The typical marketing dashboard enables data to be thrown onto a screen. I chose “thrown” deliberately. It may look appealing, but the viewer can be easily misled. They can feel as though they are wading through a mess of data.
Your Data isn’t clean Sir..
The dirt can be well hidden. But destructive. This makes it hard for the reader to understand the story you want to tell.
To explain…
Many dashboards emphasize their ability to include data from online sources. This source data is simply fed through to the dashboard.
Sadly this simple flow creates the problem. The data in the typical online system has many problems. These include:
- There are bits of data that should be filtered from your dashboard. Possibly from development or other test scenarios.
- Encoded names are like jargon. The names can include countries and other identifiers. These have meaning to those that manage the online system. But the marketing dashboard viewer may be a business executive. This executive doesn’t know or care about the internals of some online system. So the jargon can make viewers reject the dashboard.
- Splintered items due to case mismatch. These “duplicated items make reports useless Aggregation would make the reports readable.
Your dashboard charts don’t help readers with their real problem
Data gathering normally captures as much easy data as possible. The marketing dashboard can then show this presented at will. For example Google Analytics can easily capture every page on a website.
The data gathering may be deep as well. It may capture lots of detail. This allows the reader to segment the data.
For instance.
Google Analytics events are often labelled with the page. This means the reader knows on which page a particular event type occurred. There can be thousands of different pages on which even a single event type occurs.
Let’s suppose each time a web visitor downloads a brochure for a kettle an event is counted.
And suppose our dashboard user looks after household electrical products.
It still requires much work to make the numbers useful to our dashboard user.
1) We should be able to add kettles to all the other household electrical brochure downloads.
2) But we should also be able to see the kettle downloads on their own.
2) We should be able to exclude countries that the dashboard user isn’t responsible for.
But segmentation by page doesn’t aggregate products. And aggregating all products could include non electrical product downloads.
Geographical segmentation of viewers doesn’t precisely match responsibility for marketing in Southern Europe. The former is about the location of the potential consumer. The latter is about the location of the vendor. With easy global distribution of products we cannot assume these two are the same.
So our dashboard user has several nasty choices. None really address the precise problem the reader has.
The more we leave the user to do, the less likely it is that the dashboard will help answer their real questions. We relegate the dashboard to “interesting.. but not crucial”.
Your Data hasn’t been polished prior to display on the dashboard.
The example above shows how much we have to manipulate data to make it crucial information for the user.
Bad compromises result when the data doesn’t match what the user needs.
A dashboard can allow the user to segment and manipulate data. Yet this forces the senior manager to become an analyst.
I believe this is an abdication of responsibility on the part of the dashboard provider. Is the dashboard vendor just hoping that the consumer won’t notice?
Your dashboard doesn’t give adequate context
Dashboards often show data on a continuing trend. The dashboard user may compare this month with last month visually.
But the data has other relevant contexts. There may, we hope, have been a plan. So the dashboard should allow the user to compare the actual result against the plan.
But can every user see if it’s too far away from plan?
Think about the plane flying from London to New York. It will be off course for most of it’s journey. But the auto pilot will make sure the error is minimal. It would be a disaster if the plane ran out of fuel off the Brazilian coast.
Your dashboard doesn’t show comparators or tolerances
Any competent engineer understands the concept of tolerances. For instance diameter of each piston within a combustion engine has a tolerance. Each piston will be slightly different. But no piston can be so different it doesn’t fit into the cylinder.
It’s the same for marketing dashboards. There ought to be a tolerable deviation from plan. This enfranchises the non expert dashboard user. As a side note, the discussion of deviation is tolerable helps improve the plan. The qualitative what is good vs bad. What is better or poorer may be hard to assess.
Your dashboard assumes the user can accurately assess trend
Whilst most users have good eyesight this isn’t a good assumption. Changes in longer term trends can be difficult to see. Short term fluctuations may hide any acceleration or deceleration.
It’s like assuming that people know whether an approaching car is speeding up or slowing down. In this case the viewing angle makes a huge difference.
So the data often needs to be smoothed for the dashboard user. And manipulated. These can reveal subtle but important changes.
These changes may be important indicators of environmental changes. The effectiveness of marketing locations may be changing. Early warning of these is really helpful.
Your dashboard for marketing doesn’t relate to external objectives.
The client business has objectives. The marketing campaigns are subordinate to these. If the business executive can see a “line of sight” from a chart to a current business objective it’s much more relevant.
And if the link isn’t obvious the dashboard should state the link.
The client business has objectives. The marketing campaigns are subordinate to these. Can the business executive see how a chart relates to a current business goal? If it’s obvious the chart is much more relevant.
And if the link isn’t obvious the dashboard should explain the link.
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