Question

How do you organize a PRODUCT MANAGER case study? specifically this case !

Pretend you’re the pricing product manager for Lyft’s ride-scheduling feature, and you’re launching a new city like Toledo, Ohio.

The prevailing rate that people are used to paying for rides from the airport to downtown (either direction, one way) is $25. The prevailing wage that drivers are used to earning for this trip is $19.

You launch with exactly this price: $25 per ride charged to the rider, $19 per ride paid to the driver. It turns out only 60 or so of every 100 rides requested are finding a driver at this price.

(While there is more than one route to think about in Toledo, for the sake of this exercise you can focus on this one route.)

Here’s your current unit economics for each side:

Drivers:

Customer acquisition cost (CAC) of a new working driver is roughly $500

At the prevailing wage, drivers have a 5% monthly churn rate and complete 100 rides / month

Riders:

CAC of a new rider is $10 to $20 (it’s sensitive to the rate of acquisition, since existing marketing channels are only so deep)

Each rider requests 1 ride / month on average

Churn is interesting: riders who don’t experience a "failed to find driver" event churn at 10% monthly, but riders who experience one or more "failed to find driver" events churn at 33% monthly

You’ve run one pricing experiment so far: when you reduced Lyft’s take from $6/ride to $3/ride across the board for a few weeks, match rates rose nearly instantly from 60% to roughly 93%.

Your task is to maximize the company’s net revenue (the difference between the amount riders pay and the amount Lyft pays out to drivers) for this route in Toledo for the next 12 months. Let’s assume that you cannot charge riders more than the prevailing rate.

The core question is: how much more or less do you pay drivers per trip (by changing Lyft’s take)? Your goal is to maximize net revenue for the next 12 months on this route.

Answer 1

To organize the case study, analyze current market conditions and company unit economics, including CAC and churn rates. Adjust the driver payment to balance rider and driver utility, run pricing experiments, and monitor churn and match rates to find the optimal level for Lyft's take that maximizes net revenue over the next 12 months.

To organize a case study for a product manager focusing on the pricing strategy of Lyft's ride-scheduling feature in Toledo, Ohio, you need to take several steps. First, you must understand the current market conditions, such as the prevailing ride rates and driver wages. Next, analyze the company's unit economics, considering customer and driver acquisition costs and churn rates.

The goal is to maximize net revenue over the next 12 months without exceeding the prevailing rate for riders. Conducting a pricing experiment showed that lowering Lyft's take from $6/ride to $3/ride increased matching rates from 60% to 93%. To optimize net revenue, you should adjust the driver payment while factoring in the impact on customer and driver acquisition costs and churn rates. It is essential to find a balance that maximizes utility for both riders and drivers, thereby preventing high churn and ensuring a sustainable business model.

From the case details, it is clear that the rate at which Lyft compensates drivers strongly influences the availability of drivers for riders. The challenge then is to find the optimal balance between lowering Lyft's take to increase driver availability without adversely affecting the net revenue. With the current data, it's crucial to conduct further pricing experiments to find the sweet spot for Lyft's take while monitoring churn rates and match rates.

Answer 2

To maximize net revenue for the next 12 months on the Toledo route, the pricing product manager should analyze and adjust the pricing strategy by changing Lyft's take. By experimenting with different Lyft takes and monitoring match rates and churn rates, the manager can find the balance that maximizes net revenue.

Step-by-step explanation:

To maximize the company’s net revenue for the next 12 months on the Toledo route, the pricing product manager for Lyft should analyze and adjust the pricing strategy. Since Lyft cannot charge riders more than the prevailing rate of $25, the manager needs to find a balance between attracting more rides and optimizing revenue. One way to do this is by changing Lyft's take (the amount charged by Lyft) in order to increase match rates while still remaining within the prevailing rate.

The current unit economics show that reducing Lyft's take from $6/ride to $3/ride increased match rates from 60% to roughly 93%. Therefore, it can be inferred that a lower Lyft take leads to higher match rates and potentially higher revenue.

In order to calculate the optimal Lyft take, the manager needs to consider the churn rates and costs associated with both drivers and riders. By experimenting with different Lyft takes and monitoring the impact on match rates and churn rates, the manager can find the balance that maximizes net revenue for the next 12 months.