Summarize the following response by Speaker B to Speaker A's question. Only summarize Speaker B's response. Extract the salient points that directly address Speaker A's question. Keep the summary length short so that it can fit into a sticky note:

Speaker A:
Okay, yeah, that's really helpful because one of the pieces that we've been trying to think through is how data scientists make the connection between the models that they're building and the business outcomes that are trying to hit. Because the model validation piece makes sense in the context of like, I need some metric that you're using to basically kind of quantify the quality of a model, for example, is one thing, and then second is it delivering the business outcome that is needed. And so I'm curious how you thought about and if you have a good story from this sales example of how you knew that you built a model that actually was working and delivering the business outcomes.
Speaker B:
Yeah, so there are some model accuracy tests so you could conduct those quick tests and see what the percentages are. I think over 85%. Accuracy was pretty good. So I think checking accuracy, there are one or two other things that I can't recall. But I know there are a set of tests that after you build this model, you want to check and make sure that it's going through these tests and you have a pretty good accuracy. And then once we started, sort of felt like this was in a good place to move into a soft launch with, let's say, a pilot sales team, they would give us some test cases, and we would look at and these test cases were cases where we already knew the market share and we knew what to expect in the outcome. And so running that case through the model, we could be able to see how close does that get to actual data, and so would see that 95% of all of our prior test cases matched what the predictions of the model said. So that gave us a lot of confidence in the model and we were able to come up with a couple of test cases that were unique where the prediction wasn't correct. And then we can go back and iterate on the model and make some refinements there. But model is never going to be like 100%, right? There should be exactly 6 paragraphs separated by the markdown divider: ***.
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