Marketing dashboards are the logical result of three central developments in marketing over the last ten years:
(1) more intensive use of information by marketing managers,
(2) a trend towards the digitalization of marketing activities, and
(3) increasing pressure to justify the effectiveness of marketing measures.
A dashboard supports marketing managers in companies by helping them justify the necessity of specific measures better and earlier, promptly assess the effectiveness of chosen measures (in relation to various objectives), and illustrate the often-difficult-to-discern connection between tactical and strategic marketing goals. Insights from market research can be integrated with internal marketing and company data. However, this is only possible if the marketing dashboard used meets certain requirements.
Meaningful Selection of Suitable Metrics
Organizations use a wide variety of metrics to evaluate the functioning of their marketing. These range from market activities (relative price, advertising expenditures) to awareness or satisfaction measures (awareness, NPS®), usage behavior, preferences, and perception on specific image dimensions. Identifying the right trees in this forest is the first step. Fundamentally suitable metrics change over time (without being too volatile), can be logically linked, and are capable of predicting changes in important corporate goals early on (e.g., purchase intention, sales, relative market share). A dashboard should not contain more than 10-15 key figures to remain comprehensible.
A preliminary draft for suitable key figures in a dashboard could look like this, for example:
TESTING THE DASHBOARD
Which metrics are ultimately included in the dashboard depends, on the one hand, on data availability (or the necessary investment for regular, valid collection) and, on the other hand, on their explanatory power regarding the target variables important to the company. If the number of visitors to the hotel homepage helps the hotelier predict the occupancy of their hotel eight weeks later, if the weather forecast influences booking levels for the next two weeks, or if lower prices at the neighboring hotel on booking.com reduce my traffic on booking.com, then this information is useful. If not, then it doesn’t need to be in the dashboard. Of course, the relevant influencing factors vary for different industries and organizations. Accordingly, the potential key figures must be examined for their influence on the relevant target variables – whether with regression-analytical methods or configurative methods depends on the developer’s or user’s preference and expertise.
APPLYING THE DASHBOARD
Organizations can use their dashboard reactively – collecting, processing, and integrating information deemed important. Or (much better) actively: In some companies, the dashboard provides the basis for consciously experimenting with how the influencing factors under their own control interact with those not directly controllable: What short- and medium-term consequences, for example, do investments in Google Ads or price changes have on booking levels, depending on the prices offered by competitors or how the snow situation develops? This way, a company learns and can, as a “side effect,” also optimize its dashboard.
Ideally, an organization knows which measures to take to compensate for impending short-term losses, but also which measures are crucial for success in a month or quarter.
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