whkoh / rover-analytics-assessment

Rover has acquired a small pet care start-up. Let's explore their data.

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Rover.com Data Science Assessment

I use this an an example for my data science students so that they are exposed to a real take-home assessment before their job search begins.

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Scenario

In this exercise, imagine that Rover has acquired a small pet care start-up. As an analyst, you have been tasked with the responsibility of exploring their database.

Submission Requirements

For sections II-VI, choose the top 3 sections that interest you and submit your work for those. Keep any information that could identify you (e.g., photos, your name) in a separate folder named PII or a separate file named pii.txt so that we can anonymize your work.

Exercises

I. Exploring the Database

We begin by asking a few basic questions about the users of this platform. This first exercise is presented with answers so that you can diagnose any issues you might have connecting to or working with the data.

  1. How many users have signed up?

The answer is 64393.

  1. How many users signed up prior to 2018-02-03 ?

The answer is 35826.

  1. What percentage of users have added pets?

The answer is 80.43%.

  1. Of those users, how many pets have they added on average?

The answer is 1.501.

  1. What percentage of pets play well with cats?

The answer is 24.85%.

II. Conversations and Bookings

Some users can offer pet care services. When an owner needs pet care, they can create a conversation with another user that offers the service they are interested in. After exchanging some messages and possibly meeting in person, that conversation hopefully books. In that case, services are paid for and delivered. Occasionally, some conversations that have booked may be cancelled. Lastly, for uncancelled bookings, both owners and sitters have the option of leaving a review. In the following questions, we explore these concepts.

  1. For uncancelled bookings, is the owner or provider more likely to leave a review and which tends to leave better reviews? How would you narrate this finding to a business partner?

III. Recent Daily Booking Rate

The snapshot of this database was taken on 2018-08-02 at midnight and only contains data reflecting events prior to that date. A junior analyst is investigating daily booking rate during the days prior to the snapshot and is concerned about an apparent downward trend. You are tasked with helping them out.

  1. 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?
  2. 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

In order to do the next exercise, you will need to understand the fee structure for this company. Each user has a fee associated with their account (recorded on people_person ). If that user books as an owner, the company charges a service fee (in addition to the booking total) that is a percentage of the booking total (to a maximum of $50). Also, each service has a fee amount (recorded on services_service). Before a provider receives their payment, the company takes a percentage of the booking total as dictated by that fee. As an example, suppose an owner has a fee amount of 5% and books with a service that has a fee amount of 15%. If the booking was for $100, then the owner would get charged $105 (adding the ownerʼs fee). The $5 owner fee would go to the company. An additional $15 would also go to the company since the service had a 15% fee associated to it. The remaining $85 would go to the provider. To summarize:

Amount Description
Booking Total $100 e.g., 4 walks at $25/walk
Owner Fee $5 5% of the booking total
Gross Billings $105 charged to the owner
Service Fee $15 15% of the booking total
Net Revenue $20 all fees that go to the company
Provider Payment $85 earnings for the provider
  1. In each month, what were the gross billings and net revenue?
  2. Define take rate to be the percentage of gross billings that is net revenue. In the previous example, the take rate is slightly more than 19% since $20/$105 is approximately 0.1905. In each month, what was the aggregate take rate?
  3. Did take rate trend up or trend down or remain unchanged over time?
  4. 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.

V. New Conversation Flow

Internal documents indicate that this recently acquired company was performing many A/B tests; we would like to investigate one. This platform had a conversation page where owners and service providers could exchange messages as they organized their booking. The team thought this page could use a re-design and set out to improve its UI. A product manager then set up a test to measure the new page's effectiveness. On 2018-04-04 , an A/B test was launched. For those owners who sent a request, they would be randomly assigned to variant or holdout groups. Those users who are in the variant group would see the new conversation flow. However, those in the holdout group would see the old conversation flow. Providers would always see the old conversation flow.

  1. Did conversations with the new conversation page book at a higher rate?
  2. Is it statistically significant?
  3. Do you have any reservations about the experiment design? What would you recommend as next steps?

VI. Search Engine Marketing

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.

  1. 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.
  2. How many users were acquired via Google advertising since 2018-05-04 and what was the average cost per account?
  3. 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?
  4. How many additional accounts where created? What was the marginal cost per account for these additional accounts?

Data Available

The dataset includes 6 CSV files, listed and described below.

pets_pet

This table details each pet that a user has added to their profile. One owner may have more than one pet, but not vice versa. Many of the fields on this table are self explanatory but we have detailed a few below.

  • description - A short (lorem ipsum) description of the pet.
  • plays_cats - If 1, then this pet plays well with cats.
  • plays_children - If 1, then this pet plays well with children.
  • plays_dogs - If 1, then this pet plays well with dogs.
  • spayed_neutered - If 1, then this pet has been spayed or neutered.
  • house_trained - If 1, then this pet is house trained.
  • owner_id - This foreign key reports the people_person record for this petʼs owner.

services_service

On our site, users may offer pet care services. This table stores a record for each service that is offered. Each user can offer more than one service, but not more than one of each type. Many of the fields on this table are self explanatory but we have detailed a few below.

  • max_dogs - This number is the maximum number of pets this provider would prefer to care for.
  • fee - When a user books with a service, we take a percentage of the booking total. This field reports the percentage.
  • provider_id - This foreign key reports the people_person record for this serviceʼs provider.
  • added - A timestamp for when this service became active.
  • price - The price per unit booked.

conversations_conversation

An owner can book a service provider by starting a conversation with them. This table stores a record for each conversation started on our platform. Many of the fields on this table are self explanatory but we have detailed a few below. start_date - This is the date for which pet care will first be needed. end_date - This is the last date for which pet care will be needed. units - This is the number of units of service that the owner is interested in booking.

  • added - A timestamp for when this conversation was created.
  • booking_total - This is the dollar amount (not including the ownerʼs service fee) that this booking would cost.
  • requester_id - This foreign key reports the people_person record for the pet owner that is requesting pet care.
  • service_id - This foreign key reports the services_service record for the service that the pet owner is requesting.
  • booked_at - If the request is booked, this timestamp reports when that occurred.
  • cancelled_at - A booked request can be cancelled. In that case, this timestamp reports when that occurred.

conversations_conversation_pets

Since a booking may involve many pets and many pets might have had many bookings, it is necessary to store this many-to-many relationship on a separate table. Many of the fields on this table are self explanatory but we have detailed a few below.

  • conversation_id - A foreign key to a booking request on the conversations_converation table. If this conversation involves caring for more than one pets, then this conversation_id will occur on more than one row on this table (once for each pet).
  • pet_id - A foreign key to a pet that will receive pet care during the corresponding conversationʼs booking.

conversations_message

Each conversation consists of a series of messages. A conversation may contain many messages, but not vice versa. Many of the fields on this table are self explanatory but we have detailed a few below.

  • conversation_id - This foreign key reports the conversation in conversations_conversation for which this message is apart of.
  • sender_id - This foreign key reports the user in people_person that sent this message.

conversations_review

If a booking occurs, then either participant can leave a review for the experience. This table records those reviews, which consist of a brief statement and a star rating. Many of the fields on this table are self explanatory but we have detailed a few below.

  • conversation_id - This foreign key reports the booking in conversations_conversation for which this review pertains.
  • reviewer_id - This foreign key reports the user in people_person that wrote this review.

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Rover has acquired a small pet care start-up. Let's explore their data.


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