Question 1

How do you measure quality in healthcare data?

Accepted Answer

_Quality metrics for healthcare ML._

> Knowing quality is therefore of utmost importance. Three broad measurement areas in today's healthcare: (1) Metrics about quality of care — related to treatment effectiveness and patient satisfaction. (2) Metrics about need and utilization of care — gauging health requirements of a population and how often one uses what type of service. (3) Metrics about value-based healthcare — they measure disease prevention rather than disease…

— [Healthcare And Data - How To Measure Quality](https://www.forbes.com/sites/lutzfinger/2023/06/27/healthcare-and-datahow-to-measure-quality/) · _Forbes_

Question 2

What is the 'Ask, Measure, Learn' framework?

Accepted Answer

_The framework from Lutz's book._

> "Ask Measure Learn" is a non-technical guide shows you how to extract significant business value from big data. It is a system that helps you ask the right questions, measure the right data, and then learn from the results. The framework was originally devised to help governments and NGOs sift through volumes of data.

— [Ask Measure Learn](https://www.lutzfinger.com/book/) · _Book — Ask, Measure, Learn_

Question 3

What is the book Ask, Measure, Learn about?

Accepted Answer

_Topics covered in the O'Reilly book._

> **Publisher:** O'Reilly Media **Published:** Feb 1, 2014

— [Ask Measure Learn](https://www.lutzfinger.com/book/) · _Book — Ask, Measure, Learn_

Question 4

What is the difference between virality and contagiousness?

Accepted Answer

_Stories gain weight as they travel, not uniform infection rates._

Virality is something which is equally infectious at each stage. If I have a story which one out of 10 people like, that story doesn't change. One out of 10 people like it in the future as well. Contagiousness is different. As long as it travels, it gains weight. The more people believe in it, the more trustworthy the story becomes. Even a wrong information becomes more believed the longer it travels. At some point everyone believes it's truth no matter what because so many people believed in it. Forget about virality. The right word is contagiousness.

— [Measuring Social Media What Marketers Need To Know](https://www.lutzfinger.com/transcript/2014-08-22-measuring-social-media-what-marketers-need-to-know/) · _Social Media Examiner_

Question 5

What is value-based care and how does AI enable it?

Accepted Answer

_VBC framing and AI's role._

> Healthcare is on the brink of a seismic shift, and AI is its catalyst. Three converging trends are creating a perfect opportunity for change: (1) Foundational Models' growing ability to predict risks further into the future compared to traditional machine learning, (2) the rise of the self-insured healthcare industry motivated to address these risks, and (3) a surge in Value-Based Care (VBC) providers focused on risk reduction. These…

— [Three Trends Of Transformation: How AI & Value-Based Care (VBC) Will Drive Transformation Of Self-Insured Healthcare](https://www.forbes.com/sites/lutzfinger/2023/05/01/three-trends-of-transformation-how-ai--value-based-care-vbc-will-drive-transformation-of-self-insured-healthcare/) · _Forbes_

Question 6

Why do LLMs convert better than search?

Accepted Answer

_Trust, personalization, and conversion lift from AI traffic._

> Some predict that by 2028, more people will discover products and information through large language models (LLMs) like ChatGPT and Gemini than through traditional search engines. But based on research I conducted with Cornell Master's students, that shift is happening much faster. LLM-driven traffic is already starting to outperform traditional search — not in volume, but in value.

— [Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming](https://www.forbes.com/sites/lutzfinger/2025/06/19/study-shows-llm-conversion-rate-is-9x-better---aeo-is-coming/) · _Forbes_

Question 7

Why is eval data a moat?

Accepted Answer

_Evaluation data as the strategic differentiator._

> All of them matter, and all of them are being fought over. But the real value may sit in the one thing OpenAI, Anthropic, and Gemini have not yet made central: your own eval data. Sure, there is the occasional thumbs-up button. But who is really using that signal?

— [The Missing Moat In AI: Your Eval Data](https://www.forbes.com/sites/lutzfinger/2026/05/26/the-missing-moat-in-ai-your-eval-data/) · _Forbes_

Question 8

Why is measuring social media so difficult despite all the tools available today?

Accepted Answer

_Tools are everywhere, but strategy comes first, not scores._

The problem is that measurement used to require specialists with big databases and tooling. Now with social media, you suddenly have all these tools that give you cloud scores and metrics instantly. People see a score and decide something based on it without planning what they actually want to achieve. If you haven't formulated your business goal first, any measurement won't work. People start with the measurement and then think about what to do with it, while the correct way is the opposite: start with a question, then come up with a measure.