Changes for page Ideal Customer Profile (ICP)

Last modified by Robert Schaub on 2026/02/08 08:32

From version 1.4

edited by Robert Schaub
on 2026/02/08 08:32

Change comment: Renamed back-links.

To version 1.1

edited by Robert Schaub
on 2026/01/20 20:44

Change comment: Imported from XAR

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--Archive.FactHarbor 2026\.02\.08.Organisation.WebHome
++FactHarbor.Organisation.WebHome

Content

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  == 1. Purpose ==
  Understanding who benefits most from FactHarbor helps us:
--
  * **Product Development**: Prioritize features that serve core user needs
  * **Marketing**: Communicate value effectively to target audiences
  * **Partnerships**: Identify and cultivate strategic relationships
@@ -18,13 +18,11 @@
  === 2.1 Journalists & Newsrooms ===
  **Profile**:
--
  * Working journalists at news organizations (local to international)
  * Fact-checkers and verification specialists
  * Editorial teams producing investigative or political content
  **Core Needs** (from User Needs documentation):
--
  * **UN-4**: Fast social media fact-checking (≤15 seconds to initial verdict)
  * **UN-14**: API integration into professional workflows
  * **UN-5/UN-6**: Source provenance and publisher reliability tracking
@@ -31,7 +31,6 @@
  * **UN-7**: Evidence transparency for editorial review
  **Key Pain Points**:
--
  * Time pressure with breaking news and viral content
  * Need to verify claims quickly without sacrificing accuracy
  * Difficulty tracing claims to original sources
@@ -41,7 +41,6 @@
  FactHarbor provides structured, scenario-based analysis that reveals **how** conclusions are reached, saving time while providing the context needed for accurate reporting.
  **Success Indicators**:
--
  * Reduced time spent on claim verification
  * Ability to cite FactHarbor analyses in published work
  * Improved editorial confidence in complex stories
@@ -49,7 +49,6 @@
  === 2.2 Researchers & Academics ===
  **Profile**:
--
  * University researchers (political science, communications, media studies)
  * Think tank analysts
  * PhD students studying misinformation
@@ -56,7 +56,6 @@
  * Data scientists working on verification systems
  **Core Needs**:
--
  * **UN-7**: Complete evidence transparency
  * **UN-9**: Methodology transparency (auditable reasoning)
  * **UN-13**: Ability to cite FactHarbor verdicts in academic work
@@ -63,7 +63,6 @@
  * **UN-15**: Verdict evolution timeline (how assessments change with new evidence)
  **Key Pain Points**:
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  * Existing fact-checks are methodologically opaque
  * Need structured data for quantitative analysis
  * Difficulty comparing how claims are assessed across sources
@@ -73,7 +73,6 @@
  FactHarbor provides **transparent, structured methodology** that can be cited, analyzed, and built upon. The Evidence Model approach creates reusable data for academic research.
  **Success Indicators**:
--
  * Academic papers citing FactHarbor methodology
  * Researchers using FactHarbor data in studies
  * Methodology validation by academic institutions
@@ -81,7 +81,6 @@
  === 2.3 Educators ===
  **Profile**:
--
  * University professors (media literacy, critical thinking, journalism)
  * High school teachers (civics, social studies, media studies)
  * Librarians and information literacy specialists
@@ -88,7 +88,6 @@
  * Corporate trainers (media literacy programs)
  **Core Needs**:
--
  * **UN-3**: Article summaries with FactHarbor analysis for teaching materials
  * **UN-8**: Understanding disagreement and consensus (why experts differ)
  * **UN-9**: Methodology transparency for pedagogical purposes
@@ -95,7 +95,6 @@
  * **UN-7**: Evidence transparency to teach source evaluation
  **Key Pain Points**:
--
  * Fact-checks don't show reasoning process for teaching
  * Hard to teach critical thinking with black-box verdicts
  * Need tools that demonstrate **how** to evaluate claims
@@ -105,7 +105,6 @@
  FactHarbor teaches the **process** of evidence evaluation, not just the answer. Students see explicit assumptions, multiple scenarios, and how confidence levels are determined.
  **Success Indicators**:
--
  * Educators integrating FactHarbor into curricula
  * Student engagement with evidence exploration features
  * Educational institution partnerships
@@ -113,7 +113,6 @@
  === 2.4 Policy Analysts ===
  **Profile**:
--
  * Government policy advisors
  * NGO research staff
  * Legislative aides
@@ -120,7 +120,6 @@
  * Regulatory analysts
  **Core Needs**:
--
  * **UN-2/UN-3**: Context-dependent analysis (claims true under some conditions, false under others)
  * **UN-8**: Understanding why reasonable people disagree
  * **UN-1**: Trust assessment with explicit confidence ranges
@@ -127,7 +127,6 @@
  * **UN-17**: In-article claim highlighting for briefing documents
