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I think the opposite: there is not much valuable data, it is just noise.

It is very difficult to go from what users browse to what they actually buy. People very often say one thing, then do something completely different.

And sometimes they browse stuff just to make sure that their current decision is correct, so they will look at a lot of items they're not going to buy.

(oh, and everybody and their mother knows photos are important. No need for ML to find that out)



Do you think that A/B or multi-variate testing works in general?


In some cases A/B testing works very well and in other cases not at all.

So it is easy to test UI changes, but difficult to find out why people do what the do.




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