August 2023
PRODUCT TEAM CASE
STUDY #1
FOR
CLIPBOARD HEALTH
onapeter@yahoo.com
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August 2023
kindly validate my assumptions and provide answers to these questions to enable me proceed:
➢ Pricing product manager for lyft’s ride scheduling feature, launching a new city like Toledo,
Ohio.
➢ One-way prevailing rate for rides from airport to downtown= $25
➢ Prevailing wage that drivers are used to earning for this trip= $19
Launch Price
Rider=$25 per ride charged to the rider
Driver= $19 per ride paid to the driver.
Matching Rate= only 60 out of every 100 rides (60%)
For the sake of the exercise, we should focus on one route.
Current Unit economics for each side;
Drivers:
-
-
Customer acquisition cost (CAC): $400-$600
(Since our focus is on net revenue, we can assume to neglect CAC in maximizing company’s
revenue?)
At the prevailing wage:
i.
Monthly churn rate= 5%
ii.
Complete rides/month=100
Riders
-
-
CAC= $10-20
(Since our focus is on net revenue, we can assume to neglect CAC in maximizing company’s
revenue?)
Rider request per month=1
Churn Rate:
i.
Don’t experience Failed to find driver=10% monthly
ii.
Failed to find driver one or more= 33% monthly
Experiment 1#
Reduce lyft take from $6/ride to $3/ride across the board for a few weeks.
Can we assume the few weeks to be 4 weeks= 1Month?
Results:
Matching Rate: Rose from 60% to 93%.
Goal/Task
onapeter@yahoo.com
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August 2023
1. Maximize the company’s net revenue (the difference between the amount riders pays and the
amount lyft’s payouts to drivers) for Toledo route next 12 months.
2. Cannot charge riders more than the prevailing rate, which is $25
Questions:
1. Any restriction to the amount of pricing experiment we can run to maximize revenue?
2. Are we expected to show monthly revenue for the complete 12 months period?
Following this reply from Rolayo on 4 August, 2023;
Hi Peter,
Thank you for your inquiry
Kindly feel free to include any assumptions that will enable you to craft a good solution to the case but
make sure to include all assumptions made in your write up
I hope this helps
Regards,
Rolayo
In approaching any case study, I generally approach them with these best practices in mind:
1.
2.
3.
4.
5.
Articulate the problems.
Brainstorm some solutions.
Use certain criteria to prioritize and decide on them.
Pricing experiments of the solution.
A,B Testing for the solution.
PART 1
ARTICULATE THE PROBLEMS
We are in a 2-side marketplace, where we consider the driver and rider as customers/users. We start
from considering the problems that the customers are experience and walk our way back to the
company.
We can deduce the following;
i.
From the case study, we can assume from the matching rate that the drivers are not willing
to accept ride at the prevailing rate.
onapeter@yahoo.com
+2438132790865
August 2023
ii.
Riders are experiencing one or more failed request at this prevailing rate because drivers are
not accepting request.
The customer acquisition cost is rising for drivers and riders, so contribution to increase in
the unit economies on the business.
At this prevailing rate, drivers have a monthly churn rate of 5%.
At this prevailing rate, the rider’s churn rate of those that didn’t experience ‘Failed to find
driver’ is 10%, while those with one or more ‘Failed to find driver’ is 33%.
We cannot increase the prevailing rate we charge rider (@$25).
iii.
iv.
v.
vi.
PART 2
BRAINSTORM ON POSSIBLE SOLUTIONS.
Our goals is to maximize the net revenue for the company for the Toledo’s route for the next 12 months.
What is our Objective?
We have look for possible solutions that will meet these objectives:
i.
ii.
Maximize the matching rate to 100(100%).
Achieved maximum driver’s satisfaction will maximize matching rate (A happy customer is
good for business).
Reduce or eliminate rider’s experience of one or more ‘Failed to find driver’.
iii.
SOLUTIONS
A.
B.
C.
D.
E.
Increase driver’s pay per ride
Decrease driver’s pay per ride
Increase the numbers of drivers willing to accept the request.
Increase the numbers of riders on the Toledo route.
Give incentives/bonuses to increase rider’s request and driver’s willingness to accept request.
onapeter@yahoo.com
+2438132790865
August 2023
PART 3
EVALUATION CRITERIA MODEL OF THE SOLUTIONS.
We want to use certain criteria to evaluate our solutions to prioritize them based on the best possible fit
to the company’s goal, fit into our constraint, and that we have enough data/information to pursue.
We will use the following set of criteria
i.
ii.
iii.
Customer Value.
Business Value.
Data Fit.
