One of the most important things a marketer should know is how to be data-driven. Right from the beginning, they must monitor everything from the costs of acquisition, tracking funnel metrics while monitoring the rates of conversion. They are able to perform dynamic marketing by getting segments from audience date, optimizing processes through the use of behavioral data and solving issues by customers through analyzing the customer feedback data.
When looking at this perspective, they are operating with the aid of data in various ways but how can they say that they are performing in a data-driven manner as expected from marketers? What are the characteristics or habits of a successful marketer that follows the data-driven principle?
- Data-driven marketers are obsessed when it comes to data management. One must have a data management strategy and it can only be determined after a data audit is conducted. The audit can be as simple as jotting down the answers to the following – the kind of data the marketer have, knowing the origin and current whereabouts of the data and the individuals that have access to the said data. After identification of data assets, a governance policy should be made. This will cover the people responsible in maintaining the data, who can edit it and what data are made public. It is ideal for the policy to clarify who the owner of the data is and additional stakeholders are not encouraged.
- Successful marketers test their hypotheses through data and analysis without resorting to data hacking.
- A single attribution model should be used by data-driven marketers as long as highlight is given to a particular channel. If there are many channels involved, the attribution model will be a lot more complicated. This same model should be used every time in various campaigns.
- Data-driven marketers might be employing dynamic marketing that helps in their success but their relationship with the agency is as transparent as before. They must always be involved with whatever campaign data utilized. They must know the origin and how the data is used, the performance level of each segment and methods used in order to optimize the performance.