Join forces with other publishers to outsmart AI summaries together
UK news publishers lose substantial click-through traffic and advertising revenue when Google’s AI summaries display their content without driving visitors to original articles.
CiteCollective is a collaborative platform where UK news organizations anonymously share AI summary performance data. The platform aggregates this intelligence into powerful collective playbooks, shared schema templates, and industry benchmarks that help every member recover traffic. Individual publishers get personalized recommendations informed by the wisdom of the entire network.
UK news publishers and online media organizations
True network effect - the more publishers that join, the smarter and more effective the shared optimization library becomes for everyone
friendly
Share your AI performance metrics without revealing competitive information
Access schemas and tactics that worked for other UK publishers
Get suggestions based on your content type using collective intelligence
See how your AI traffic loss compares to similar publishers
Curated and rated collection of working AI citation schemas
Templates and data to engage with Google and regulators
Visualize collective trends across UK media
Form smaller trusted circles within the network
Learn from detailed anonymized case studies
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| created_at | timestamp | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| org_name | text | No |
| vertical | text | No |
| anonymized_id | text | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| publisher_anonymized_id | text | No |
| schema_content | text | No |
| success_rate | int | Yes |
| content_vertical | text | No |
| votes | int | No |
| created_at | timestamp | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| insight_type | text | No |
| data | text | No |
| vertical | text | Yes |
| created_at | timestamp | No |
/api/contributeSubmit anonymized performance data to collective
/api/recommendationsGet personalized recommendations based on collective data
/api/schemasBrowse and search collective schema library
/api/benchmarksFetch industry benchmarking data
Cannot contribute data
None
None
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 80 | 15% | $348 | $4,176 |
| Month 6 | 650 | 22% | $3,182 | $38,184 |
The more you share (anonymously), the smarter we all become at forcing AI summaries to cite and link properly.
1. Seed with 12 progressive UK publishers through News Media Association connections offering lifetime 50% discount for being founding members. 2. Host virtual roundtable for digital directors on 'Collective Defense Against AI' and convert attendees. 3. Create compelling case study after first 90 days showing network-wide improvement and use it for outbound to larger publishers.
Excellent industry research
Slow, non-actionable, not real-time
Real-time actionable shared intelligence with direct implementation tools
Strong advocacy
No technical tools or shared schema library
Combines advocacy with immediately usable collective technical intelligence
Strong network effects - value increases dramatically with each additional participating UK publisher, creating high switching costs
The shared pain from AI Overviews has reached a critical threshold where publishers are now willing to collaborate on data sharing in ways they wouldn't have two years ago
Publishers hesitant to share data even anonymously
Start with strong anonymization, offer significant value before asking for contribution, use trusted industry partners as validators
Competition law concerns around industry collaboration
Work with legal counsel specializing in media to design strict anonymization protocols and avoid any pricing or competitive discussion
Success: At least 70% of participants say they would join and contribute
Success: At least 9 actively contributing data within 30 days
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