Price estimation system
A method of operating a price estimation system includes obtaining service requests from consumers, and obtaining bids from service professionals based on the service requests obtained from the consumers. The method additionally includes generating a training set based on the bids and the service requests, and generating a model for generating price estimates based on the training set. The method also includes employing the model to generate the price estimates based on additional service requests provided by additional consumers. In some aspects, the method further includes communicating the price estimates to the additional consumers during performance of a process for obtaining the additional service requests from the additional consumers. In other aspects, the method further includes communicating the price estimates to additional service professionals during performance of a process for obtaining additional bids from the additional service professionals based on the additional service requests.
1 . A method comprising:
receiving, at a server from a consumer computing device, first data indicative of a first input by a user of the consumer computing device, wherein the first input comprises a selection by the user of a request for a home cleaning service;
sending, by the server based on the receiving of the first data at the server, second data to the consumer computing device, wherein the second data causes the consumer computing device to display a first prompt for a zip code in which the home cleaning service is requested;
receiving, by the server from the consumer computing device, third data indicative of the zip code entered by the user via the first prompt for the zip code displayed on the consumer computing device;
sending, by the server to the consumer computing device, fourth data that causes the consumer computing device to display a second prompt for a number of bedrooms and a number of bathrooms in which the home cleaning service is requested;
receiving, by the server from the consumer computing device, fifth data indicative of the number of bedrooms and the number of bathrooms entered by the user via the second prompt for the number of bedrooms and the number of bathrooms displayed on the consumer computing device;
generating, by the server, an estimate for the home cleaning service based at least in part on the zip code, the number of bedrooms, and the number of bathrooms, wherein the generating of the estimate further comprises using a model trained using a training set comprising service requests from consumers and bids from service professionals based on the service requests, wherein generation of the training set comprises:
establishing an empty training set data structure;
retrieving, from a database, a plurality of service requests R and bid data B (R) comprising bids b associated with the service requests; and
for each service request R in the plurality of service requests:
for each bid b in the bid data B (R) associated with the service request R:
adding to the training set data structure an entry comprising the service request R and the bid b; and
send, by the server to the consumer computing device, sixth data indicative of the estimate, wherein the sixth data causes the consumer computing device to display information related to the estimate.
2 . The method of claim 1 , wherein the information related to the estimate comprises a price estimate for the home cleaning service.
3 . The method of claim 1 , wherein the information related to the estimate comprises an estimated price range for the home cleaning service.
4 . The method of claim 1 , wherein the information related to the estimate comprises an estimated average price for the home cleaning service, an estimated high price for the home cleaning service, and an estimated low price for the home cleaning service.
5 . The method of claim 1 , wherein the estimate is further generated based on a home type input by the user of the consumer computing device.
6 . The method of claim 5 , wherein the home type input comprises one of a home type input, apartment type input, or business type input.
7 . The method of claim 1 , further comprising storing the model in memory of the server.
8 . A system comprising:
a processor; and
a memory having non-transitory computer readable instructions stored thereon that, upon execution by the processor, cause the system to:
receive, from a consumer computing device, first data indicative of a first input by a user of the consumer computing device, wherein the first input comprises a selection by the user of a service request;
send, based on the receiving of the first data, second data to the consumer computing device, wherein the second data causes the consumer computing device to display at least one prompt for a specific service detail related to the service request;
receive, from the consumer computing device, third data indicative of a response to the at least one prompt for the specific service detail related to the service request;
generate an estimate for the service request based at least in part on the selection by the user of the service request and the specific service detail related to the service request, wherein generation of the estimate further comprises using a model trained using a training set comprising service requests from consumers and bids from service professionals based on the service requests, wherein generation of the training set comprises:
establishing an empty training set data structure;
retrieving, from a database, a plurality of service requests R and bid data B(R) comprising bids b associated with the service requests; and
for each service request R in the plurality of service requests:
for each bid b in the bid data B (R) associated with the service request R:
adding to the training set data structure an entry comprising the service request R and the bid b; and
send, to the consumer computing device, fourth data indicative of the estimate, wherein the fourth data causes the consumer computing device to display information related to the estimate.
9 . The system of claim 8 , wherein the instructions further cause the system to store the model in the memory.
10 . The system of claim 8 , wherein training of the model using the training set comprises the instructions further causing the system to apply a machine learning algorithm to entries in the training set to obtain a model M that approximates each bid b for each service request R in the training set.
11 . The system of claim 8 , wherein the selection of the service request comprises at least one of a service category selection or a specific service selection.
12 . The system of claim 8 , wherein at least one prompt for a specific service detail related to the service request is determined based on the selection by the user of the service request.
13 . A system comprising:
a processor; and
a memory having non-transitory computer readable instructions stored thereon that, upon execution by the processor, cause the system to:
receive, from a consumer computing device, first data indicative of a first input by a user of the consumer computing device, wherein the first input comprises a selection by the user of a service request;
send, based on the receiving of the first data, second data to the consumer computing device, wherein the second data causes the consumer computing device to display a plurality of prompts for specific service details related to the service request;
receive, from the consumer computing device, third data indicative of a first response to a first prompt for a first specific service detail related to the service request;
generate a first estimate for the service request based at least in part on the selection by the user of the service request and the first specific service detail related to the service request, wherein generation of the first estimate further comprises using a model trained using a training set comprising service requests from consumers and bids from service professionals based on the service requests, wherein generation of the training set comprises:
establishing an empty training set data structure;
retrieving, from a database, a plurality of service requests R and bid data B(R) comprising bids b associated with the service requests; and
for each service request R in the plurality of service requests:
for each bid b in the bid data B (R) associated with the service request R:
adding to the training set data structure an entry comprising the service request R and the bid b;
send, to the consumer computing device, fourth data indicative of the first estimate, wherein the fourth data causes the consumer computing device to display information related to the first estimate;
receive, from the consumer computing device, fifth data indicative of a second response to a second prompt for a second specific service detail related to the service request;
generate a second estimate for the service request based at least in part on the selection by the user of the service request, the first specific service detail, and the second specific service detail; and
send, to the consumer computing device, sixth data indicative of the second estimate, wherein the sixth data causes the consumer computing device to update a display of the consumer computing device to replace the first estimate with the second estimate.
14 . The system of claim 13 , wherein the display of the consumer computing device is updated automatically after the user selects the second specific service detail in response to the second prompt.
15 . The system of claim 13 , wherein a first amount of the first estimate is different than a second amount of the second estimate.
16 . The system of claim 13 , wherein the instructions further cause the system to receive, from the consumer computing device, seventh data indicative of a user confirmation to move forward with the service request for a price shown as the second estimate.