We are constantly asking marketers to be more data-driven, yet often the reports or dashboards they receive don’t deliver information in a format conducive to finding actionable insights.
Leading on from our Digital marketing fails post, we’ll be discussing common dashboard mistakes that may be keeping your marketers from making optimized decisions around their data. We’ll also share some ideas on what they could do to utilize their reports at full potential. In this two-part series we’ll be talking about:
Let’s get started with part one:
When handed a report, how clear is it? Is the page full of disconnected tables and charts or does it follow a logical order? Every once in a while we come across dashboards packed with tables and charts, but lacking KPIs.
Why is this a problem? Tables and charts do give ample amounts of information, but data consumers often become lost when they receive reports full of them. However, when KPIs proceed charts and tables, the reader is able to quickly identify the main indicators affecting performance and then search for the details they need to answer why in the supporting data visualizations.
By the same token, make sure your KPIs really are key. Limit KPIs at the top of the screen to a short list to ensure you’re not overwhelming the reader with vanity metrics or useless information. By making use of tabs to divide up your dashboards in smaller bite-size portions, you’ll avoid overloading your dashboard consumer and allow them to hone in on the metrics that impact results.
This may seem a bit more nitpicky, but if you are going to go about building a comprehensive and powerful dashboard, why not spice it up a little bit? Sometimes taking an extra 5 minutes to change the background image, add logos, and of course, coordinate the color palette to match your brand will go a long way in the eyes of the dashboard consumer. After all, engaged viewers are more likely to think through what the report is presenting and make more informed decisions.
The science of colors can also be a tricky topic. Keep in mind that certain emphasis colors, such as red, will communicate a stronger negative tone than more subtle color choices. Incorporate emphasis colors: reds, pinks, or yellows, to highlight important behaviors, and standard colors: greens, blues, grays, or browns, to help dashboard consumers interpret the data easily.
Some dashboards or reports go overboard on information. They are full of so much data that it is nearly impossible to take it all in. Just as we use data visualizations to make sense of large amounts of data in a more compact and easy-to-understand format, we should do the same with our dashboards. Organize data in a logical order with tabs, and make sure the data is condensed to the only information that the dashboard consumer needs to make decisions. The longer the scroll bar grows, the less engaged your dashboard consumer is likely to be.
Ask yourself a few simple questions to determine if your dashboard and the information it contains will bring value to the consumer:
Ultimately data visualizations should only make it easier to interpret data. In order to do so, metrics and dimensions should be paired with charts that contain clear and complementary information. Unfortunately, all too often we come across ineffective pie charts in place of what could be more easily visualized in a column chart.
Recently I saw a dashboard with three pie charts, all comparing audience demographics for the organization’s three highest performing landing pages. Not only do three pie charts take up a copious amount of space, but it’s rather difficult to compare them. Whereas; if we move the data into a stacked column chart, you would be able to visualize the parts-to-a-whole data for each landing page side-by-side, thus giving the chart viewer a more comprehensive format where they can actually compare the three landing pages.
Data tables are great. They often include significant amounts of information making them a very comprehensive and complete dashboard element. Their use, however, should be limited. Infinite amounts of information and meticulous detail could be included in data tables – they can go on for days.This could, however, lead to poor comprehension and mean the inclusion of irrelevant information which may lead to marketer’s to make poor decisions or to ignore this data altogether.
Add data tables for supporting context, but consider limiting how many data tables you include per tab. Also, limit the amount of information contained in the data table. If there are 50 columns of data available, but the last 40 don’t provide any benefit to the viewer, exclude them from the final report.
On the opposite end of the spectrum, we have graphs or tables that are so full of data they are virtually impossible to read. If you are not simplifying the process of interpreting a large amount of data, then you need to set a limit.
Readers should be able to find insights quickly and not lose time (or interest) trying to decipher which line is which and how it compares to the next.
It’s just as important that we don’t trick our readers and lead them to faulty conclusions. This often occurs when truncated axes are used to deliver critical data. A truncated graph simply starts the y-axis at a point other than zero, and while this can be useful in some cases, it can also make minuscule differences look much larger than they really are.
If you want to use a truncated graph to emphasize certain minor behaviors or simply because starting at zero wouldn’t make sense, that’s ok too. If need be, add extra content to the graph to make sure your readers are aware of what insights the graph is actually conveying.
Have any of your reports been delivered with the same blunders? What other critiques could make reports or dashboards more visually appealing and easier to comprehend?
Not Another Dashboard.