CUSTOMER VALUE:
We are in 2-side marketplace, where we consider drivers and riders as customers/users. Their
experience is critical to the success of the business and also achieving the business objective. Our job is
to provide good solution for the case that will give short term and long term satisfaction to lyft’s
customers. When drivers are satisfied, the matching rate will increase, churn rate will decrease for
riders. And when riders are satisfied by having success request, their churn rate will decrease.
BUSINESS VALUE:
One of the business objectives is to make money by maximizing it net revenue. Our solutions should be
able to provide lyft’s a pricing strategy that will enable her maximize her net revenue at prevailing
market conditions.
DATA FIT:
We need solutions that can fit into the data/information provided by the case study. A solution that we
have enough data/information to test it validate.
EVALUATION CRITERIA MATRIX
CRITERIA/CUSTOMER
CUSTOMER VALUE
BUSINESS VALUE
DATA FIT
DRIVER
A, E
A, B, C
A, B
RIDER
E
D
SOLUTION A:
➢ Increase the driver satisfaction and willingness to accept request.
➢ Business objective of customer satisfaction will be achieved and although decrease lyft’s take,
but will be compensated by the increase in matching rate.
➢ There is enough data/information provided by the case study to test this solution.
onapeter@yahoo.com
+2438132790865
August 2023
SOLUTION B:
➢ Tend to increase lyft’s take and so maximize net revenue, but will reduce matching rate,
increase churn rate for riders.
➢ There is enough data/information to test this solution.
SOLUTION C:
➢ It has the tendencies to increase matching rate, so reduce churn rate for riders, but will not
reduce churn rate for drivers and also will not increase their individual satisfaction.
➢ No enough data/information from the customer acquisition cost of driver to test the impact of
the solution from the case study (weather an increase/decrease in CAC influence the number of
drivers).
➢ The core question revolves around driver’s pay.
SOLUTION D:
➢ It can only increase the total revenue for lyft.
➢ No enough data/information from the CAC of the rider to test the impact of the solution
(weather an increase of decrease of CAC for riders influenced the numbers of riders).
➢ The core question revolves around driver’s pay.
SOLUTION E:
➢ This solution has the tendencies to increase customer’s satisfaction of drivers and riders. May
reduce churn rate for riders and drivers.
➢ Increase the CAC of rider and driver.
➢ No enough data/information to test its impact.
Therefore, based on the evaluation criteria matrix, SOLUTION A meet the three (3) criteria and will be
considered for testing to see if lyft’s net revenue can be maximize.
PART 4
PRICNG EXPERINMENT OF SOLUTION A
Solution A: Increase driver’s pay per trip
Objective:
1. Reduce lyft’s take
2. Maximize the matching rate to 100(100%)
onapeter@yahoo.com
+2438132790865
August 2023
Pricing Experiment 1#
Lyft’s Take= $6/ride
Matching rate= 60%
Assume, in a period of 1 month;
Lyft’s Take reduce to = $3/ride
Then, matching rate increase to = 93%
Pricing Experiment 2#
Percentage increase of matching rate when lyft’s take decrease from $6/ride to $3/ ride;
93% -60% = 33%...............................................(i)
The difference in amount of lyft’s take;
$6 -$3= $3……………………………………………………. (ii)
If we divide the difference in amount of lyft’s take & the percentage increase of matching rate by a
common denominator of Three (3), we will arrive at;
$3/3
=
$1
=
33%/3……………………………(iii)
11%.................................(iv)
Therefore, we can deduce that each $1 decrease in lyft’s take = 11% increase in the matching rate.
Also, since 100 cents = $1,
We can state that;
100 cents decrease in lyft’s take = 11% increase in the matching rate.
If we further divide it by a common denominator of 10;
100 cents/10
10 cents
=
=
11%/10…………………………………………(v)
1.1%................................................(vi)
Based on the rate of increase/decrease, in achieving a 100% matching rate, we will need to multiple
equation (vi) by 6;
10 cents X 6
60 cents
onapeter@yahoo.com
= 1.1% X 6
= 6.6% ……………………………………………………….(vii)
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Therefore;
Decreasing lyft’s take by 60 cents;
$3- $0.6 = $2.4……………………………………………………………………. (viii)
We increase matching rate by;
93% + 6.6% = 99.6%...................................................................(ix)
Note: we approximate 99.6% to nearest whole number to get 100%
Therefore, at $2.4 lyft’s take will produce 100% matching rate for the trip.
Therefore, at $2.4 lyft’s take, we will maximize the company’s net revenue for Toledo route in the
next 12 months.
Core Questions:
How much more or less do you pay drivers per trip (by changing lyft’s take)?
Answer:
Decreasing lyft’s take to $2.4, will increase drivers pay per trip by $3.6 more.
Therefore, driver’s pay per trip will be;
= $19 + $3.6 = $22.6.
