Marketing departments are under increasing pressure to report on their activities. The obvious solution is to develop a marketing performance dashboard. But this merely begs the question of what data the dashboard should present. The answer, of course, depends on why the dashboard is being created. Broadly speaking, marketers are asked to answer three kinds of questions: What value is marketing contributing to the organization? Are marketing activities aligned with the corporate strategy? Is marketing operating as efficiently and effectively as possible? Each question leads to a different set of measures.

Return on marketing is the ultimate question, but it has no simple answer. One set of relevant measures shows the outcomes that marketing is expected to effect. These include financial results (sales, profits, cash flow, return on capital); market results (market share, consumer awareness, brand value, customer equity); and customer measures (lifetime value, satisfaction levels, retention rates, cross-purchase rates).

The other set of measures shows the marketing investments themselves. The total marketing budget itself is easy enough to report, but not very useful: there is little meaning in a ratio between total revenue and marketing expense. This is because any outcome measure reflects many factors outside marketing (most obviously, customer experience with the products and services themselves). And the effects of marketing expenditures are spread over many periods, so current results reflect the past and current activities impact the future.

Teasing apart all these factors is an exercise in advanced dynamic modeling, requiring both deep business insight and sophisticated statistical techniques. At a minimum, dashboard designers need to recognize that current activities can have only an incremental effect on current results. This means they should focus on changes in targeted values rather than their absolute levels. Realistically, dashboards need tools such as marketing mix models and business simulators to estimate the combined results of multiple marketing programs.

An alternative (or complementary) approach is to relate specific marketing activities to specific intended results - for example, matching a particular ad campaign to brand awareness goals in a particular market segment. This results in many more data points than a top-level dashboard should display, so aggregation is required. It also requires a disciplined marketing planning process to identify these relationships in the first place.

Showing alignment with corporate strategy means marketers must identify how their efforts support larger company goals. Or, more precisely, the team responsible for corporate strategy must determine what role marketing will play and work jointly with marketing to select measures that show how they are meeting objectives. For example, a corporate strategy based on selling a new electronic gadget at a high price to early adopters would include specific objectives for marketing based on awareness and customer attitudes in the target market segments. The marketing plan would include projects to achieve these goals. The strategic alignment dashboard would show spending on these projects (absolute and as a percentage of total marketing budget) and the values of target measures.

Managers both inside and outside marketing want to know that money is being spent as wisely as possible. The first step in understanding this is having an effective control system to track planned and actual activities. Therefore, one set of measures should monitor the utilization of such a system, through metrics such as percentage of marketing projects with complete data in the planning system. Because all other reporting depends on planning system data, this is more important than it may sound.

A more conventional set of measures will report on concrete marketing activities and results, such as calls made, response rates, cost per thousand mail pieces, cost per new customer and revenue by campaign. These can be calculated directly from operational statistics - in contrast to metrics such as lifetime value, which may involve quite a few assumptions. Such concrete measures are easy to grasp and less susceptible to manipulation. Managers are used to seeing and planning against them. They can be valuable monitoring tools when checked for variances against plans, budgets and similar projects.

Another set of measures tracks internal efficiency, such as staff hours to set up a campaign or number of days to execute a direct mail program. They often must be paired with other measures to avoid negative consequences: for example, pressure to reduce time-per-call in a call center can result in a decline in service levels unless the company also keeps track of customer satisfaction.

A final set of operational measures aims to show that resources within marketing are being allocated properly. Like high-level return on marketing, this requires some way to measure the long-term value of different decisions, which reintroduces business models and statistical projections. Again, tools such as marketing mix models and optimization routines must be used to identify optimal marketing decisions and to compare these with actual results. The goal at this level is to ensure that marketers adjust as quickly as possible to changes such as productive new channels or falling response rates. Suitable measures could include number of campaigns evaluated through such systems or estimated improvements in results from system-recommended reallocations. 

Register or login for access to this item and much more

All Information Management content is archived after seven days.

Community members receive:
  • All recent and archived articles
  • Conference offers and updates
  • A full menu of enewsletter options
  • Web seminars, white papers, ebooks

Don't have an account? Register for Free Unlimited Access