What Do Companies Need Now: Data-Driven Marketers
The more (digitally) recorded data becomes available, the more critical the collection and analysis becomes. Yet the majority of organizations still do not work data driven. And if this is the case, then analytics is an integral part of the organization of just a few companies. Let alone that marketers and other decision-makers know how to deal with it. This must be different: a plea for more data-driven marketing.
Intuition versus data
When making decisions, intuition often prevails. That does not have to be wrong. A good feeling can be formed as a result of a learning process. But usually, the gut or delusion of the day has a significant influence.
In order not only to depend on it, it makes sense to combine intuition and data in order to make good decisions. The more relevant data is available, the less you have to base your choices on assumptions. In doing so, intuition is based on accumulated experiences, and so can be seen as (un) consciously collected and stored data. Nevertheless, companies often still find it difficult to base their choices on data. T
Companies have to start using data seriously
Who does not recognize it: all those departments with their own interests, objectives and directors? They sometimes seem to oppose each other more than to reinforce each other. A company that wants to get serious with data needs to adjust the way it works.
It is not the interests and objectives of department x, y or z that are leading, but clearly defined and jointly why links departments, objectives, and interests. Data are not alone here but are integrated into processes and strategic decisions that stimulate short-cycle learning and optimization. It is not the interests and objectives of department x, y or z that are leading, but clearly defined and jointly why links departments, objectives, and interests.
So not only after a few weeks or even months the dipstick in it to evaluate results. But constantly keep a finger on the pulse to immediately adjust or intensify on the basis of the findings.
Make success measurable
An organization can not know whether it is successful unless it has determined what success is and has made it measurable. Where it goes wrong for many organizations and departments within these organizations, it is either they do not determine a goal. Or – if they have determined a goal – this is ultimately not what they actually want to measure. What makes them bogged down in reporting stand-alone, meaningless metrics.
Salient as long as the data drive of the marketers and decision makers is inadequate, these reports are often taken for granted and nothing seems to be going on.
Marketing as a fairy earner, not as a burner
What the limited data drive maintains is that companies often simply consider marketing as a cost item. Every year they donate amount x for marketing purposes, without really being asked about how that budget was ultimately spent. And what it has yielded.
As long as the company is doing well, nothing is wrong. But only when things go wrong and the results are disappointing, does management want to know how. But then it is too late, because it has not or hardly been recorded how and in what way the money was spent exactly and whether that was a good choice. Putting the finger on the sore spot is difficult.
Marketing automation is not the solution
Anyone who expects the outlined doom with the arrival of marketing automation to be a thing of the past will be disappointed. Data-driven marketing is not a machine that transforms data into bite-sized innovations, messages and reports. And pursuing more and more data makes little sense if you do not know if they do have value for your organization. What is needed are marketers who are data-driven to determine that.
What characterizes data-driven marketers?
As a marketer, you want to respond as well as possible to the (potential) customer and his or her customer journey, to ultimately promote the sale of products or services of the organization. Data-driven marketers are able to translate relevant, valuable data into meaningful insights in order to improve their marketing efforts. To realize a predetermined behavior with their (potential) client, they are adept in:
- collecting the right data
- bringing together the different data streams
- linking the necessary software systems
- finding the most important metrics
- interpreting the data
- to formulate advice based on this
- the implementation of the actions
Plan, do, analyze, communicate & act
Data-driven marketers make learning and optimizing an integral part of their working method. A short-cycle system, in which they continuously analyze and optimize, through successive processes of the “PDACA” model: plan, do, analyze, communicate and act.
- Plan: determine what you want to improve and lay down your objectives and how you measure their progress
- Do: perform the improvement
- Analysis: measure the result and test it against the set objectives
- Communicate: communicate the results of the analysis with others
- Act: adjust according to the results and insights gained
PDACA is an edited version of William Edwards Deming’s model, which is seen as the founder of modern quality control. It is a powerful method to improve the performance of an organization in a data-driven manner.
By following the circle regularly and consistently with the right data and metrics, and guaranteeing the results, an intelligent and learning organization is created. Not the gut or the delusion of the day governs, but the knowledge about the user. Data are an integral part of the development process, with each new version being tested. It is therefore important that a company knows what it wants to measure, how it will measure it and on the basis of which it assesses the result. Relevant metrics lead to informed decisions.
Data-driven marketing in practice
If a data-driven organization really wants to work and succeed with data-driven marketing, then 3 things are essential:
There must be a context and culture in which real learning, reflection, and evolution flourish. All parties involved are structurally engaged in the development. So no longer, incomplete or incorrect objectives with meaningless reports, so you do not know and clearly define what you want to achieve. And therefore can not determine what you need to know, to determine if you are successful.
Choose the right indicators
Are the objectives clear? Then make sure you choose the right indicators to demonstrate the achievement of these objectives. Make clear choices, so that there is an unambiguous goal. So not, we want to conclude so many contracts, but also generate so much reach. If contract conversion is the ultimate goal, generating x-range is only a means to achieve that goal, not an end in itself.
Conversely, if you bet on an x-range of your message, you should not pay the success of the campaign to the final (disappointing) number of contracts concluded. After all, that is not the defined goal.
Then it comes to the individual employees. Smart people who know how to ask the right questions and analyze and present data in the right context and in a reliable way. That is what companies need. Employees who understand the potential of data, but also know the limitations and can distinguish real patterns of sham patterns. In short, data-driven employees.