Industry: Anyone who has a website and/or online marketing campaignsData source: Google Analytics + Excel*
*the dashboard is composed of dummy data
Analyzing your KPIs can give your business that all important edge over your competitors. We recently built this dashboard to give users an idea for the sort of webmarketing dashboard that's possible in Bime. The data is composed of web analytics data from Google Analytics and an Excel Spreadsheet containg some financial data. We have allowed full viewer functionality on the dashboards making the dashboards highly interactive, allowing the viewer to dig deeper into the data as explained below. The images in this blog post are just screenshots, click the link below to load the full interactive dashboard.
Bringing together different data-sources
In Bime users are able to analyze several Google Analytics properties together on the same dashboard. Throughout the dashboard, on most of the visualizations, Bime has automatically aggregated the combined measures for the two different online properties on the dashboard, a domestic website and an international website. The very first visualization shows the breakdown of the total visits and how they are split between the domestic website and the international website. With a direct connector to Bime, when connecting to your data, you simply select which online properties you wish to analyze from your Google Analytics account. If you want to analyze properties from two different Google Analytics accounts, this is possible with QueryBlender, with which two or more different data sets can be merged.
We used QueryBlender to also analyze financial data which was stored in an Excel Spreadsheet and create KPIs which take data from both datasets. QueryBlender can be used to merge two datasets if there is a common measure or attribute between the two datasets. When making the dashboard we were able to link the two data sets using the common measure of date. Once we had both our financial data and our webmarketing side by side in the Bime pivot table we were able to create some calculated measures to identify some KPIs.
Bime offers several post-processing options which allowed us to measure the percent increase or decrease in bounce rate month by month. All post-processing options are found to the right of the pivot table as shown below. Post-processing options allow the dashboard creator, or the dashboard viewer (as explored later in this article) to make changes to the queries on-the-fly without having to re-query the original data set. This visualization also has dual axes. Dual axes give you the option to display two measures with two quantitative scales on a single axis (either the x or the y axis) regardless of their units. Therefore we are able to display both 'visits' and '% change in bounce rate' on a single visualization for a clear comparison of the two measures.
On the bottom half of the dashboard we have all our data regarding conversions. The 'exploded' pie chart displays how our converted customers are finding the website and also how many pages on average the converted customers are viewing, reflected in the size of the segment. The gauges represent the percentage of visitors to our websites we are converting in each of the different segments and how close we are to achieving our target of a 30% rate.
Allowing viewers to dig deeper into the data
In Bime it is possible for the dashboard owner to allow viewers to dig deeper with options to restructure the data through focus, drecompose and apply to all options. Viewers also have certain filtering and post-processing options available to them at the side of the page.
TRY THIS: POST PROCESSING To the right of the dashboard are the viewer's post-processing options. Under the years tab, click 2012 and the visualizations on the dashboard that include the measure 'years' will update to only show results for 2012.
Similarly, if allowed by the dashboard owner, viewers have the power to dig into the data with the drill down, focus on and apply to all options. The apply to all option, takes the segment you wish to focus on and re-queries the remaining visualizations using this data. For example...
TRY THIS: APPLY TO OTHER VISUALIZATIONS Click on the search traffic section of the pie chart and select apply selection to other visualizations. Bime will then re-calculate all the visualizations just based on search traffic (this may take 30-40 seconds as Bime has to re-query all the data again from scratch). Interestingly the marketing spend per search traffic conversion is much higher than general conversions. Several of our visitor metrics have also been altered.
TRY THIS: DECOMPOSE Decompose allows viewers to drill down into the data, to transform the visualzation from being defined by one attribute to another. For example as the viewer I am curious as to which operating system was used by the visitors who reached the page by searching for the keyword MySolution. To find out I can click the MySolution area on the treemap visualization, select decompose and find system: operating system.
TRY THIS: FOCUS
[one_third]Try it out with your own data now, we offer a free 10 day trial at the premium level of the solution to allow you to try out some of the features mentioned in this post.[/one_third]