  **Key Pain Points**:
--
  * Policy questions rarely have simple true/false answers
  * Need to understand stakeholder perspectives and their evidence
  * Difficulty synthesizing information from multiple sources
@@ -137,7 +137,6 @@
  FactHarbor's **scenario-based analysis** explicitly maps how conclusions depend on assumptions, enabling policy analysts to present balanced, well-sourced briefings.
  **Success Indicators**:
--
  * Policy briefs citing FactHarbor analyses
  * Repeat usage for complex policy questions
  * Feedback on improved briefing quality
@@ -145,7 +145,6 @@
  === 2.5 Content Consumers (General Public) ===
  **Profile**:
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  * Social media users seeking to verify viral claims
  * Engaged citizens following news and politics
  * People making decisions based on contested information
@@ -152,7 +152,6 @@
  * Anyone who has been frustrated by oversimplified fact-checks
  **Core Needs**:
--
  * **UN-1**: Trust assessment at a glance (immediate visual understanding)
  * **UN-4**: Fast social media fact-checking
  * **UN-12**: Ability to submit unchecked claims
@@ -159,7 +159,6 @@
  * **UN-17**: In-article claim highlighting when reading content
  **Key Pain Points**:
--
  * Don't trust fact-checkers' authority
  * Want to understand reasoning, not just accept verdicts
  * Time-constrained but want to make informed decisions
@@ -169,7 +169,6 @@
  FactHarbor shows **reasoning you can inspect**. Trust comes from transparent methodology, not authority. You can form your own judgment based on visible evidence.
  **Success Indicators**:
--
  * User retention (return visits)
  * Time spent exploring evidence details
  * Claims submitted for verification
@@ -182,7 +182,6 @@
  **Priority**: HIGH (Tier 1)
  **Target Partners**:
--
  * Swiss Broadcasting (SRG SSR, SRF, RTS, RSI)
  * Major newspapers (Tamedia, NZZ)
  * Regional news organizations
@@ -189,12 +189,10 @@
  * Digital-first news outlets
  **Partnership Value**:
--
  * **For Partners**: Automated initial analysis saves journalist time; structured evidence for reader transparency
  * **For FactHarbor**: Validation, use cases, credibility, potential funding
  **Engagement Model**:
--
  * API integration for newsroom tools
  * Embedded analysis widgets
  * Co-branded fact-checking initiatives
@@ -205,7 +205,6 @@
  **Priority**: HIGH (Tier 1)
  **Target Partners**:
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  * IFCN (International Fact-Checking Network) members
  * EFCSN (European Fact-Checking Standards Network) members
  * dpa Fact-Checking (DACH region)
@@ -213,12 +213,10 @@
  * Full Fact (UK)
  **Partnership Value**:
--
  * **For Partners**: Technology platform, scalability, methodology alignment
  * **For FactHarbor**: Credibility, network access, ecosystem integration
  **Engagement Model**:
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  * Open-source technology sharing
  * ClaimReview schema collaboration
  * Joint methodology development
@@ -229,7 +229,6 @@
  **Priority**: HIGH (Tier 1)
  **Target Partners**:
--
  * ETH Zurich / University of Zurich (Swiss, research collaboration)
  * Duke Reporters' Lab (ClaimReview, Tech & Check)
  * Harvard Shorenstein Center (network access)
@@ -237,12 +237,10 @@
  * Oxford Reuters Institute (journalism research)
  **Partnership Value**:
--
  * **For Partners**: Research platform, real-world data, novel methodology to study
  * **For FactHarbor**: Academic validation, grant access (Innosuisse), publications
  **Engagement Model**:
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  * Research partnerships
  * Student thesis projects
  * Co-authored publications
@@ -254,7 +254,6 @@
  **Priority**: MEDIUM (Tier 2)
  **Target Partners**:
--
  * Knight Foundation (journalism innovation)
  * Google News Initiative (fact-checking fund)
  * Swiss Innosuisse (research/innovation grants)
@@ -262,12 +262,10 @@
  * Prototype Fund Switzerland
  **Partnership Value**:
--
  * **For Partners**: Support innovative, transparent approach to misinformation
  * **For FactHarbor**: Operational funding, validation, network access
  **Engagement Model**:
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  * Grant applications
  * Progress reporting
  * Impact documentation
@@ -278,7 +278,6 @@
  === 4.1 Unifying Frustrations ===
  All ideal customers share frustration with:
--
  * Binary "true/false" verdicts that hide complexity
  * Opaque methodology ("trust us" authority model)
  * Lack of explicit assumptions and confidence ranges
@@ -288,7 +288,6 @@
  === 4.2 Unifying Values ===
  All ideal customers value:
--
  * **Transparency**: Visible reasoning chains and methodology
  * **Nuance**: Context-dependent truth (scenarios)
  * **Independence**: Forming own judgment from evidence
@@ -298,7 +298,6 @@
