Before jumping in, let me understand the question properly.
We are facing an increase in the number of cancellations of the rides booked by the users for the last week.
So, why is it a major problem? The more the cancellations the more the revenue gets affected. In the long term, this will lead to churn in users.

For how long are we facing the issue? For the last 2 weeks.

Which type of offerings faces this drop? Was it Sharing, Personal, Bikes, or Rental modes? The drop was spread throughout the options

With the basic understanding, I would like to mention how I would like to find the root cause of this problem. First of all, I would like to gather some more context about the situation and then come up with few hypotheses. Later, I’ll discuss how to confirm whether the hypotheses are right. Finally, I’ll state what might have been the root cause.

Gather Context:

So, Let me bucket my questions into two branches. One, that deals with external factors and the next that deals with internal factors.

External Factors:

Was the change a gradual one? or a sudden one? Let me assume that the change was gradual.

Was it a regional change? or a global level problem? Regional

Was there any Seasonality? No

Was there a drop in specific user demography affected in terms of age? 25+ Segment

Was the drop affecting only our company? Or was it spread throughout the industry? Only our company

Was there any new emergence of competitors or a new product that has gained huge attraction? No

Was there any change in the sentiment of users wrt our product/company? Sentimentality changes don’t occur within a few weeks. So, can be neglected.

Was any particular medium hit? like the Android app? iOS app? No Particular Medium was affected

Internal Factors:

Was the drop visible in any other metrics as well? No data

Was there any new update released when the problem started coming up? No

Was the logged data accurate? Yup

With the above assumptions, the following could be the probable cause.

Hypotheses:

• It could be probably because of some problems in finding the correct location to pick the customer/ too much of surging at normal hours.
• It might also be because of the connection between drivers and customers.

Hypotheses Checks:

1. 1. Check the metrics of Avg time taken in allotting drivers for every hour for those weeks.
   2. Check the avg rates calculated per ride and the no. of surges happening per day.

Probable Solutions: