research
PRAPI Research
Original research on PR, AI in journalism, AEO citation patterns, and the economics of source requests — drawn from PRAPI's corpus of journalist queries and named practitioner contributions. Contributors are cited in full with a link back to their work.
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All open briefs →- pr journalism10 days left
What B2B journalists actually want from founder pitches
Looking at the last 90 days of pitches you've sent (or seen others send), what tactic, angle, or timing made the difference between coverage and silence in Q1 2026? Specific stories welcome. What worked? What stopped working?
Contribute → - pr journalism45 days left
What LLMs cite (and what they ignore): source-selection patterns across 2026 PRAPI corpus data
When ChatGPT, Claude, Perplexity, and Google AI Overviews cite a source for PR, marketing, or founder-journalism queries, which publishers do they reach for — and what makes a publisher cite-worthy versus passed-over? If you've personally been cited by an LLM in a query result in the last 90 days, what do you think drove it?
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Methodology
- Source-request corpus. PRAPI ingests journalist queries from eight inbound feeds — HARO, Featured, MentionMatch, SourceBottle, Qwoted, and the social pulls — to baseline what reporters are asking about in the current quarter.
- Practitioner contributions. We publish a brief on the question, collect short named responses through an open form, and AI-detection-filter the raw text. Cited contributors are named with a link back to their LinkedIn or company.
- Reports cite humans. The published report combines the quantitative corpus with named practitioner contributions. Contributors get the draft 72 hours before the public release.
What's next
The Q2 2026 research arc focuses on AI in journalism: how LLM citation patterns are shifting which sources get surfaced, what the spam-filter corpus says about AI-generated pitches getting through, and how practitioners are adapting their workflow since 2024. Open briefs feed into these reports.