Imagine you're a PM at Swiggy.
You introduced a new feature (via an A/B) that auto-suggests (with quantity as zero) desserts / sides / soft-drinks at checkout time in the carts of users. All users have to do is to increase 0 to 1 and voila, they get that item in their cart. I'm guessing, you've experienced the feature first hand - if not, pls try and add something to your Zomato cart to see it yourself. It looks like ->
Write a case study (in a shared Google doc or whatever) that shows the outcome of that A/B.
The goal of the feature is to increase GMV for Swiggy and AOV for restaurants. There are multiple metrics that might move upward or downward as a result of this feature.
In the assignment, we'd like you to figure out what those metrics might be and make up some imaginary numbers (like, say, the B bucket had 9,50,670 users and X metric went up 10% or Y metric went down 5% or whatever) and then present the case.
In other words, we'd like you to imagine that
(a) the A/B has already occured,
(b) the B bucket was shown this auto-suggest feature,
(c) there was some outcome of the A/B and then present the case.
The goal is to check whether you
understand all the metrics that might be affected by such a feature, how they interplay with each other
, and how a case like this is