AI Insights: Uncovering Customer Value

Do you know what people really think about your business? Wondering how AI can help you determine your real value so you can stand out in a noisy marketplace?

In this article, you'll discover how AI can help you make data-driven marketing decisions that resonate with your audience.

A Compassionate Approach to AI Adoption

Liza Adams has worked in AI for about ten years, though not solely in generative AI. Her work began in predictive analytics and machine learning when AI was less prominent. Her journey to working with AI has an interesting backstory. 

She's been based in Boulder, Colorado, for 20 years but spent half of her career in Silicon Valley. During this time, she worked for several large Silicon Valley companies, including Brocade (now part of Broadcom), Pure Storage, and Juniper Networks (now part of HP). She also worked for Smartsheet in the Seattle area.

Her last corporate role, which she thought would be her final role, was with a Colorado-based company specializing in CRM, ERP, and SaaS solutions for the beverage alcohol supply chain. She loved the business and planned to stay for five years. However, the company was acquired, and her exit happened just a year and a half into her tenure.

This unexpected change led her to consider serving on boards, as she’s passionate about increasing the representation of marketers, women, and women of color in board positions. 

Her research revealed that only 41 marketers serve on Fortune 1,000 boards and less than 3% of board members, regardless of company size, have marketing experience. When she investigated further, she discovered marketers are often viewed as tacticians rather than strategists.

Many people tend to focus on the visible aspects of marketing – ads, social media, websites, events, campaigns, and emails. However, they often overlook our strategic work in go-to-market strategy, ensuring product-market fit, developing segmentation and positioning strategies, understanding markets deeply, and creating category leadership. This high-level strategic work is crucial for developing effective market campaigns.

She made it her personal mission to work with other like-minded individuals to elevate the strategic value of marketing. 

This mission coincided with the launch of ChatGPT in November 2022. 

While others initially saw it as a tool for creating blogs, summarizing reports, or helping with emails, Liza recognized its broader potential. She envisioned using it for thought leadership, as a thought partner, for analytics and research to inform insights and decision-making, automation, personalization, and strategic content creation. Liza believes this technology represents a gift—an opportunity to flip traditional thinking.

By infusing our work with AI, we can become more strategic. Previously, companies lacked the patience to conduct deep market inspections, research, surveys, and strategy development. AI has compressed these timeframes, allowing us to analyze vast amounts of data and generate unique insights much more efficiently.

Adams emphasizes the importance of meeting people where they are in their AI journey. 

“We have to be graceful and respectful of where everybody is in their AI journey,” she insists. “Because I happen to be passionate about something, and I happen to do it for a living… I live and breathe AI almost every day. But not everybody has the same passion. Not everybody has the same time. Not everybody has the same access to AI.”

This perspective shapes her approach to AI literacy. 

She believes understanding AI is crucial for business success and making informed decisions about ourselves, our families, our careers, and society as a whole. 

Rather than being influenced by others who may not share our values, she advocates for developing personal AI literacy at whatever pace works for each individual.

Adams uses a compelling metaphor to describe the ideal relationship between humans and AI, comparing it to the Justice League.

“Humans, we cannot remember things… I don't remember what I did yesterday. I can't process a lot of data, but AI can,” she explains. “However, the flip is AI cannot adapt easily. It doesn't have an emotional response.”

This complementary relationship forms the foundation of her effective AI strategy. 

Humans bring emotional intelligence, adaptability, and creative thinking, while AI contributes data processing power and pattern recognition. 

Together, they overcome each other's limitations to achieve better results than they could alone.

The Strategic Value Framework: How to Use AI to Analyze Product-to-Market Fit Through Value & Defensibility

Adams' framework emerged from decades of experience across multiple technological transformations, from the internet and cloud computing through mobile, social media, and now AI. This framework has proven its durability through these technological inflection points, making it particularly valuable for navigating the current AI revolution.

NOTE: This framework requires data collection, formatting, and anonymization. Scroll to the end of the article for a comprehensive approach that protects your company and customers from having proprietary and personal information leaked into an AI learning machine.

#1: Use AI to Establish Your Value Dimension

You can't out-campaign a bad product-to-market fit. If you don't have a good product-to-market fit and infuse AI into your campaigns, you'll end up with something similar to executing an all-out campaign for snowblowers in Florida. You will have essentially amplified a path to campaign failure.

This is where the value dimension that establishes your product-to-market fit comes into play.

The value dimension examines how an organization's offerings compare to competitors. Adams breaks this analysis down into measurable components rather than relying on gut feelings. The scale includes three distinct levels.

1. Base Level: You provide the same value as your competitors.
2. Middle Tier: You are delivering incremental improvements.
3. Top Tier: You offer order-of-magnitude improvements in price, unmet needs, scalability, and business transformation potential.

