Dashboards, dashboards, dashboards! Dashboards are a hot topic within the web analytics world at the moment.
Dashboards are great because they enable you to set targets, track your progress and obtain early warnings. This is extremely important if you want to optimize your web activities on a continuous basis.
But how do you build a successful dashboard? How do you ensure relevance and impact? How do you ensure that your dashboard lead to concrete action?
The steps towards a successful dashboard
Although there are many ways of building dashboards, in my experience it always boils down to the following steps:
- Target your dashboard
- Select only the most relevant KPIs
- Visualize data as much as possible
- Include benchmarks
- Explain the results
- Make the dashboard interactive
1. Target your dashboard
Do you work for a large company with several departments? Are you the responsible for distributing updated reports to many different persons on a monthly basis?
In this case, you should first of all think about your target groups. How can the users of your dashboards be categorized according to their needs? And how can you best build dashboards that serve these different needs?
For example, you could operate with the following groups:
- Web team
- Marketing department
- Sales department
- IT department
- Top management
Each of these groups is likely to demand very different types of dashboards. The top management might want a high-level aggregate view of all web activities. The sales department might want a list of new hot leads. The marketing department might want to measure ROI of their online marketing activities. And so on.
Even if you are only building dashboards for yourself, you should think about the different contexts in which you will use dashboards.
What is the purpose of the specific dashboard you are building? Are you trying to measure the effects of the newsletter? Are you aiming to optimize the internal search field on your website?
The more focused you make your dashboard, the higher relevance and impact it is likely to have. Focus is also the prerequisite for the next step, namely to select the right KPIs.
2. Select only the most relevant KPIs
In case you don’t already know, a KPI (Key Performance Indicator) is a measurement which quantifies the success of your web activities. Given that “success” is a subjective thing (it depends on the goal you set yourself), a measurement becomes a KPI the moment you decide it to be so.
In principle, all measurements could therefore be turned into KPIs. The art, however, is to confine yourself to the most important measurements.
Web analytics includes so many interesting measurements that they cannot all be listed here. Let me instead simply say that web analytics measurements divide into the following main groups:
- Marketing KPIs which measure the effectiveness of search engines, online banner campaigns, e-mails/newsletters and other traffic sources.
- Engagement KPIs which measure the website’s ability to retain visitors, stimulate interest in content and make visitors perform certain actions
- Usability KPIs which measure the effectiveness of the website’s navigation, including the website’s search field
- Conversion KPIs which measure the website’s ability to convert visitors into customers, leads or prospects
- Loyalty KPIs which measure the website’s ability to make visitors come back often and with short intervals and to use certain functionality repeatedly
If you break down each of these main groups, you will get a very long list of potentially interesting measurements. From this long list, you should carefully choose a unique collection for each dashboard target group.
3. Visualize data as much as possible
Gestalt psychology tells us that the human mind is much better at understanding visual forms than processing raw numbers. If you want your dashboard to communicate clearly and rapidly, you must carefully consider how to apply visualization. In the end visualization can be what makes or breaks your dashboard.
Visualization of data, as I see it, is not simply about choosing the right chart for the right numbers. It is also about using colors appropriately, arranging the information in meaningful ways, putting visual emphasis on important information, using icons for warnings, exploiting space in the most efficient manner, etc.
One of the best books I have read on data visualization for dashboards is “Information Dashboard Design” by Stephen Few. Although his views are sometimes a bit extreme, the underlying principles are no doubt sound.
4. Include benchmarks
KPIs are almost useless, if they are not related to standards of good and bad values. In order to make a particular KPI stand out as good or bad, you must include benchmarks.
There are several ways of doing so. The simplest type is a static value indicating your goal. For example, such a static value can be displayed in a column graph by a straight horizontal line. In gauges, you can add color ranges – e.g. green, yellow, red – indicating good, medium and bad values.
It is also possible to work with dynamic benchmarks such as a line calculated as X % increase of the value previous year or, even more sophisticated, an error band from a linear regression. Finally, benchmarks can be calculated as average values across content sections, across the company’s websites and/or across competing websites.
5. Explain KPI trends
Benchmark is one way of providing your dashboard with “context”. Another important way is to include information which explains your main KPIs. Ideally, a dashboard should consist of a number of data visualizations which supplement each other.
Although dashboards can rarely offer exhaustive explanations, you should at least try to include the most obvious first step in an in-depth analysis. Let’s say you include a line chart showing an upward traffic trend on your website. In this case, it would be interesting to know which traffic source has contributed with most new visitors. This can be done, for example, by adding a bar chart which breaks down the traffic on sources such as direct entries, search engines, link traffic or paid-for campaigns.
Immediately the dashboard viewer will understand not only that the traffic has gone up in the last few weeks, for example, but also why this might be the case. Even if you always need to supplement with in-depth analyses, you should still think in terms of cause and effects when designing your dashboard.
6. Make the dashboard interactive
I believe it is important to distinguished between dashboards and in-depth analysis. A dashboard should enable the viewer to see all of the relevant information on a single screen. In-depth analysis, on the other hand, involves exploring data and searching for answers by applying new filters and looking at data from different angles.
The primary purpose of a dashboard is to monitor, not to analyze. Having said this, however, there is no reason for a dashboard not to support exploratory analysis. The best dashboard applications allow the viewers to move seamlessly from a passive state of monitoring to an active state of analyzing. In doing so the dashboard transforms itself into a powerful analytical application, which enables the viewer not only to see “what” is happening, but also “why”.
Here are some interactive features that I consider important to a dashboard that supports analysis:
- Global filters: The ability to remove unwanted data from the entire display
- Local filters: The ability to remove unwanted data from a particular chart
- Highlights: The ability to highlight selected segments across all of the views
- From static to trend: The ability to transform a single KPI (e.g. a gauge) into a trend line and vice versa
- More charts: The ability to quickly add or remove a chart to the display
Conclusion
Dashboards are a powerful way of monitoring websites and distributing information to different target groups. However, they can be extremely difficult to design, because successful designs require deep insight into the needs of the target groups as well as into the field of web analytics.
In this post I have given some guidelines as to the characteristics of an effective dashboard. If you have other ideas about best practices for building dashboard, please leave a comment below.
