Factory Analogy Bridges Analytics Gap Between CMO and CIO

CMOs are often approached by CEOs, who have a penchant for numbers, to present data that either demonstrates results or supports marketing initiatives. To satisfy the top brass, CMOs must work with their chief information officers (CIOs) and create a predictive model for forecasting sales results from marketing investments, and an analytical model for measuring the results against their predictions.

Therein lies the problem. Traditional marketing professionals are notorious for having creative minds. Collectively, many heads of marketing struggle when working with intensive analytics. This can lead to trouble when they try to speak a language that allows them to collaborate with the CIOs, who are savvy with data and analytics but can seem like human calculators.

How can marketers overcome this language barrier between the creative and the analytic? It is helpful to view marketing as a factory through which there will eventually be an output for every input. CMOs’ creative minds can more readily embrace that analogy than complex analytical models or marketing dashboards, and they can also better illustrate metrics to their creative teams.

The best-designed marketing strategic systems are ones which change the way the marketing organizations operate, allowing better capture data through all stages of the process through to lead generation. The system should include a customer relationship management process, a workflow management tool, a marketing activity calendar and enterprise reporting tool. The latter is required to build the dashboard that will provide essential information.

To create all this, CMOs must work with the heads of information systems and their teams. The dashboard should be constructed so CMOs can develop a language and methodology that can be translated into an equation the CIO can understand and manipulate. The initial discussions about the system may be challenging, but by establishing this common language, CIOs can relate to the concepts behind marketing.

Done correctly, the system should allow both CMOs and CIOs to monitor key metrics along the production cycle in order to make adjustments real-time to ensure results, rather than having to wait until the end of the cycle to know if they have been successful in achieving forecasts and goals.

Early on, CMOs and CIOs will need to establish precise definitions for every term. For example what, exactly, constitutes a lead? While everyone in the CMO’s unit agrees that a lead is a customer who has expressed interest in purchasing, is that how the system defines it? Furthermore, is what constitutes a lead an automated selection based on triggers in the system, or is it manually set by a salesperson?

The answers to these questions must be clearly defined for the CIO who builds or maintains the information systems and enterprise reporting tools. The code on which the system is written has no room for soft terms which can be defined in more than one way.

Other ambiguous terms which need to be clearly defined could include: qualified prospect; conversion ratio; marketing activity; and sales activity. All of these are vital for understanding what is happening within the marketing “factory”, which provides forecasting data for next actions and anticipated output.

After the CMO has established the model, terms and definitions, it is time to nail down the information needed from the systems. At this point, the CMO can address the metrics that will be monitored through the production cycle. For example, the CMO may need to monitor the quantity of the raw inputs into the factory (i.e. marketing activities) and the output (i.e. wins) to ensure that factory production (the marketing and sales operations) is at top efficiency.

Meanwhile, the CIO can use the same terms and definitions to translate that information and build a requirements document. The “input system” required to capture data on what is entering the marketing factory is a marketing database. The “output system” would come in the form of a CRM or order management system which ties the output back to the input.

When this system is implemented, a company’s marketing lead generation activities can expand dramatically and the CMO can make predictions regarding lead generation numbers, broken down by quarter and division. The system enables effective monitoring progresses through a dashboard weekly, monthly and quarterly. Once this shared terminology is in place, the creative soul of the CMO and the metrics-driven mentality of the CIO can find true harmony in the IT enterprise and collaboratively turn marketing from an art to a science.

Christine G.D. Schaefer is VP of marketing at DLT Solutions.