Week 6

Big Picture of the GoNitely project

https://sites.google.com/a/gapps.hswlu.ch/ice2016/home/4-gonitely/week-6-final/GoNitely-BigPicuture.PNG

ICE16 Project: Pricing prediction tool

Management Summary

As part of the International Campus Experience 2016, we independently and successfully completed a project for the company GoNitely. The project was completed in the given time frame, which span from 9/12/16 to 10/21/16. This paper will solely focus on describing the results of the project. Hence, no additional context about how the project was completed will be provided.

The main result of the project is a pricing tool which is able to predict for the owner of a house the amount of expected rental income per year in any area in the USA and Switzerland. This has been done by programming a reliable pricing algorithm with Node.js. For the calculation, the owner has to input the number of bedrooms, baths and guests his/her property can accommodate. Therefore, this calculated income depends on at least these inputs. In order to get a reliable amount of the rental income we also take into account the nightly average price, average occupancy, along with a few additional factors, which won’t be published in accordance with the non-disclosure agreement (NDA).

Another result of this work is the amount of data which has been collected (and will be continuously collected!) within the project from the rental platform Airbnb. These data are (and will be) listed on the database of GoNitely. The more data it is in there, the more precise the calculation will be. GoNitely can continue collecting data with the web scrapper which is programmed in the language python.

In a few weeks (approximately two or three) the Website of GoNitely will be published and the tool which has been programmed will be one of the important instruments in order to win home owners. The tool is able to give them a precise amount of how much money they can make. Figure 1 shows our final design of the tool. You can put in for e.g. the city which in this case is “San Francisco” as well as the number of bedrooms, baths and sleeps. For the result you see the calculated amount of the income per year which is $39’155. Additionally, it shows the lowest ($17’368) and the highest ($204’759) amount of the income per year.

After six weeks of work the tool is finally developed.

So now let’s start to make money with your second home - have a local take care of it for you!

https://sites.google.com/a/gapps.hswlu.ch/ice2016/home/4-gonitely/week-6-final/MGT1.png

Figure 1 Design of the pricing prediction tool

10.17.2016

Weekly meeting with Mr. Schneider.

Finished the Management Summary

Redesign the GUI

Begin with the documentation

10.18.2016

Weekly meeting with Mr. Ghiassi and discuss our calculation.

Prepared the presentation

10.19.2016

Deployment functions of

the pricing algorithm and

running the API server from goNitely.

Bugfixes

Finished the documentation

10.20.2016

Final Skype with Markus

Meeting with Mr. Ghiassi

Finished the preparation of the presentation

10.21.2016

Final-Presentation !!!