III. Recent Daily Booking Rate
Column
Discovery
Findings align with those of the analyst; daily booking rates fell signifanctly during the timeframe… The table below shows the dates and amount when the daily booking rate began on the downward slope.
First, let’s reproduce their results. They tell you that daily booking rate is defined to be the percentage of conversations created each day that eventually book. What is the daily booking rate for each of the 90 days prior to the snapshot? Is there a downward trend?| date | total_count | booked_count | percent |
|---|---|---|---|
| 2018-07-28 | 310 | 118 | 38.06 |
| 2018-07-29 | 267 | 83 | 31.09 |
| 2018-07-30 | 304 | 57 | 18.75 |
| 2018-07-31 | 306 | 38 | 12.42 |
| 2018-08-01 | 284 | 14 | 4.93 |
Trend
As seen below in the 90 days prior to the snapshot trend there is a very visible downward trend beginning at the end of July
Conclusion
Can you narrate a reason why this trend exists? Is there a reason to be concerned? Please provide additional data and evidence to justify your position.
IV. Analyzing Take Rate
Column
Gross Billings
In each month, what were the gross billings and net revenue?
Below shows the gross billings| month | gross_billings |
|---|---|
| 2016-08-01 | 6874.70 |
| 2016-09-01 | 3303.95 |
| 2016-10-01 | 5396.95 |
| 2016-11-01 | 8692.85 |
| 2016-12-01 | 8754.95 |
| 2017-01-01 | 14369.25 |
| 2017-02-01 | 13678.10 |
| 2017-03-01 | 16725.60 |
| 2017-04-01 | 19650.05 |
| 2017-05-01 | 22184.30 |
| 2017-06-01 | 25953.60 |
| 2017-07-01 | 28120.80 |
| 2017-08-01 | 31419.60 |
| 2017-09-01 | 33403.20 |
| 2017-10-01 | 35808.00 |
| 2017-11-01 | 35301.60 |
| 2017-12-01 | 41694.00 |
| 2018-01-01 | 44108.40 |
| 2018-02-01 | 41865.60 |
| 2018-03-01 | 50127.60 |
| 2018-04-01 | 50133.60 |
| 2018-05-01 | 54199.20 |
| 2018-06-01 | 55066.80 |
| 2018-07-01 | 58752.00 |
| 2018-08-01 | 2488.80 |
Net Revenue
Below is the net revenue| month | net_revenue |
|---|---|
| 2016-08-01 | 896.70 |
| 2016-09-01 | 430.95 |
| 2016-10-01 | 705.63 |
| 2016-11-01 | 1135.67 |
| 2016-12-01 | 1146.68 |
| 2017-01-01 | 1875.60 |
| 2017-02-01 | 1793.90 |
| 2017-03-01 | 2189.70 |
| 2017-04-01 | 2579.20 |
| 2017-05-01 | 3220.85 |
| 2017-06-01 | 4346.30 |
| 2017-07-01 | 4699.60 |
| 2017-08-01 | 5248.55 |
| 2017-09-01 | 5598.10 |
| 2017-10-01 | 5993.05 |
| 2017-11-01 | 5906.20 |
| 2017-12-01 | 6972.52 |
| 2018-01-01 | 7389.34 |
| 2018-02-01 | 7011.83 |
| 2018-03-01 | 8411.93 |
| 2018-04-01 | 8383.18 |
| 2018-05-01 | 9090.32 |
| 2018-06-01 | 9211.12 |
| 2018-07-01 | 9840.51 |
| 2018-08-01 | 414.80 |
Take Rate
what was the aggregate take rate? Did take rate trend up or trend down or remain unchanged over time? a.| month | take_rate |
|---|---|
| 2016-08-01 | 27.26087 |
| 2016-09-01 | 13.56522 |
| 2016-10-01 | 21.96522 |
| 2016-11-01 | 36.44348 |
| 2016-12-01 | 36.69565 |
| 2017-01-01 | 58.73913 |
| 2017-02-01 | 56.56522 |
| 2017-03-01 | 68.73913 |
| 2017-04-01 | 80.73913 |
| 2017-05-01 | 98.54529 |
| 2017-06-01 | 129.95833 |
| 2017-07-01 | 140.54167 |
| 2017-08-01 | 157.04167 |
| 2017-09-01 | 167.91667 |
| 2017-10-01 | 180.87500 |
| 2017-11-01 | 175.87500 |
| 2017-12-01 | 209.20000 |
| 2018-01-01 | 222.00000 |
| 2018-02-01 | 209.99167 |
| 2018-03-01 | 252.97500 |
| 2018-04-01 | 253.04167 |
| 2018-05-01 | 273.41667 |
| 2018-06-01 | 274.82500 |
| 2018-07-01 | 296.01667 |
| 2018-08-01 | 12.50000 |
Take Rate Trend
Conclusion
If it did change, investigate why and provide an explanation. Be sure to provide additional data/charts/evidence that justify your explaination. Any claims should be backed by data.
VI. Search Engine Marketing
Column
Discovery
Conclusion
Search engine advertising is a huge driver of new user accounts. Users that are aquired through search engine marketing can be identified by looking at people_person.channel . These users will have ‘Google’ listed there. Historically, this company spent an average of $30 per account to advertise in the 2nd position on Google. However, on 2018-05-04 , they decided to start bidding for the 1st position. Since 2018-05-04 , they have spent $207180 in total. . For each day, determine the count of users that joined and were acquired through Google. Plot this and confirm there is an inflection point on or near 2018-05-04 . _. How many users were acquired via Google advertising since 2018-05-04 and what was the average cost per account?
`. Estimate how many users would have been acquired had the company not changed its bidding strategy. What would have been the marketing spend in that case? a. How many additional accounts where created? What was the marginal cost per account for these additional accounts?