In this final episode with Ryan Scott from DNA Behavior, we explore the ethical boundaries of AI personalization, data ownership rights, Gene AI's revolutionary hiring capabilities, and the future of democratized executive coaching through artificial intelligence.

Keywords

Ryan Scott, DNA Behavior, Gene AI, AI Ethics, Data Ownership, Executive Coaching, Behavioral AI, Privacy Rights, Microsoft AI Standards, DISC Migration, AI Coaching, Hiring Intelligence, Interview Questions

Key Takeaways

When NOT to Use Personalization

- Avoid personalization where "telephone game" can occur

- Emergency communications (fire drills, safety instructions) should remain consistent

- Large office-wide messages need uniform clarity to prevent confusion and mistrust

- Best for one-on-one sales/marketing interactions, not group communications

Microsoft's AI Ethics Framework

- Fair, reliable, and safe implementation

- Privacy and security protections built-in

- Inclusive and transparent processes

- Company accountability for adherence to standards

- Leading enterprise AI adoption methodology

Revolutionary Data Ownership Model

- Individual owns their behavioral insights, not the company or coach

- Users can opt-out of data sharing with other companies anytime

- Complete control over data access and permissions

- Fundamental shift from traditional B2B2B model ownership

Gene AI Capabilities

- Natural language interface for all DNA Behavior insights

- Automates complex hiring processes previously requiring certification

- Creates hiring benchmarks for specific roles (civil engineer example)

- Generates behavioral interview questions based on candidate strengths

- Identifies outlier behaviors that matter most for coaching focus

Hiring Process Revolution

- Input: 100 job applicants

- Gene AI ranks candidates against rockstar benchmarks

- Shortlist top 5 candidates automatically

- Generate personalized behavioral interview questions

- Focus on strengths AND potential struggles for each candidate

DISC Migration Strategy

- 50% discount for DISC coaches switching to DNA Behavior

- More competitive pricing than traditional DISC

- AI translator converts DNA insights into familiar DISC language

- Reduces switching costs by maintaining familiar terminology

- Additional insights beyond standard DISC offerings

AI Coaching Preparation Notes

- Focuses on outlier behaviors rather than typical patterns

- Provides speaking notes for coaches and consultants

- Speeds up facilitation by highlighting what matters most

- Eliminates manual reading on small screens

- Enables coaches to focus on high-value work

The Future of AI Coaching

- Democratizing executive coaching beyond C-suite access

- $500+ per hour coaching expertise available to middle managers and manufacturing workers

- Real-time, secure AI coaching conversations

- Video AI coaching interfaces

- Scaling behavioral intelligence across entire organizations

The 60% Mismatch Reality

Ryan's key insight: "If you were to be matched with anybody in the world, there's about a 60% likelihood that you two will be a mismatch."

The solution isn't necessarily technology - it's adapting personal communication styles to work better with others.

Big Data Organizational Intelligence

- Advanced number crunching capabilities

- Organizational-level behavioral insights

- Enterprise-wide pattern recognition

- Scaling individual insights to company-wide intelligence

Implementation Resources

- DNA Behavior website: dnabehavior.com/start

- Dedicated page for podcast listeners and event attendees

- Video tutorials and trial access

- Self-guided navigation options

This episode demonstrates how AI can democratize expertise while maintaining ethical standards and individual data rights, transforming both hiring processes and ongoing professional development across organizations.

Links

https://dnabehavior.com/

In this episode, we continue our conversation with Ryan Scott from DNA Behavior, exploring AI development processes, revolutionary conference experiences with behavioral intelligence, and practical marketing personalization strategies using HubSpot's smart content features.

Keywords

Ryan Scott, DNA Behavior, Conference Networking, HubSpot Smart Content, Behavioral Personalization, N8N Development, Digital Scan, Event Technology, Marketing Automation, Content Personalization, Behavioral Intelligence

Key Takeaways

AI Development Process Framework

- Start with Excel to understand calculations and insights

- Focus on one process per worksheet (agentic AI approach)

- Keep data small initially (tested with 100 people vs. 3.5 million)

- Use N8N for R&D and local agentic solutions

- Export code or hand off to developers for custom implementation

The "Onion Model" for Simplification

- Take charge

- Outgoing

- Patient

- Planned

Revolutionary Conference Experience

- Colored lanyards (blue, green, black, gold) based on behavioral personas

- Natural networking through behavioral compatibility

- Currently implemented with Better Business Bureaus and Chambers of Commerce

- Summer enterprise conferences planned

Three-stakeholder event value

- Attendees: Better networking with behaviorally compatible people

- Event organizers: Curate content based on audience personas (data-driven vs. energetic presentations)

- Sponsors: Understand how to communicate with leads based on behavioral data

HubSpot Smart Content Integration

- Moved from Salesforce to HubSpot specifically for smart content features

- Uses HubSpot's native rules-based content swapping

- Personalizes emails, web pages, blogs, videos, and infographics

- DNA provides behavioral persona data, HubSpot handles the technology

Content Personalization Strategy

- Outgoing personas: Bright colors, energetic content

- Analytical personas: Facts, background knowledge, detailed science

- Patient personas: Lifestyle-focused infographics

- Take-charge personas: Bulleted lists with direct facts

Implementation Best Practices

- Create four content flavors instead of 4,000 variations

- Always include a fallback option for adaptive clients

- Import contact lists for quick persona analysis

- Don't overcomplicate the personalization process

- Focus on broad reach with personalized touches

HubSpot's 2025 Marketing Recommendation

- Every firm should analyze behavioral personas of their customer base as a key marketing strategy for 2025

Technical Tools Mentioned

- Excel: Initial calculations and workflow mapping

- N8N: R&D and local agentic solution development

- HubSpot Marketing Hub: Smart content and rules-based personalization

- DNA Behavior Digital Scan: Instant behavioral analysis without questionnaires

This episode demonstrates how behavioral intelligence can transform both event experiences and marketing personalization, making AI-powered customization accessible through existing marketing platforms.

Links

https://dnabehavior.com/

In this episode, we explore the intersection of AI and behavioral science with Ryan Scott, Head of Product at DNA Behavior, who has transformed traditional personality testing into an AI-powered behavioral intelligence platform over his 15-year journey with the company.

Keywords

Ryan Scott, DNA Behavior, Behavioral Intelligence, AI Personality Testing, Digital Scan, DISC Alternative, Myers-Briggs, Machine Learning, Behavioral Prediction, Enterprise Psychology, Workplace Analytics, Custom GPTs

Key Takeaways

DNA Behavior's Evolution Journey

- Started with faxed PDF questionnaires requiring manual data entry by interns

- Four major iterations over 15 years: workplace talent → financial insights → combined platform → AI-driven enterprise solution

- Founded in Australia, moved to Atlanta for Georgia Tech research partnerships

- Differentiated by making behavioral insights actionable through dashboards vs. static PDF reports

The Traditional Assessment Problem

Traditional personality tests (DISC, Myers-Briggs, Enneagram) follow a broken model:

- 60-90 minute questionnaires that produce PDF reports

- Reports "die in a dust drawer" and aren't used day-to-day

- No integration with business systems or decision-making processes

- High switching costs for organizations with existing assessment data

Digital Scan AI Innovation

DNA Behavior's breakthrough solution predicts behavioral insights using only:

- Person's name and job title

- Company information and background data

- No questionnaire required

Training data foundation:

- 3.5 million behavioral questionnaire responses

- 3.25 million people across 4,000 behavioral insights

- Backwards compatible with 15 years of historical data

- Machine learning algorithm predicts same insights as traditional assessments

AI Implementation Cost Savings

Ryan's practical tips for reducing LLM costs:

- Clean and standardize data locally before cloud processing

- Use local LLAMA models for initial data processing

- Convert to CSV format before uploading to cloud services

- Use custom ChatGPTs for R&D before paying for APIs

- Structure responses as JSON instead of unstructured text (reduces hallucinations)

- Process only necessary data rather than scanning entire documents

Organizational AI Adoption

- Required making "hard decisions" about team members resistant to change

- Used behavioral insights to identify team members suited for fast-paced innovation

- Some people "weren't really suited for the fast-paced innovation that AI brings"

- Essential to choose adaptable people for AI transformation success

Business Model Innovation

B2B2B structure with coaches/consultants as intermediaries:

- Reduces switching costs by importing existing DISC/Myers-Briggs reports

- AI translator contextualizes insights in familiar assessment languages

- No retraining required for managers familiar with other systems

- Seamless comparison between AI-scanned and traditionally assessed individuals

Market Differentiation Strategy

- Contextualized insights for specific use cases (financial decisions, relationships, management)

- Enterprise-grade platform vs. individual assessment tools

- Big data approach with millions of behavioral data points

- Focus on actionable intelligence rather than static reports

This episode demonstrates how AI can revolutionize traditional industries by solving fundamental usability problems while maintaining compatibility with existing systems and knowledge.

Links

https://dnabehavior.com/