The 36 Days Customer LOVE Challenge!

The 36 Days Customer LOVE Challenge!

It is all about how you make your customers fall in LOVE with you…(and your brand 😉). I will not provide recipes because there are no templates for YOUR customer’s success.

Instead, I will inspire. The inspiration that will lead you to think how important it is to listen, to understand, to read between the lines, to draw the right conclusions, and to be able to act on it.

This challenge takes 36 business days – Monday to Friday.

Why 36?

Professor Arthur Aron of the University of New York conducted experience where two strangers ask each other 36 predefined questions. After the study, an unexpectedly large amount of participants became couples and married. Statistically, the method dramatically increases the likelihood of falling in love.

In this challenge, I will make you fall in love with me and my mission: The mission to free business decision making from the curse of spurious correlations and false assumptions, from correlation-prone fact-based management and blind hypothesis-driven analytics.

In this, I will answer the 36 questions, and I will encourage you to do the same (in metaphoric terms) to do the same with your customers.

Are you in?

Frank

p.s. you want to learn more about my mission?

…and the mission of the whole Success Drivers Group? Ok, then follow me:

The core of the issue is a simplistic understanding of fact-based management. This understanding is taught in business schools today. “What you can measure you can manage” is a big misunderstanding. Sure, without data, no managed improvement possible. But data alone is just noise. Jumping from data to conclusions is similarly effective as management by gut-feeling.

Why? Because correlation is not causation. Even comparing two KPIs is also a kind of correlation analysis. But this is 99% of fact-based decision making is built on.

The way we make a decision based on data must be set from head to its feet. We need to acknowledge what we need to make decisions: EVERY decision is based on causal assumptions. “If I do X, then Y will happen”. What we need to make a better decision is NOT better data. It actually can not be even measured. It is hidden BEHIND data.

That’s why its crystal clear what we need: a practical and actionable causal analysis framework. Conventional statistics do not provide a toolset that has the properties businesses need in many ways. This is why we developed a causal analysis methodology based on machine learning (Causal-AI).

Amazing case studies like this from T-Mobile are the best proof for its vast power. Who wouldn’t want to double the revenue at record profits enabled by a simple AI-powered insight?

The Next-Level are AI-Solutions Not Just Tools.

The next level, however, are our latest efforts to package the technology into ready-to-use solution bundles.

CX.AI ends the widespread wastage of customer feedback data. It’s AI codes text like a human and then uncovers CX drivers like a “genius”.

CX.AI leverages data that every enterprise already has. It helps to make fast, impactful business decisions. In an easy, simplified process, all analysis results are accessibly in an interactive dashboard.

The 36 Days Customer LOVE Challenge!

It is all about how you make your customers fall in LOVE with you…(and your brand 😉). I will not provide recipes because there are no templates for YOUR customer’s success.

Instead, I will inspire. The inspiration that will lead you to think how important it is to listen, to understand, to read between the lines, to draw the right conclusions, and to be able to act on it.

In this challenge, I will make you fall in love with me and my mission: The mission to free business decision making from the curse of spurious correlations and false assumptions, from correlation-prone fact-based management and blind hypothesis-driven analytics.

Do you want to learn more about my mission?

The core of the issue is a simplistic understanding of fact-based management. This understanding is taught in business schools today. “What you can measure you can manage” is a big misunderstanding. Sure, without data, no managed improvement possible. But data alone is just noise. Jumping from data to conclusions is similarly effective as management by gut-feeling.

Why? Because correlation is not causation. Even comparing two KPIs is also a kind of correlation analysis. But this is 99% of fact-based decision making is built on.

The way we make a decision based on data must be set from head to its feet. We need to acknowledge what we need to make decisions: EVERY decision is based on causal assumptions. “If I do X, then Y will happen”. What we need to make a better decision is NOT better data. It actually can not be even measured. It is hidden BEHIND data.

That’s why its crystal clear what we need: a practical and actionable causal analysis framework. Conventional statistics do not provide a toolset that has the properties businesses need in many ways. This is why we developed a causal analysis methodology based on machine learning (Causal-AI).

Amazing case studies like this from T-Mobile are the best proof for its vast power. Who wouldn’t want to double the revenue at record profits enabled by a simple AI-powered insight?

The Next-Level are AI-Solutions Not Just Tools.

The next level, however, are our latest efforts to package the technology into ready-to-use solution bundles.

CX.AI ends the widespread wastage of customer feedback data. It’s AI codes text like a human and then uncovers CX drivers like a “genius”.

CX.AI leverages data that every enterprise already has. It helps to make fast, impactful business decisions. In an easy, simplified process, all analysis results are accessibly in an interactive dashboard.