The purpose of this case 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.

## Pricing Strategy: [Next 12months]

### 🌟 TL;DR

### If we reduce the Lyft’s take by $1.45 (from $6 to $4.55), we will be able to increase the revenue by 6.2% per month for next 12 months.

Given Parameters :

Drivers:

CAC is around $400-600 for a new driver.

Riders have a 5% monthly churn rate - they complete 100 rides per month.

Riders:

CAC for a new rider is $10-20

average of 1 ride per month for each rider. Churn rate 10% (even if they found a driver) - 33% ( did not find the driver)

Recommendation:

Given that 60 out of 100 rides are matched, the current net revenue per month is $6 * 60 = $360.

When Lyft’s take was reduced from $6 to $3, the match rate increased from 60% to 93%. This suggests that for every $1 reduction in Lyft’s take, the match rate increases by about 16.5%. The relationship between Lyft’s take and the match rate is not linear but for the sake of the study let’s say it is. More rides happened at $3 but this resulted in Lyft taking home $279 opposed to $360 per month. More drivers and active riders were present but we gave too much $$ to get there. We can find a middle price that brings a heroically consistent match rate across 12 months. This rate could potentially shift down churn (need more data due to rapid fluctuations) and build rider/driver base.

So, if Lyft’s take decreases by, $1.45 (from $6 to $4.55), the match rate increases by about 24% (from 60% to 82%).

Revenue from riders = $25 * 84 = $2,100 |

Cost for drivers = $20.45 * 84 = $1717.8 |

$2,100 — $1,717 = $382.2 Monthly Net Revenue
Alternatively, 4.55 * 84 = $382.2 Monthly Net Revenue