Analyzing Lyft Driver Dropout

Gerard Kolan

Any Google problem solving interview question starts with clarifying what the interview is looking for.

Clarification

By ‘dropping out’, do you mean the DAU of Lyft drivers who successfully provided rides in this city decreased? [No, the DAU of Lyft drivers who can accept rides]
Is this a large city or small city, asking because sometimes Lyft drivers will operate cross the border of Citys [Small city, so cross border operation is possible]
Is the drop significant, outside of normal fluctuation? [Yes]
Is the drop a sudden drop or a gradual drop? [Gradual]
Do we see similar drops in adjascent cities? [No]

Analysis:

The journey for a Lyft driver is like:

1. Apply to be a driver

2. Pass screening

3. Open Lyft app, and wait for system assigned tasks

4. Accept the ride

5. Pickup the passenger on that day

A Lyft driver will only qualify for a DAU if he reaches step 3

Since we already know this is not a seasonal change, outside of normal fluctuations, I will first try to narrow down the scope of the problem. Looking at the metrics at different stages and conversions can give up insight on whether:

Acquisition problem, where the driver attrition rate looks normal, but new driver recruitment rate dropped in the greater area.
Engagement problem, where the frequency of drivers becoming available to ride in this city dropped.
Retention Problem, where drivers are leaving the Lyft platform at a higher than normal rate.

I can nail down the category by doing cohort analysis of drivers in different buckets, such as the acquisition volume, the drivers who used to operate in this city, are they operating in other cities? or have they left completely.

Assuming the issue is with Engagement, I will move on to determine whether it’s caused by internal factors or external factors.

Internal factors includes :

feature launch or bugs, e.g. causing frequent app crashes in this area.
Hw outage,e.g. related to load balancer in this city.
Policy change, e.g. end of incentive program.

External factors include:

Demand, e.g. drivers move to other cities due to no business here.
Environment, e.g. flood, public events, traffic congestion, or even government regulation
Competition, e.g. Uber announced incentive program in this city.
PR, e.g. there might be a ‘Delete Lyft’ compaign going on in this city.

By looking into metrics by sw version, OS(Android or IOS), Support contact rate and distributions, feature release timeline we can determine whether it’s internal factors.

By monitor PR headlines, competitor announcements, demand volume, or news relevent to the environment, we can determine whether it’s external factors.

Solution:

For issue with feature release causing the drop, I can work with eng to rollback the change.

For bugs, I can work with eng to push corresponding changes to fix.

For Issues around incentive program, I can work with corresponding team to resume or update the driver incentive program.

If the issue is with demand, I can work with biz team to offer discounts to riders to attract more riders.

If the issue is with government regulation, I can work with gov relationship team and local government to find solution, and keep drivers informed of progress.

if the issue is with competition, I need to come up with strategy to address the challenge, either through incentive policies, or through new features.

If the issue is with PR, I will work with PR team to mitigate, and keep our drivers/riders informed of the progress.

Summary

In short, I will first determine whether the drop is seasonal? whether it’s due to driver acquisition, engagement or retention. and finally pinpoint the internal or external factors causing the chang, and propose changes accordingly.

David Mercy

I assume “dropping out” refers to deactivating such that they do not drive for Lyft anymore. First of all, I would cross-check the source of the red flag data to be sure it is accurate.

Assuming the trend is verified, I’d ask these clarifying questions:
– What % of drivers are deactivating?
– Over what period of time has this deactivation been occurring? When did it begin?
– Did the change occur suddenly or gradually over a period of time?
– What changes occurred at the time the change occurred that might affect app performance? E.g. a code release or vendor change
– Is the change occurring within the entire driver population in the city, or among certain drivers only? e.g. only drivers that signed up in the past 6 months are affected
– What feedback have we heard from the drivers in the affected group? Have they provided reasons for deactivating?
– Have there been similar drops in other Lyft metrics in the area? e.g. has ridership experienced a similar trend?
– Has this trend appeared before in this city or another city? if yes, what was the cause?
– Has there been any server downtime or other errors reported?

Using this information, we want to determine if the problem is *internal* or *external* in nature.
An internal problem could be a bug, server issue, or a new feature that had unintended consequences. An external problem could be related to competition, bad PR, a natural disaster, a firmware change, or new regulatory or legal change.

If the problem is identified as internal, meaning a bug or the like, I would work with the engineering team to isolate the problem and push out a fix. Depending on the severity of the problem, I might ask to interrupt the current sprint and push this out as a hotfix, or if less severe, could include the fix in the next sprint plan.

If the problem is a feature that is causing issues, I’d work with Eng to roll back the feature and if possible, spec out a new feature that does not have a similarly detrimental impact.

If the issue is external, such as a hurricane, change to the law, or new competitor entering the market, I’d work through the normal product development cycle to plan for an address the problem. If the issue is temporary or seasonal, there may not need to be further action taken as the drivers will likely return without further intervention.

Pankaj Jain

There are multiple reasons why there could be a drop of drivers. We can break it down into company, customer (both driver and passenger), product, competition, and even government.

Which city is this specifically? And, how much of a percentage decrease are we talking about?
Is there some economic reason for this happening in that city that is outside of our control (government is increasing tariffs to be a driver or taxes for a 1099 employee is too much)?
Have we gotten bad PR?
Have our business model changed? Have we taken more % of the drivers pay?
What do you mean by dropping out? Are they deleting the driver app and/or resigning as being a driver? What specific metric are we talking about?
Is the percentage / # of driver drop similar MoM or YoY (seasonality)?
Are there recent changes made in the app that make it difficult to drive?
Are competitors (Uber, etc.) having a stronger play and have the incentive to drive for them and quit Lyft?

Add Your Answer

Answers (3)