How often is thinkwithgoogle.com cited by AI models?

thinkwithgoogle.com was cited 2 times by AI models, representing 0.4% of all source citations.

Which AI models cite thinkwithgoogle.com?

thinkwithgoogle.com is cited by 1 AI models including Perplexity Sonar (with search) (latest), Anthropic Claude Sonnet (latest), OpenAI ChatGPT Latest, Google Gemini Flash (latest), X.AI Grok (latest).

What is thinkwithgoogle.com's ranking among source domains?

thinkwithgoogle.com ranks #55 out of 266 source domains analyzed (with 183 brands also tracked).

What brands are associated with thinkwithgoogle.com?

AI models reference thinkwithgoogle.com when discussing brands like Google.

How is source ranking determined?

Sources are ranked by Share of Voice = Model Coverage × Quality Score. Model weights are based on Monthly Active Users (OpenAI ChatGPT Latest: 900M MAU, Google Gemini Flash (latest): 650M MAU, Perplexity Sonar (with search) (latest): 45M MAU, etc.). Sources appearing earlier in AI responses receive higher prominence scores.

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Share of Voice

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About thinkwithgoogle.com (Tech Companies)

This page provides details about thinkwithgoogle.com (Tech Companies) which was ranked #55 out of 266 in the list of sources (2 citations (0.4% share)) in answers from AI models (OpenAI ChatGPT Latest) when they were asked the following 1 question: "What are the most common mistakes people make with AI Tools for Marketers and how can they be avoided?" on Oct 24, 2025 by AI Chat Watch. This source is referenced for brands: Google.

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Voice

Position

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Citations

Used by AI Models

Model	Voice	Position	Citations
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Pages from thinkwithgoogle.com (1 link)

URL Path	Citations	Position
/marketing-strategies/data-and-measurement/what-is-incrementality	2	95

Brands Referenced By This Website (1 brand)

Brand	Voice	Mentions
Google	58.6%	104

Citations from AI Responses

OpenAI ChatGPT Latest (2 citations)

What are the most common mistakes people make with AI Tools for Marketers and how can they be avoided?

[...] split), incrementality testing, and appropriate attribution. Tie content/creative changes to lift vs. a control. Sources: A/B testing (https://en.wikipedia.org/wiki/A/B_testing), GA4 – Attribution (https://support.google.com/analytics/answer/10596866), Think with Google – What is incrementality? (https://www.thinkwithgoogle.com/marketing-strategies/data-and-measurement/what-is-incrementality/), Meta – Conversion Lift (https://www.facebook.com/business/help/294516419058121), Marketing mix modeling (https://en.wikipedia.org/wiki/Marketing_mix_modeling) - Mistake 8: Bias and representational harm in content or targeting How to avoid: Audit datasets, prompts, and outputs for fairness; ad [...]

thinkwithgoogle.com/marketing-strategies/data-and-measurement/what-is-incrementality October 24, 2025

[...] with-claude/prompt-engineering). - Add a review workflow: fact check, compliance check, brand check, and accessibility check (https://developers.google.com/search/docs/fundamentals/creating-helpful-content; https://www.w3.org/TR/WCAG22/). - Run at least one controlled lift test per major AI change (https://www.thinkwithgoogle.com/marketing-strategies/data-and-measurement/what-is-incrementality/; https://www.facebook.com/business/help/294516419058121). - Lock down data: use enterprise instances with documented data handling (https://openai.com/policies/api-data-usage-policies; https://cloud.google.com/vertex-ai/docs/generative-ai/data-governance-security; https://learn.microsoft.com/en-us/c [...]