[nilirl]

I have a few dumb questions for people who really understand how this stuff works:

- Is prediction based on historic transaction and sales data effective? I always assumed transaction and sales data in isolation didn't contain enough information to be effective predictors of buying behavior. Is that wrong?

- How much more effective is it than a human intuitively setting a discount? I can see large retailers saving time on having to set discounts for a large number of products. Just wondering if small merchants would just be better off doing it themselves.

[pmoot]

1) What we're really doing with this first product is predicting how price impacts conversion rate. That's been a relatively simple thing to measure in my experiences. It's more difficult to do things like predict a customer's probability of buying based on their order history.

2) Yes so we don't have a case study comparing us to manually setting discounts, but the task gets pretty time consuming quickly if you want to update the discount daily (or more frequently) and personalize the discount (which is one of the features we're planning on adding).

[altdataseller]

Re: small merchants. Thats what I dont get. The companies that need this are the big ones not the small merchants with relatively few products they wish to discount. They’re better off investing time and effort to making more sales not nickeling and diming with discounts

[RussianCow]

> They’re better off investing time and effort to making more sales not nickeling and diming with discounts

But discounts are one way to get more sales! There are plenty of mom-and-pop merchants that have to compete with large retailers and would benefit from a sophisticated discount system to drive higher volumes, but they just don't have the resources or the experience to implement it themselves.

Source: I know the owners of a brick and mortar garden store that struggles with this.