To understand which of these tiers your business occupies, you must define clear parameters for value based on differentiators such as:

• Price competitiveness
• Ability to meet unmet market needs
• Scaling capabilities
• Business transformation potential
• Market-specific metrics
• Customer service

The key is to uncover what your customers and target audience truly see as valuable by gathering customer data and pasting it into a spreadsheet or another format so that your AI can work with it: 

• Customer reviews from online platforms like Amazon Reviews, Google Reviews, Facebook, and Gartner Peer Insights
• Customer surveys or interviews
• Slack conversations
• Excel spreadsheets
• HubSpot records
• Email communications
• Sales transcripts

This will take time–often two to three weeks, but the result will be a customer-supported value proposition.

When your data is collected, anonymized, and formatted, you can upload it and ask your AI to begin analyzing it based on a dimension such as customer sentiment.

Look at these reviews and identify the customers who have commented on customer service.

When the AI has segmented that pool of customers, you can prompt:

Based on this segment of comments, infer customer sentiment on a scale of 1 (highly dissatisfied) to 5 (extremely satisfied).

Pro Tip: Run the same data collection and analysis for your competitors so you can benchmark effectively.

#2: Use AI to Establish Your Defensibility Dimension

The defensibility dimension assesses how difficult it would be for competitors to replicate your competitive advantages. Think of these competitive advantages as a moat protecting your business.

The defensibility scale includes three levels:

1. Easy to Copy: Features that competitors could replicate in their next release
2. Moderate Difficulty: Features that competitors could replicate with significant investment
3. Hard to Copy: Features that would require competitors to invest in extraordinary resources or potential acquisition of your company

To find a genuinely sustainable competitive position, you'll need to look beyond technological advantages and consider details such as:

• Product ingredients or specs
• Partner ecosystems
• Deep vertical industry expertise
• Unique customer knowledge
• Brand strength
• Distribution channels
• Location advantages
• Proprietary recipes, data, or processes

You'll need a weighted scoring system to evaluate your defensive advantages and prioritize investments in strengthening your competitive position. For example, a food business might weight its defensive moats as:

• Ingredients: 50%
• Recipe: 40%
• Location: 10%

Pro Tip: The defensibility dimension has become particularly crucial in the AI era because many companies are building solutions on top of existing large language models from OpenAI, Google, or Meta, raising questions about how defensible AI-based advantages really are.

The Competitive Defensibility Analyzer: A Custom GPT SolutionAdams has developed a free custom GPT called the Competitive Defensibility Analyzer to guide you through a systematic competitive defensibility evaluation process.

In the initial assessment phase, the tool:

• Identifies potential defensive moats
• Evaluates the strength of current positions
• Compares against competitor capabilities
• Suggests improvement opportunities

In the weighted analysis phase, the tool helps organizations:

• Weight the importance of different defensive elements
• Calculate overall defensibility scores
• Compare positions across market segments
• Identify strategic priorities

Once the data is prepared, the analysis typically takes about thirty minutes, providing a starting point for deeper strategic discussions with leadership teams.

#3: Use Value and Defensibility Analysis to Guide Strategic Decision Making

What if you discover you need a better product-to-market fit? Or your positioning isn't as defensible as you thought it was? 

Using AI with the Thorn Bud Rose framework helps you evaluate opportunities systematically:

1. Roses: Current strengths and positive aspects
2. Thorns: Challenges and potential obstacles
3. Buds: Opportunities for future growth

Please review our value and defensibility dimensions, then give me an analysis based on the Thorn Bud Rose framework to help me find opportunities we have yet to consider. 
1. Roses: Show me current strengths and positive aspects
2. Thorns: Show me challenges and potential obstacles
3. Buds: Show me opportunities for future growth

Adams recommends using AI to apply this framework consistently across different market segments or strategic options, providing comparable analyses that support decision-making.

Tips for Data Preparation and Analysis

The foundation of effective AI-driven strategy lies in proper data preparation. This process involves a comprehensive approach to data preparation.

Data Structuring

You'll need a system to govern data entry and optimize your data for more accessible AI analysis.

Create consistent data storage formats, develop standardized taxonomies, and establish clear categories that work for everyone.

Data Collection from Multiple Sources

During the collection phase, gather data from all relevant sources to ensure comprehensive coverage.

• Slack conversations
• Excel spreadsheets
• HubSpot records
• Email communications
• Customer interviews
• Sales transcripts

As you transfer your data, document the data origins, metadata, and context to maintain the data's integrity.

Data Protection and Anonymization

Adams shares an innovative approach to protecting sensitive data while maintaining analytical value – the zoo metaphor.

“I keep telling people that AI probably thinks I own a zoo because I always give it context, such as this is a zoo. The data I'm giving you is based on the most popular cages in the zoo” versus “This is my market size, and these are the penetration rates by segment.”

This creative approach allows organizations to work with sensitive data while maintaining confidentiality. For example:

• Company names become generic identifiers (e.g., “Yourt” becomes “Acme”)
• Market segments become “exhibits”
• Customer populations become “visitor statistics”
• Revenue becomes “attendance figures”

Other Notes From This Episode

• Connect with Michael Stelzner @Stelzner on Facebook and @Mike_Stelzner on X.
• Watch this interview and other exclusive content from Social Media Examiner on YouTube.

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