TrustRadius: an HG Insights company

CrunchJunkie

What is CrunchJunkie?

CrunchJunkie is an AI Visibility Software (GEO Tools) and Marketing Analytics platform. The system monitors how brands, products, and websites are cited across generative search engines while consolidating multi-channel advertising and analytics metrics into customizable client reports.

Key Capabilities
  • Generative Engine Optimization (GEO) Monitoring: Tracks brand mentions, product-level visibility, rankings, and citations across ten generative answer engines (ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, Google AI Mode, Microsoft Copilot, Grok, DeepSeek, and Meta AI).
  • Statistical Rigor & Auditing: Calculates sample size metrics, margin of error ranges, and pooled rates for prompt evaluations. Includes automated site audit functionality and gap-analysis content brief generation.
  • Multi-Channel Reporting Consolidation: Ingests metrics from advertising networks and analytics services (Google Ads, Meta Ads, Microsoft Ads, LinkedIn Ads, Amazon Ads, Reddit Ads, GA4, Search Console, Facebook, Instagram, Matomo, Piwik PRO, and Google Merchant Center) to generate scheduled, white-label client reports.
  • Model Context Protocol (MCP) Interface: Incorporates an OAuth-secured MCP connector exposing 45 tools to query reporting data and generate documentation directly from compatible AI clients (including Claude, ChatGPT, and Cursor), featuring workspace owner write controls.
  • Attribution & Traffic Analysis: Connects with Google Analytics 4 (GA4) to analyze website traffic attribution originating from AI search engines and assistants.

Audience & Use Cases
  • Audience: Digital marketing agencies, in-house growth teams, and search engine optimization (SEO) analysts.
  • Use Case: Tracking brand presence and competitive share of voice across AI engines, auditing site structure for generative search readiness, and consolidating cross-channel ad spend and analytics reporting for client presentation.

Technical Specifications
  • Supported Integrations: GA4, Google Search Console, Google Merchant Center, Matomo, Piwik PRO, and major digital ad platforms (Google Ads, Meta Ads, Microsoft Ads, LinkedIn Ads, Amazon Ads, Reddit Ads).
  • Protocol Support: Model Context Protocol (MCP) via OAuth with configurable read/write permission tiers.
  • Data Residency & Infrastructure: Hosted in Frankfurt, Germany (EU-resident infrastructure) with a public sub-processor directory; developed and operated by Tiki-Taka Media GmbH (Hamburg, Germany).
  • Vendor Claims: According to the vendor, plans start at €14 per month per brand managed, include a 14-day trial, and support either direct user-provided LLM API keys without vendor markup or metered managed AI models.

Categories & Use Cases

Media

Screenshot of AI Visibility overview for one brand. It shows how often the brand is named across the tracked AI engines (here 35.6% of 2,848 answers, with the margin of error), its average position and sentiment, how often its own pages are retrieved and cited, whether AI crawlers can reach the site, and the mention rate for each tracked prompt. Every percentage carries its sample size.
Screenshot of A white-label client report. The agency's own name and logo head the report, and each AI-visibility metric (visibility, share of voice, sentiment, average position, mentions) shows its change against the previous period and the number of AI answers it is based on. The same report can also carry Google Ads, Meta, GA4 and Search Console widgets.
Screenshot of The Signals inbox lists changes that deserve attention, each with its sample size and confidence. In this example: a firewall refusing 13% of AI-crawler requests (465 of 3,515), two statistically significant visibility drops, missing Product schema, and a competitor overtaking on share of voice. Signals can be acknowledged, snoozed, or turned into automated alerts.
Screenshot of GEO Audit for a website: an AI-readiness score (93 of 100 here, across 6 pages) with sub-scores for AI crawler access, content accessibility, structured data, technical SEO hygiene and llms.txt. Below it, the fixes are ranked by the points each would add, and the built-in assistant can draft each fix.
Screenshot of Brand Perception shows the words AI models use when they describe a brand, here based on 1,952 mentions over 30 days: the term most associated with the brand, the term only it receives, the largest gap against a competitor, and a radar chart comparing its description profile with selected competitors.
Screenshot of Citation gap analysis: the domains AI engines cite when they name competitors but not you, ranked by gap score, with how often each domain was cited for competitors and for your brand. It is the working list for outreach and content placement.
Screenshot of Sources shows which domains AI engines cite when answering the tracked prompts, over time and filterable by engine, topic and tag. Source health checks the cited pages for dead links and retracted citations (here 150 cited pages; all 40 checked so far are healthy).
Screenshot of Tracked prompts with suggested additions. Suggestions are grounded in the brand, its competitors and its category and are labelled as discovery or gap prompts. CrunchJunkie does not show a search volume for prompts, because no tool can measure one.
Screenshot of Every metric links back to the raw AI answers. Responses can be filtered by mentioned, not mentioned or mention gap and by tag, and each shows the engine's full answer with the links it cited.

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Screenshot of AI Visibility overview for one brand. It shows how often the brand is named across the tracked AI engines (here 35.6% of 2,848 answers, with the margin of error), its average position and sentiment, how often its own pages are retrieved and cited, whether AI crawlers can reach the site, and the mention rate for each tracked prompt. Every percentage carries its sample size.