Visitors Dataset - Conversion Rate - Job Value - Data Analysis Assignment Help
Dataset Assignment HelpTask :
Thumbtack is a marketplace for local services. Our customers come to our website or mobile app, fill out category-specific request forms, and receive up to 5 quotes from relevant professionals within the next 24 hours. For example, a customer might submit a house cleaning request for a two bedroom, one bathroom apartment in San Francisco and get 3 quotes from professionals (“pros”), each with a price estimate for the project. Customers then have the option to hire one of these pros and leave them a review.
Datasets and schema Visitors CSV
This dataset contains a list of unique Thumbtack visitors who started request forms in either house cleaning or local moving categories within the last few months. Some of these users submitted a request. These customers then received between 0 and 5 quotes from pros (i.e., professionals providing services on Thumbtack). Customers who received quotes then had the option to hire one of the pros.
date (string) the day the visitor came to Thumbtack
device (string): whether the visitor is using a desktop or mobile device
category (string): category for which the visitor needs a project done
request_sent (integer): 1 if the user sent a request, 0 if not
request_id (integer): unique identifier for a request, NA if the user did not submit a request
how_far (string): for requests in the moving category, how far the customer estimates that they will move
num_rooms (string): for requests in the cleaning category, how many rooms the customer has
num_baths (string): for requests in the cleaning category, how many bathrooms the customer has
This dataset contains a list of quotes that pros sent in response to customer requests. Each quote is associated with a particular request and usually contains a price estimate.
quote_id (integer): unique identifier for a quote
request_id (integer): unique identifier for the request a quote is associated with
quote_price (integer): estimated price in dollars for the project
hired (boolean): 1 if the quote was marked as hired by the customer, 0 otherwise
pro_id (integer): identifier for a pro
Thumbtack has decided to take a closer look at performance in two of its largest categories - House Cleaning and Local Moving. Please complete the analyses suggested below and overlay your own recommendations for how we can improve and grow our marketplace. In your analysis, please also note any steps you took to transform or clean the data.
1. Visitors and Conversion Rate
How does the number of visitors change over time?
What percent of visitors submit a project request?
How do category and device influence these metrics?
2. Quotes Per Request
What is the distribution of number of quotes per request?
What factors contribute to some requests getting more quotes than others?
3. Job Value
By category, what is the distribution of quote prices for a project?
By category, what price do you think Thumbtack should charge pros to quote? Why?
Explain your reasoning for any assumptions that you make.
4. Further Exploration
Briefly describe two other questions or analyses you would be interested in pursuing if
you had more time to explore this data
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