Digital Marketing

The objective of this project is to understand the relationship between MeetUps/informations sessions held and the visits on the website of a client. For convenience, I will refer to MeetUps and information sessions as events from now on, i.e. an event is either a MeetUp or an information session.

This client had hosted many events since its inception in 2016. The business model is such that such events are a major factor in increasing the business so it is extremely important to track the interest of the audience by tracking the traffic on the website on the day of the event and also on the days after the event. This gives an overall picture about how successful an event was and which events are more popular and attract more audience.

Here is the flow of the project:

• Get data about events with the help of Eventbrite API using Python
• Prepare data for merging and visualization
• Get data about the website traffic using Python
• Prepare this set of data for merging and visualization
• Merge two datasets and get the plot using plotly

I utilized Eventbrite to get the dates of such events.

Eventbrite is an event organizing platform where the event organizer publishes the details of an event and the targeted audience would register to attend the event.

First step was to get data from the Eventbrite API.

Here is an example in Python that shows how to get the events information from Eventbrite using the authorization token.

From Eventbrite API, it is possible to get the event title and date.

Here is the code for that:

There are 145 events in total between May 1st, 2016 and March 8th, 2018.

The actual data that we get from the API looks like this:

From the above, we need only the names of the event and the date on which it was organized. Part of the code to do so is as follows:

Next, we get data from the client’s website to find out how many people visited the website when the events were held. We get this data using Google Analytics. It is a service provided by Google to track the information about traffic on the website. Website owner can get a good idea about how well their website is performing and they can make business decisions and alter marketing strategy based on that information. More information about Google Analytics can be found on https://www.google.com/analytics/

Before accessing the Google API, it is important to run this script in the command window ‘pip install — upgrade google-api-python-client’, then download the secret file and keep it in the same folder as Jupyter notebook.

Thus, we get data for visits to the website on all the days between May 1st, 2016 and March 8th, 2018.

Now that we have data from both the APIs we can combine them and prepare them for plotting.

We need to do some data cleaning to ensure that the plot will be readable.

Using Plotly, the plot is generated as follows.

The visualization is done using Plotly and the picture below shows a small time period between May 14th and July 9th, 2017.

The numbers show the event number and when you hover over the line you can see the number of visits to the website in blue and white, as you can see on the far right.

Tableau Visualization:

For Tableau Visualization, I had to prepare a .csv file in Python.

The first step is to import the file in Tableau.

Then I have created two different sheets, one for months and another for events.

Here is an image of the sheet with the details by month.

And here is the one with details by event (The event names are converted into numbers for privacy purposes)

This is the final Dashboard where both the sheets are combined.

Summary:

Based on the analysis of data generated from Google API and Eventbrite API, it was observed that there was serge in traffic on the website immediately after the event but not necessarily on the day of the event. It was also observed that certain events (like events related to job search and career advice) were more popular compared to the other events. This information helped the client to focus more on the events which generate more traffic on their website. In future, this client would like to know more about registration detail of every event on the Eventbrite website. I would gladly do that for him for a few $$$ more.

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