What We Still Need To Learn About AI In Marketing.

πŸ” Here are the key takeaways and insights from podcast episode of HBR IdeaCast

M W Khan
2 min readSep 8, 2021
Photo by Stephen Phillips - Hostreviews.co.uk on Unsplash

πŸ” Introduction

  • The promise of AI is to make decisions.
  • For marketing, companies look for profitable use cases of the technology.
  • If not implemented rightly, the use of AI may cause loss to a business.

πŸ” AI and Marketing

  • Many leaders are leaning towards AI for their marketing strategy without getting to know it.
  • The simple use of AI in marketing is to use consumers data and do some forecasting.
  • The sophisticated use of AI is to build real-time pricing models like Uber.
  • They collect real-time data, analyze it, and make a decision that’s optimal for them.

πŸ” Misalignment Problem

  • To leverage the value of an AI, the prediction must be aligned with the decision the company would make in the end.
  • The data science team will build a system that can predict customer churn.
  • Whereas the marketing team wants to know what offers may persuade these customers to stay.

πŸ” The Street Light Effect

  • The AI team is more gravitate towards predicting the behavior.
  • The marketing team wants to decide to change that behavior.
  • The miscommunication between both teams is causing this misalignment problem.
  • AI is not causing the problem, but it is a sort of enabler.

πŸ” Decision under Uncertainty

  • Companies use AI to predict the unknowns that have uncertainties.
  • Companies have to understand the cost of a decision made using those uncertainties and integrate those accordingly.

πŸ” What Companies Need To Do

β€œThe data science team did not even know how their predictions had been used.”

  • 3 step framework to help companies make better decisions using AI:
  1. The data science team and marketing team must work together and try to understand what problem they are trying to solve.
  2. Identify the wrong questions and replace those with the right questions to be asked from data.
  3. Analyze the data to answer those questions.
  • Understand that the predictions of the AI model deviate from our real world. And how this deviation can cost a company in terms of money.

β€œCompute the cost of doing one thing wrong to the cost of doing other thing wrong.”

πŸ” Humanly Problems

  • Humans do what they know how to do. The Street Light Effect
  • Humans are reluctant to change.
  • Humans are not good at showing what they don’t know.
  • A good mindset is to improve by doing iterations, do not aim for perfection.

Listen to the whole episode here.

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M W Khan

I am here to write about things I find interesting while listening to Podcasts and reading Articles and Books.