Marketing Optimization: It All Starts With Data!
Analytics are only as good as the data you begin with - so it's important to start with great, complete data!
Analytics are only as good as the data you begin with - so it's important to start with great, complete data!
Data has become the modern-day oracle for businesses seeking wise counsel and deep insights into the lives of their target audiences. Indeed, I sometimes think that Big Data has assumed almost mythic proportions in the minds of marketers who want to unlock the art and science of analytics to probe the hearts and minds of consumers. But you still need to start at the beginning – the quality and completeness of data. It’s that simple.
Analytics applied to poor-quality or incomplete data will fail. Visualizations based on substandard data and analytics are little more than pretty pictures. Actions taken based on these “insights” are unlikely to achieve your business goals and may even prove to be misleading. Said in the plainest terms, the quality of output depends on the quality of input.
What does this all mean to a marketing team striving to make data-driven decisions? Customers today expect highly relevant, personalized omni-channel experiences from brands, whether they are answering a smartphone promotion, responding to a campaign on Facebook, or buying through a call center.
That journey to optimize marketing begins with data.
In the past I’ve advised marketing teams to start by identifying the questions to be answered and the decisions to be supported as a foundation for determining the type of data that will be needed. Now, we are moving to a paradigm where we can collect so much multichannel data so quickly that almost any question can be answered. That makes it less important to precisely define the questions in advance and more significant to have timely access to high-quality and granular data on which to base your iterative analysis. With that in mind, let’s break down the marketing optimization process to four primary components:
As you can see, data is the most objective element in the optimization process. It is fundamental. Analytics, visualization, and actionability, which become increasingly subjective due to personal or situational choices, are all built on top of that critical layer. Regardless of your preferences for modeling or visualization tools or the motivations of your specific marketing actions, the importance of data quality to best support decisions is not really up for debate.
Let’s start, then, at the very beginning. Analytics, or the action it drives, can never be better than the data it is based on. That’s why the marketing team needs to start by evaluating the data sets. And when you do, consider these three criteria:
Once data is collected and integrated into the optimization process, analytics, visualization, and actionability layers to the puzzle are chosen on more subjective criteria related to various business and technology needs. Because of that subjectivity, openness and flexibility become critical features of effective analytics visualization and actionability platforms. Many of the big vendors have built proprietary, closed systems, which hold data hostage in silos behind firewalls and limit the tools you can use. That will not do. It’s essential to invest in open systems not just for the flexibility to use your current preferred tools and solutions, but to be able to embrace the newcomers (‘cause, trust me, they are coming!).
Yes, I could go on and on (and will do so on my next column!)…but, for now, I would like to leave you with one truism. The value of the analytics and actions is bound by the quality and completeness of the data. After all, it really does all start with data!