PART 5
A-B TESTING FOR THE SOLUTION FOR 12 MONTHS.
A = Lyft’s take of $6
B = Lyft’s take of $2.4
Note:
Why $2.4 not $3 for Test B?
Since our goal is to maximize net revenue; at $3 the matching rate is 93%, but at $2.4 the matching rate is 100%. Therefore, net
revenue will likely be maximized at $2.4 than at $3. So, we will use $2.4 for B against $6 for A
Perimeters for the A-B testing;
-
Total Number of rides per month.
Matching rate for A.
onapeter@yahoo.com
= 1000
= 60% (0.6)
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August 2023
-
Matching rate for B.
Riders who don’t experience a ‘failed to find driver’ event
churn rate.
Riders who experience one or more ‘Failed to find driver’
event churn rate.
= 100% (1)
=10% (0.1)
= 33% (0.33)
Month 1#
A
Total Matched rides= 1000 x 0.6= 600
Total unmatched ride = 1000-600 = 400
Total net revenue = 600 x 6 = $3,600
B
Total matched rides= 1000 x 1 = 1000
Total unmatched ride = 0
Total net revenue = 1000 x 2.4 = $2,400
Month 2#
A
Matched ride = 600
Matched ride x Churn rate = 600 x 0.1= 60
Available ride =600 -60 = 540
Unmatched ride = 400
Unmatched ride x Churn rate = 400 x 0.33 = 132
Available ride = 400 – 132 = 268
Total available ride = 540 + 268 = 808
Total matched ride = 808 x 0.6 = 485
Total Net Revenue = 485 x 6 = $2,910
B
Matched ride = 1000
Matched ride x Churn rate = 1000 x 0.1 = 100
Available ride = 1000 – 100 = 900
Total Matched ride = 900 x 1 = 900
Total Net Revenue = 900 x 2.4 = $2,160
Month 3#
A
Matched ride = 485
Unmatched ride = 323
Matched ride x Churn rate = 485 x 0.1 = 49
Available ride = 485 – 49 = 436
Unmatched ride x Churn rate = 323 x 0.33 = 107
Available ride = 323 – 107 = 216
Total Available ride = 436 + 216 = 657
Total Matched ride = 657 x 0.6 = 391
Total Net Revenue = 391 x 6 = $2,346
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B
Matched ride = 900
Matched ride x Churn rate = 900 x 0.1= 90
Available ride = 900 - 90 = 810
Total Matched ride = 810 x 1 = 810
Total Net Revenue = 810 x 2.4 = $1,944
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Month 4#
A
Matched ride = 391
Unmatched ride = 260
Matched ride x Churn rate = 391 x 0.1 =39
Available ride = 391 -39 = 352
Unmatched ride x Churn rate = 260 x 0.33 = 86
Available 260 – 86 = 174
Total Available ride = 352 + 174 = 526
Total Matched ride = 526 x 0.6 = 316
Total Net Revenue = 316 x 6 = $1,896
B
Matched ride = 810
Matched ride x churn rate = 810 x 0.1 = 81
Available ride = 810 – 81 = 729
Total Matched ride = 729 x 1= 729
Total Net Revenue = 729 x 2.4 = $1,750
Month 5#
A
B
Matched ride = 316
Unmatched ride = 210
Matched ride x Churn rate = 316 x 0.1 = 32
Available ride = 316 – 32= 284
Unmatched ride x Churn rate = 210 x 0.33 = 69
Available ride = 210 – 69 = 141
Total Available ride = 284 + 141 = 425
Total matched ride = 426 x 0.6 = 255
Total Net Revenue = 255 x 6 = $1,530
Matched ride = 729
Matched ride x Churn rate = 729 x 0.1 = 73
Available ride = 729 – 73 = 656
Total matched ride = 656 x 1 = 656
Total Net Revenue = 656 x 2.4 = $1,574
Month 6#
A
Matched ride = 255
Unmatched ride = 171
Matched ride x Churn rate = 255 x 0.1 = 26
Available ride = 255 – 26 = 229
Unmatched ride x Churn rate = 171 x 0.33 = 56
Available ride = 171 – 56 = 115
Total Available ride = 229 + 115 = 344
Total Matched ride = 344 x 0.6 = 206
Total Net Revenue = 206 x 6 = $1,236
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B
Matched ride = 656
Matched ride x Churn rate = 656 x 0.1 = 66
Available ride = 656 -66 = 590
Total Matched ride = 590 x 1 = 590
Total Net Revenue = 590 x 2.4 = $1,416
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Month 7#
A
Matched ride = 206
Unmatched ride = 138
Matched ride x Churn rate = 206 x 0.1 = 21
Available ride = 206 – 21 = 185
