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

How do you spot social media bots?

Accepted Answer

_Detection heuristics._

> Figure 6-4. Subset of a social network, created using LinkedIn Labs Since bot networks will first create their own group by linking to one another before they start to infiltrate the rest of the network, especially in the beginning, you will see a highly dense network with very low cohesion to the rest of the network. However, those measures using network topology only work in the beginning as the bot network is formed. Once the bots…

— [Finger Dutta Ask Measure Learn (1)](https://www.lutzfinger.com/book/) · _Book — Ask, Measure, Learn_

Question 3

What is a data product?

Accepted Answer

_Definition and how to build one._

> Now, to be a good product developer, you need to think about self-referential loops within your products. How to get signal, how to get feedback from your users so your AI, or your data science, can leverage that information to make the product work better. So that moved a little bit within it. The innovation, and the inspiration about, and the curiosity about how to use data in novel manners, that's still data science, because that's…

— [Unit 3 Full Transcript](https://www.lutzfinger.com/ecornell/) · _eCornell course_

Question 4

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 5

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 6

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 7

What was Ultimate AI's key insight that made customer onboarding faster than competitors?

Accepted Answer

_Automated clustering replaced manual training data creation for faster setup_

We couldn't afford AI trainers manually creating training data, so we built a clustering pipeline that analyzed historical customer conversations already sitting in CRMs like Salesforce. This let us automatically find the 100 or 200 most common questions and show customers all 30,000 actual ways users asked questions like where's my order. Competitors were using FAQ pages and having people manually write 50 to 100 variations, which didn't reflect real customer language. Our approach gave faster time to value because we used actual conversation data instead of imagined variations, and customers could see their real top questions before even talking to us.

— [How Ultimate evolved from hundreds of supervised models to UltimateGPT](https://www.lutzfinger.com/transcript/2023-05-12-how-ultimate-evolved-from-hundreds-of-supervised-models-to-ultimategpt/) · _The Edge_

Question 8

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 9

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.