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.
Marketing Optimization Made Simple
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:
- The data: What mechanisms do you use to collect digital and offline data? How complete and detailed is it? How do you ensure you own the data you generate? How do you standardize the data you collect to make it actionable?
- The analytics: Are you primarily collecting and counting data, or doing more advanced analytics such as visitor stitching, event scoring, correlation, and other statistical modeling? How mature is your multichannel attribution program?
- The visualization: How effectively do your reports and dashboards unify your multichannel data? Do you have visibility not only into the “state of the system” of your multichannel marketing efforts, but also into the “levers of change” to drive the right actions.
- The action: How personalized, targeted, and timely are the actions you take as a result of your data collection and analytics? Can they be automated across channels and platforms to drive right-time marketing?
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.
Data – The Most Objective Element
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:
- How detailed or granular is the data? Detailed data is always better than aggregated data because it can tell you about the individual consumer, rather than a generalized version of that individual. More detailed data will yield information far beyond simple counts of website visits or numbers of “likes” on a social media platform. It will instead offer information about the intersection of that one consumer with your brand platforms and create the foundation for seeing hidden correlations across all channels and platforms.
- Is the data first-party or third-party? This is not just a long-debated topic referring to online cookie data, but it is also about data ownership. First-party data will track the individual consumer across platforms visited or ads clicked. The data is key to understanding interactions on your brand’s various platforms, enabling you to create relevant omni-channel experiences – so naturally you want to own it.
- Is the data complete or locked in data silos? The ability to consolidate and integrate data from multiple sources is fundamental to conducting effective multichannel marketing. Marketers must be able to unify data generated in multiple platforms: digital applications that typically live in the cloud; internal systems like sales and finance; and third-party sources like Census Bureau statistics, reference data providers that shed light on share of shopper/share of market trends or audience ratings services. Ask yourself – are you able to identify the consumer as he or she moves from mobile or social platforms to a website or call center or to a store? Can you easily stitch those interactions together to get a picture across all platforms and channels?
Openness and Flexibility Are Key
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!
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