In this tutorial, you will get a complete overview of data analysis and dashboard creation with Bime using the Google Analytics connector. It's a lot easier than you might think; the hardest part is just getting set up.

This tutorial is designed to last 20 minutes.

First of all, create a Google Analytics connection. Fill in your Google login and password details and choose the different websites you want to analyze. If you choose several accounts, the application will aggregate information from these websites. It is possible to visualize data from different accounts, thanks to the "Profiles" attribute.

Bime is really easy to use: you just have to drag and drop dimensions and measures onto the pivot table.

Let's take a look at visitors per browser: drag the "visitors" measure in the measure box and the "browser" dimension on the column axis.

Bime provides different types of visualizations such as heatmaps, pie charts, sparklines and many more! Choose a visualization by selecting from the drop down menu as shown below.

Let's try the pie chart to analyze your visits per browser. The pie chart is great for displaying the percentage of a total.

After generating your visualization you can use some post-processing features. For instance, you already tested the "TOP" function which retrieves the first x number of results. We can now use post-processing filters (kind of masks) to only display what we are really interested in.

You can also decompose your data for a specific dimension; in this case, we will decompose visits using the Internet Explorer browser, and we’ll decompose by browser version.

Thanks to Bime, you can create your own calculated attributes and measures and edit the display format for each measure which provides you with infinite possibilities.

Create calculated attributes in a few steps and re-use these attributes when ever you need them. Let's see a quick example with the "Page Tracking: Page path" dimension. Suppose you want to know the number of visits for page paths which contain a specific text. For instance the number of visits on web pages containing the text "image".

Create calculated measures in a few steps and re-use these measures when ever you need them. Let's see a quick example with visits (time page > 15s).

You can create and use global variables. Click on the arrow next to a dimension and select "Create a global variable". Then, determine a min value, a max value and a defaut value for this variable. Just follow the last example after creating your global variable and replace timeOnPage > 15 by timeOnPage > YOUR_VARIABLE

Whenever you want to analyze different dimensions in a complex way, the Treemap could be your best friend. You can instantly see the most relevant elements, and also use the hierarchy option to sort the results (the first measure determines the size, and the second one color). That way, it really makes sense.

It's always good to finish a tutorial with a shining example. Keep your "Custom visitors" measure on the measure axis and choose the heatmap visualization. Then, put the "Visitor::City" or "Visitor::Country" dimension on the column axis and appreciate the result!

You successfully finished this tutorial! You now have a good foundation in web analytics with Bime and Google Analytics, and can start asking all sorts of questions of your web data. There are still so many features unexplored here within Bime, so don't hesitate to sign up for an account! You can also find our complete online documentation here.