Multi world testing in retailUsing machine learning to find the perfect offer

When personalizing marketing there’s a huge number of variables to consider.

Information collected from mobile and connected devices lets us adapt messaging to context.

We can A/B test options until enough people choose one over the other.

Then there’s multi world testing. Think of it as a multi armed bandit problem:

When we’re in a casino we want to play the slot machine that will give us the most money. The only way to find that machine is to play all of them.

Our strategy should balance playing the machine with the best pay out, and testing to see if there’s any better.

If we connect context and results, knowing the context will tell us the best machine to play.

Ultimately, our goal is to play the best machine as often as possible.

In retail terms, which offer should we send in order to maximize our return in different contexts?

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