Sample size 200
Completed / Failed 200 / 0
Which content asset type do you believe is most effective at triggering direct citations in generative AI search engines like ChatGPT and Perplexity?
Proprietary survey data with numerical metrics and exact sample sizes
64.5%
n=129
Respondents for this option · Drivers
High perceived authority and trustworthiness by AI models
Direct alignment with user search intent and query specificity
Structural compatibility with AI indexing and extraction
Ease of production and scalability of the format
Comprehensive product feature documentation and technical guides
16.0%
n=32
Respondents for this option · Drivers
Structural compatibility with AI indexing and extraction
Direct alignment with user search intent and query specificity
High perceived authority and trustworthiness by AI models
Ease of production and scalability of the format
Secondary roundups citing third-party market research reports
11.0%
n=22
Respondents for this option · Drivers
Structural compatibility with AI indexing and extraction
Direct alignment with user search intent and query specificity
High perceived authority and trustworthiness by AI models
Ease of production and scalability of the format
Expert opinion pieces and thought leadership essays
7.0%
n=14
Respondents for this option · Drivers
High perceived authority and trustworthiness by AI models
Direct alignment with user search intent and query specificity
Structural compatibility with AI indexing and extraction
None of these are effective for AI search citations
1.5%
n=3
Respondents for this option · Drivers
Ease of production and scalability of the format
Proprietary survey data with numerical metrics and exact sample sizes audience
B2B content leaders prioritize proprietary survey data as the most effective asset for AI search engine citations.
129 / 200 respondents64.5%
The segment is most heavily concentrated in the Southern United States, representing 47% of the group.
Respondents are primarily aged 35-44 and hold master's degrees, indicating a preference for data-backed authority.
Male professionals make up the majority of this segment at 63%.
Key differences
Potential risks
What are they worried about?
High resource investment with uncertain ROI and citation frequency
The primary risk is sinking significant budget into high-production assets that fail to generate actual citations, leaving us with no measurable ROI for our search visibility efforts.
Traffic cannibalization by AI-generated summaries
The primary risk is that AI models will extract my proprietary data points to provide instant answers, which effectively cannibalizes my site traffic by removing the user's need to click through to my original content.
Technical barriers regarding schema, indexing, and parsing
The biggest risk is that proprietary data often lacks the structured schema and technical markup required for AI models to easily parse and index the specific numerical insights I provide.
Content obsolescence and rapid loss of relevance
The biggest risk is that third-party market data loses its edge rapidly, meaning my content could quickly become obsolete and fail to provide the fresh, authoritative insights that AI models prioritize for citations.
Sampling data