexity citations, track AI Overviews mentions, see if their brand shows up in AI search, discover which prompts competitors rank for in AI search, find citation opportunities, or audit a website for AI visibility readiness.
author: Daniela Ryplová
author_url: https://github.com/danielarypl
metadata:
  keywords: "ai-search, geo, aeo, generative-engine-optimization, answer-engine-optimization, brand-visibility, citations, ai-overviews, chatgpt-search, perplexity, copilot, gemini, google-search-scraper, monitoring, scheduling"

AI Search Visibility Tracker

Four workflows covering the full AI visibility lifecycle: **discover** which prompts matter → **find** citation opportunities → **audit** your site → **track** over time.

All workflows use `apify/google-search-scraper` for AI search. Workflow C also uses `apify/website-content-crawler`.

**Recommended flow:** Run Workflow A to discover prompts → Workflow B to find citation opportunities → Workflow C to audit your site → Workflow D to track everything on a schedule.

---

Workflow A — Competitor Prompt Discovery

**Goal:** Find which queries surface a competitor in AI search answers, so you know which prompts are worth monitoring.

Inputs to collect

| # | Input | Notes | |---|-------|-------| | 1 | Competitor domain(s) | e.g. `brightdata.com`, `scraperapi.com` | | 2 | Seed topic keywords | e.g. "web scraping", "data extraction API" | | 3 | AI sources | Default: all six (AI Overviews, AI Mode, ChatGPT, Perplexity, Copilot, Gemini) |

Workflow

1. Generate 15–30 candidate queries from seed keywords using these templates:

• `best [topic]`, `[topic] tools`, `how to [topic]`, `[topic] for [use case]`
• `[topic] vs [competitor brand]`, `[competitor brand] alternative`
• `[topic] API`, `[topic] pricing`, `[topic] tutorial`

2. Run `apify/google-search-scraper` for each candidate query. For each result, extract:

• `aiOverview.sources[]`, `aiMode.sources[]`, `chatGptAnswer.sources[]`, `perplexityAnswer.sources[]`, `copilotAnswer.sources[]`, `geminiAnswer.sources[]`
• Also check `answer_text` / `aiOverview.text` for competitor brand name mentions (word-boundary match: `\bBrand\b`)

3. For each (query, source) pair where the competitor domain or brand appears: record a hit.

4. Output a prompt-major table sorted by total hit count descending:

| Query | ChatGPT | Perplexity | AI Overviews | AI Mode | Copilot | Gemini | Total |
|-------|---------|------------|--------------|---------|---------|--------|-------|
| "best web scraping API" | ✓ | ✓ | — | ✓ | — | ✓ | 4 |
| "how to scrape Google" | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 6 |

5. Deliver the top-N queries (default 10) as a ready-to-paste list for Workflow D's `config.json` prompts.

---

Workflow B — Citation Opportunity Finder

**Goal:** For a target topic, identify which domains and content types AI engines most often cite — revealing where to publish or pitch content.

Inputs to collect

| # | Input | Notes | |---|-------|-------| | 1 | Target topic / industry | e.g. "web scraping", "ecommerce automation" | | 2 | Seed queries | 5–20 queries covering the topic space | | 3 | AI sources | Default: all six | | 4 | Deep-crawl top cited? | Optional: crawl top-3 cited pages with `website-content-crawler` for structure patterns |

Workflow

1. Run `apify/google-search-scraper` for each seed query across selected AI sources.

2. Collect every URL from `sources[]` across all results. Normalise to registrable domain (`blog.example.com` → `example.com`).

3. Aggregate:

• **By domain**: count citations, list which AI sources cite it, list which queries triggered it
• **By content type**: infer from URL path patterns (docs → `/docs/`, `/reference/`; blog → `/blog/`; news → known news domains)

4. Rank by total citation count. Output:

Top-cited domains for "web scraping" (42 queries × 6 sources):
| Domain | Citations | AI Sources | Inferred type |
|--------|-----------|------------|--------------|
| docs.apify.com | 38 | ChatGPT, Perplexity, AI Mode | Documentation |
| scraperapi.com/blog | 21 | AI Overviews, Gemini | Long-form blog |

5. If deep-crawl enabled: run `apify/website-content-crawler` on the top-3 cited URLs per domain. From the markdown output, extract:

• First heading that directly answers the query
• Presence of code blocks in first 500 words
• Word count
• Whether an H2/H3 contains the exact query phrase

6. Summarise patterns: "AI engines in this topic prefer [long-form docs / short direct-answer posts]. Typical cited page: [word count range], [has/lacks direct-answer H2], [has/lacks code example above the fold]."

---

Workflow C — GEO Website Audit

**Goal:** Check whether a specific website's content is structured for AI citation; compare it against what AI engines actually cite for your target prompts.

Inputs to collect

| # | Input | Notes | |---|-------|-------| | 1 | Your website URL | e.g. `https://apify.com` | | 2 | Target prompts | Use Workflow A output, or supply 5–10 directly | | 3 | AI sources | Default: all six |

Workflow

1. Run `apify/google-search-scraper` for each target prompt. For each (prompt × source) record whether your registrable domain appears in `sources[]`.

2. For prompts where your domain is **not** cited: identify the top-cited competitor URL for that prompt.

3. Run `apify/website-content-crawler` on:

• Your most relevant page(s) for each un-cited prompt
• The t