Unmatched ride x Churn rate = 138 x 0.33 = 46
Available ride = 138 – 46 = 92
Total Available ride = 185 + 92 = 277
Total Matched ride = 277 x 0.6 = 166
Total Net Revenue = 166 x 6 = $996
B
Matched ride = 590
Matched ride x Churn rate = 590 x 0.1 = 59
Available ride = 590 – 59 = 531
Total matched ride = 531 x 1 = 531
Total Net Revenue = 531 x 2.4 = $1,274
Month 8#
A
B
Matched ride = 166
Unmatched ride = 111
Matched ride x Churn rate = 166 x 0.1 = 17
Available ride = 166 – 17 = 149
Unmatched ride x Churn rate = 111 x 0.33 = 37
Available ride = 111 – 37 = 74
Total Available ride = 149 + 74 = 223
Total Matched ride = 223 x 0.6 = 134
Total Net Revenue = 134 x 6 = $804
Matched ride = 531
Matched ride x Churn rate = 531 x 0.1 = 53
Available ride = 531 -53 = 478
Total Matched ride = 478 x 1 = 478
Total Net Revenue = 478 x 2.4 = $1,147
Month 9#
A
Matched ride = 134
Unmatched ride = 89
Matched ride x Churn rate = 134 x 0.1 = 13
Available ride = 134 – 13 = 121
Unmatched ride x Churn rate = 89 x 0.33 = 29
Available ride = 89 – 29 = 60
Total Available ride = 121 + 60 = 181
Total Matched ride = 181 x 0.6 = 109
Total Net Revenue = 109 x 6 = $654
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B
Matched ride = 478
Matched ride x Churn rate = 478 x 0.1 = 48
Available ride = 478 – 48 = 430
Total matched ride = 430 x 1 = 430
Total Net Revenue = 430 x 2.4 = $1,032
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Month 10#
A
Matched ride = 109
Unmatched ride = 72
Matched ride x Churn rate = 109 x 0.1 =11
Available ride = 109 -11 =98
Unmatched ride x Churn rate = 72 x 0.33 = 24
Available ride = 72 – 24 = 48
Total Available ride = 98 + 48 = 146
Total Matched ride = 146 x 0.6 = 88
Total Net Revenue = 88 x 6 = $528
B
Matched ride = 430
Matched ride x Churn rate = 430 x 0.1 = 43
Available ride = 430 – 43 = 387
Total Matched ride = 387 x 1= 387
Total Net Revenue = 387 x 2.4 = $929
Month 11#
A
B
Matched ride = 88
Unmatched ride = 58
Matched ride x Churn rate = 88 x 0.1 = 9
Available ride = 88 – 9 = 79
Unmatched ride x Churn rate = 58 x 0.33 =19
Available ride = 58 – 19 = 39
Total Available ride = 79 + 39 = 118
Total Matched ride = 118 x 0.6 = 71
Total Net Revenue = 71 x 6 = $426
Matched ride = 387
Matched rid x Churn rate = 387 x 0.1 = 39
Available ride = 387 – 39 = 348
Total Matched ride = 387 x 1 = 348
Total Net Revenue = 348 x 2.4 = $ 835
Month 12 #
A
Matched ride = 71
Unmatched ride = 47
Unmatched ride x Churn rate = 71 x 0.1 = 7
Available ride = 71 – 7 = 64
Unmatched ride x Churn rate = 47 x 0.33 = 16
Available ride = 47 -16 = 31
Total Available ride = 64 + 31 = 95
Total Matched ride = 95 x 0.6 = 57
Total Net Revenue = 57 x 6 = $342
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B
Matched ride = 348
Matched ride x Churn rate = 348 x 0.1 = 35
Available ride = 348 -35 = 313
Total Matched ride = 313 x 1 = 313
Total Net Revenue = 313 x 2.4 = $751
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Total Net Monthly Revenue for Lyft for the Next 12 Months
Month/Testing 1
2
3
4
5
6
7
8
9
10
11
12
A (@$6) ($)
3600
2910
2346
1896
1530
1236
996
804
654
528
426
342
B (@$2.4) ($)
2400
2160
1944
1750
1574
1416
1274
1147
1032
929
835
751
Goal/Task
1. Maximize the company’s net revenue (the difference between the amount riders pays and the
amount lyft’s payouts to drivers) for Toledo route next 12 months.
Results:
1. The table above shows that for Month 1-4, the total net monthly revenue for lyft’s take for $6
was higher than for $2.4 consecutively.
2. But from Month 5-12, the total net monthly revenue for lyft’s take for $2.4 was higher than for
$6 consecutively.
3. Therefore, at $2.4 the company will maximize it net revenue for the Toledo route for the next 12
months.
onapeter@yahoo.com
+2438132790865