A web and mobile application for IOS and Android. This repo contains a report of the in-store analytics based on time inside a business geo-fence. To accurately show the user distribution, we used Pandas and Plotly to chart the duration inside in seconds. The following steps are how we collected the data from a third party back-end host Back4App.

1. Clean the data by checking to see if there are any null values.

2. Count the values from the duration column in the user_data table.

3. Sort the values in ascending order to visualize trends in user in-store activity.

Imported the following libraries to clean and visualize the data:

• Import pandas

  import pandas as pd
  

  • Import numpy

  import numpy as np
  

  • import matplotlib.pyplot

  import matplotlib.pyplot as plt
  

  Result

The results of duration analysis shows that the average time in seconds a user is inside a geo-fence is 5-6 seconds, showing that most geofence logs are user drive-bys. The graph shows that there were active user logs of over 200 logs for users that were inside the geofence between 5 and 60 seconds. See below the .gifs of the selected graphs for the report.