Marketing Data Science — Working with Tableau | by Andreas Stockl | August 2022

Visualization of Google Analytics data


In this series of articles, I’ve written about marketing data science so far. “Use case” and “Customer Data Platforms”, and I described the typical applications of Data Science “Lead Prediction”, “Churn Prediction” and “Segmentation”. In this article, I show how to visualize Google Analytics data with Tableau.

Tableau Software is a US-based business intelligence software company. It was founded in Mountain View, California in 2003 and is now located in Seattle, Washington. Robert LaJeunesse and Stephen M. Smith, two computer science professors at Stanford University, started the company in 1999 as a commercial outlet for their research. They specialized in visualization strategies to explore and analyze relational databases and data cubes. In 2019, the company was acquired by Salesforce for $15.7 billion.

In this article, we’ll see how Tableau can be used to create data visualizations and dashboards using data from online marketing reports as an example.

We use data from Google Analytics to show some visualization possibilities in Tableau. Google Analytics is a public service offered by Google that generates detailed statistics on website visits. It also provides information about the geographical location of visitors, their sources, their language and the browsers they use. The data generated by this service is collected according to standard Internet research principles without compromising the privacy of individual users. The data that can be collected includes page impressions, time spent on the site, new visitors versus repeat visitors, where the visitor spends most of their time on the website, and many other parameters.

First, we need to connect to the data we want to visualize.

Data can be imported into Tableau using data connectors. Data connectors are easy to use, and you can import many different types of data into Tableau. You can import data from a variety of file types, including Excel files and SQL databases.

We start with an Excel file export that contains three months of web browsing data in columns, including date, number of visits, and page views. We thus choose the file with the Excel connector.

It is also possible to acquire the data directly from your Google Analytics account without exporting it. You must authenticate with your Google account, then you have access to all your Google Analytics accounts.

The Tableau user interface has two main panes: the Data pane and the Data table. Data can be dragged to the data table to generate insights. The data pane is where you can see your data before it enters the data table. The data table then displays the data graphically. Data is also created in the data table through calculations (“calculated fields”).

Data points are selected by clicking on them with a mouse or by using the cursor keys to highlight them. You can also select multiple data points at once for some analyses.

A dimension is simply a different way of organizing the data points on the data table by categorizing them. Some examples of dimensions are date, region, country, city, and browser. All data points will have a value on a specific dimension.

A measure is a numeric property of a data point on a dimension. For example, the page views per day on our website could be our measure of interest. We may use simple or advanced statistics to analyze this data table and better understand how we can improve our web browsing behavior.

Tableau provides many different charts that you can use to help you visualize data. Bar charts are used to display quantitative data, while line charts are used to show the evolution of a data point over time. By placing the “Date” dimension in the column field and the “Pageviews” and “User” metrics in the rows field, we create line plots for them.

As an alternative, area or bar charts are used: we can combine the two measures by choosing “Dual Axes” from the axes context menu.

We use a dataset with metrics from online marketing campaigns to illustrate the many types of charts in Tableau. The dataset metrics are budget, impressions, clicks, CTR, CPC, and CPM.

CTR is the number of people who click on your ad. Having a good CTR is key to getting more companies to advertise with you.

In online marketing, it is possible to see how many people have clicked on a website ad. There are numbers that show the cost of advertising for each click CPC.

CPM is an acronym that stands for ‘Cost per Mille’. It refers to the cost a company pays you for 1,000 views of their ad.

The dimensions are channel name, campaign name, start date, and end date.

With the campaign name in the column field and the budget metric in the rows field, we can build a bar chart that shows the amount of money spent on different online campaigns.

We show the number of page impressions in the different channels “Facebook”, “Adwords and “DV360” in a Piechart by assigning the dimension “Channel” to the color and the measure to the angle.

Next, we build a Gantt chart with our campaign duration. First, we create a calculated field from the start date and end date fields that contain the duration of the campaign.

A calculated field is a field made up of calculations performed on other data points. It’s like adding two numbers together, but it really doesn’t add anything because there’s no data point inside yet. The name of the calculated field will come from what you want to present in your final result. In our example: ‘Duration’.

This field is used for the size of the Gantt chart, with the start date in the column field and the campaign name for the rows. The color of the bars reflects the campaign budget.

We can create visualizations with multiple charts. In our example, we compare CTR, CPC, and CPM of campaigns with bar charts, placing the metrics in the rows file and the campaign name in the columns field.

If we have a website’s raw web tracking data, we can perform geographic analysis of visitors and page views, and display them as a map.

We achieve this by dragging the feature with the country name to the data pane. Tableau then automatically determines the longitude and latitude and draws them on the world map. If the number of page views is used to colorize a map, we get a colorized map.

Once you have gained insight into your data, you can generate dashboards for other users in your organization. In our example, we combine the Conversion Rate Barcharts with the Time Gantt Chart.

Tableau offers four versions of data visualization software. Tableau Desktop is the most popular which allows unlimited number of data sources. Tableau Public is available for free and can be published on the Internet. Tableau Server is offered with an annually paid subscription. Tableau Online is cloud-based and therefore accessible anywhere there is an internet connection.

The data visualization software offers a 10-day free trial during which it is possible to test the software to its full extent.

Tableau is integrated with the Salesforce software stack. Salesforce is a customer relationship management (CRM) platform that offers the ability to build custom apps on top of their cloud-based app platform.

Salesforce Einstein is a Data Science product from Salesforce. It consists of several modules which are Data Analysis, Data Discovery, Data Preparation, Data Visualization, Data Connector, Data Synchronization and Data Export. The tools are offered as a complementary service to the CRM platform. It has been developed with artificial intelligence that brings real-time data insights into the CRM platform.

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