Ideal Customer Profile

This page defines FactHarbor's ideal customer segments and partner profiles to guide product development, marketing, and partnership strategy.

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
• Resource Allocation: Focus limited resources on highest-impact activities

Philosophy: FactHarbor serves users who want to understand, not just believe. Our ideal customers share a frustration with binary "true/false" verdicts and value transparent reasoning they can inspect.

2. Primary User Segments

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
• 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
• Binary fact-check verdicts lack nuance for complex stories

Value Proposition:
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

2.2 Researchers & Academics

Profile:

• University researchers (political science, communications, media studies)
• Think tank analysts
• PhD students studying misinformation
• 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
• UN-15: Verdict evolution timeline (how assessments change with new evidence)

Key Pain Points:

• Existing fact-checks are methodologically opaque
• Need structured data for quantitative analysis
• Difficulty comparing how claims are assessed across sources
• Binary verdicts hide important uncertainty

Value Proposition:
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

2.3 Educators

Profile:

• University professors (media literacy, critical thinking, journalism)
• High school teachers (civics, social studies, media studies)
• Librarians and information literacy specialists
• 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
• 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
• Limited resources for curriculum development

Value Proposition:
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

2.4 Policy Analysts

Profile:

• Government policy advisors
• NGO research staff
• Legislative aides
• 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
• 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
• Risk of appearing biased when presenting controversial topics

Value Proposition:
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

2.5 Content Consumers (General Public)

Profile:

• Social media users seeking to verify viral claims
• Engaged citizens following news and politics
• People making decisions based on contested information
• 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
• 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
• Frustrated by partisan accusations about fact-checkers

Value Proposition:
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
• User satisfaction with transparency

3. B2B Partner Segments

3.1 Media Organizations

Priority: HIGH (Tier 1)

Target Partners:

• Swiss Broadcasting (SRG SSR, SRF, RTS, RSI)
• Major newspapers (Tamedia, NZZ)
• Regional news organizations
• 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
• Pilot programs for election coverage

3.2 Fact-Checking Organizations

Priority: HIGH (Tier 1)

Target Partners:

• IFCN (International Fact-Checking Network) members
• EFCSN (European Fact-Checking Standards Network) members
• dpa Fact-Checking (DACH region)
• Correctiv (Germany)
• Full Fact (UK)

Partnership Value:

• For Partners: Technology platform, scalability, methodology alignment
• For FactHarbor: Credibility, network access, ecosystem integration

Engagement Model:

• Open-source technology sharing
• ClaimReview schema collaboration
• Joint methodology development
• Cross-referencing and data sharing

3.3 Academic Institutions

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)
• Stanford Internet Observatory (misinformation research)
• 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:

• Research partnerships
• Student thesis projects
• Co-authored publications
• Conference presentations
• Joint grant applications

3.4 Funding Organizations

Priority: MEDIUM (Tier 2)

Target Partners:

• Knight Foundation (journalism innovation)
• Google News Initiative (fact-checking fund)
• Swiss Innosuisse (research/innovation grants)
• Gebert Rüf Foundation (Swiss innovation)
• Prototype Fund Switzerland

Partnership Value:

• For Partners: Support innovative, transparent approach to misinformation
• For FactHarbor: Operational funding, validation, network access

Engagement Model:

• Grant applications
• Progress reporting
• Impact documentation
• Network participation

4. Common Customer Characteristics

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
• Inability to see evidence and reasoning process
• No way to understand why experts disagree

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
• Integrity: Non-profit, open-source, no hidden agenda
• Accessibility: Understanding without specialized expertise

4.3 Decision Criteria

When evaluating fact-checking tools, ideal customers prioritize:

1. Methodology Transparency: Can I see how conclusions are reached?
   2. Evidence Quality: Are sources traceable and credible?
   3. Nuance Handling: Does it acknowledge complexity?
   4. Speed & Usability: Can I use it in my workflow?
   5. Trust & Independence: Is there hidden bias or agenda?

5. Customer Journey

5.1 Awareness

How they find us:

• Academic publications citing FactHarbor
• Referrals from fact-checking organizations
• Search engine results (ClaimReview schema visibility)
• Media coverage of misinformation topics
• Social media discussions about fact-checking

5.2 Evaluation

What they assess:

• Methodology documentation (open and detailed?)
• Sample analyses (quality and transparency?)
• Open-source code (auditable?)
• Non-profit status (trustworthy?)
• User experience (usable?)

5.3 Adoption

How they start:

• Submit a claim they're curious about
• Explore an existing analysis in depth
• Review methodology documentation
• Test with a known case to validate quality
• Integrate API into existing workflow

5.4 Retention

Why they return:

• Consistent quality and transparency
• Time savings in verification workflow
• Unique value (scenario analysis not available elsewhere)
• Trust in methodology
• Community participation

6. Anti-Personas (Not Our Target)

6.1 Confirmation Seekers

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:

• Don't compromise methodology to satisfy them
• The transparency may eventually convert some

6.2 Speed-Only Users

Profile: Users who only want instant answers, no interest in evidence

Why Not Ideal:

• 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:

• Provide quick summary views (UN-1: trust at a glance)
• Make deeper exploration available but not required

6.3 Bad-Faith Actors

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

7. Metrics and Validation

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?
• Retention: Do they return?
• Referral: Do they recommend others?

7.2 Segment-Specific Success Indicators

7.3 Partnership Metrics

8. Related Pages

• User Needs - Detailed user need definitions
• Requirements - How user needs map to requirements
• Partnership Strategy - Partnership opportunity details
• Funding & Partnerships - Funding sources and contacts
• Organisational Model - How FactHarbor is structured