  === 4.3 Decision Criteria ===
  When evaluating fact-checking tools, ideal customers prioritize:
--
 . **Methodology Transparency**: Can I see how conclusions are reached?
 . **Evidence Quality**: Are sources traceable and credible?
 . **Nuance Handling**: Does it acknowledge complexity?
@@ -310,7 +310,6 @@
  === 5.1 Awareness ===
  **How they find us**:
--
  * Academic publications citing FactHarbor
  * Referrals from fact-checking organizations
  * Search engine results (ClaimReview schema visibility)
@@ -320,7 +320,6 @@
  === 5.2 Evaluation ===
  **What they assess**:
--
  * Methodology documentation (open and detailed?)
  * Sample analyses (quality and transparency?)
  * Open-source code (auditable?)
@@ -330,7 +330,6 @@
  === 5.3 Adoption ===
  **How they start**:
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  * Submit a claim they're curious about
  * Explore an existing analysis in depth
  * Review methodology documentation
@@ -340,7 +340,6 @@
  === 5.4 Retention ===
  **Why they return**:
--
  * Consistent quality and transparency
  * Time savings in verification workflow
  * Unique value (scenario analysis not available elsewhere)
@@ -354,13 +354,11 @@
  **Profile**: Users who want verdicts that confirm their existing beliefs
  **Why Not Ideal**:
--
  * Will be frustrated by nuanced, scenario-based analysis
  * May reject conclusions that don't match expectations
  * Not looking for transparent reasoning—looking for validation
  **How to Handle**:
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  * Don't compromise methodology to satisfy them
  * The transparency may eventually convert some
@@ -369,13 +369,11 @@
  **Profile**: Users who only want instant answers, no interest in evidence
  **Why Not Ideal**:
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  * Don't value FactHarbor's core differentiator (transparency)
  * Would be better served by simpler binary fact-checkers
  * Won't engage with evidence or scenarios
  **How to Handle**:
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  * Provide quick summary views (UN-1: trust at a glance)
  * Make deeper exploration available but not required
@@ -384,13 +384,11 @@
  **Profile**: Users seeking to game or manipulate the system
  **Why Not Ideal**:
--
  * Waste resources
  * Damage system integrity
  * Not genuine users
  **How to Handle**:
--
  * AKEL detection of manipulation patterns
  * Moderation for flagged escalations
  * Transparent ban policies
@@ -400,7 +400,6 @@
  === 7.1 Segment Metrics ===
  Track for each segment:
--
  * **Acquisition**: How many from each segment?
  * **Activation**: Do they complete first analysis?
  * **Engagement**: Do they explore evidence?
@@ -409,27 +409,28 @@
  === 7.2 Segment-Specific Success Indicators ===
--| Segment | Key Success Metric |\\
--|-|-|\\
--| Journalists | API calls per newsroom; time saved per verification |\\
--| Researchers | Papers citing FactHarbor; data downloads |\\
--| Educators | Curricula integrations; student engagement |\\
--| Policy Analysts | Briefings citing FactHarbor; repeat usage |\\
++| Segment | Key Success Metric |
++|---------|-------------------|
++| Journalists | API calls per newsroom; time saved per verification |
++| Researchers | Papers citing FactHarbor; data downloads |
++| Educators | Curricula integrations; student engagement |
++| Policy Analysts | Briefings citing FactHarbor; repeat usage |
  | Content Consumers | Retention rate; evidence exploration rate |
  === 7.3 Partnership Metrics ===
--| Partner Type | Success Metric |\\
--|-||\\
--| Media | Integration count; co-published analyses |\\
--| Fact-Checkers | Data sharing volume; methodology alignment |\\
--| Academic | Papers published; grants received |\\
++| Partner Type | Success Metric |
++|-------------|----------------|
++| Media | Integration count; co-published analyses |
++| Fact-Checkers | Data sharing volume; methodology alignment |
++| Academic | Papers published; grants received |
  | Funders | Grants awarded; renewal rate |
  == 8. Related Pages ==
--* [[User Needs>>Archive.FactHarbor 2026\.02\.08.Specification.Requirements.User Needs.WebHome]] - Detailed user need definitions
--* [[Requirements>>Archive.FactHarbor 2026\.02\.08.Specification.Requirements.WebHome]] - How user needs map to requirements
++* [[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]] - Detailed user need definitions
++* [[Requirements>>FactHarbor.Specification.Requirements.WebHome]] - How user needs map to requirements
  * [[Partnership Strategy>>FactHarbor.Organisation.Partnership-Strategy]] - Partnership opportunity details
  * [[Funding & Partnerships>>FactHarbor.Organisation.Funding-Partnerships]] - Funding sources and contacts
  * [[Organisational Model>>FactHarbor.Organisation.Organisational-Model]] - How FactHarbor is structured
++

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