Black Box Thinking for Digital Marketing Analytics
Last month I read the book Black Box Thinking by Matthew Syed, where he highlights the importance of learning from past actions, and how doing so leads to positive outcomes. The book puts emphasis on non-bias collection of data surrounding events and an organizational culture willing to frame setbacks as opportunities for innovation.
The core concepts are very much applicable to the trial-and-error approach to Digital Marketing. The low cost compared to traditional marketing makes trial-and-error attractive and viable. This strategy promotes the culture of using potential setbacks in trials as opportunities illustrated in Syed’s book.
The Importance of Analytics
But what about data collection? It’s tempting for marketing departments to start running digital campaigns without a plan to truly evaluate outcomes in order to promote innovation and measurement to company objectives. Ignoring or trivializing this step is risky and can lead to stagnation, surface-level marketing metrics, and the inability to make accurate marketing decisions.
How do you know if you fall into this trap? If you have been struggling to obtain your digital marketing goals and have not seen any traction recently, you might want to determine if data collection and reporting challenges are holding you back from pushing forward.
A good starting point is your ability to answer the following:
Can I determine how many dollars are earned for every marketing dollar spent?
It’s the hallmark question mature marketing organizations can answer. Are you able to connect your marketing spend to revenue it drives into your company? If you are unsure about the efficiency of your marketing investments, now might be a valuable time to think about building out the capabilities.
Is my marketing campaign reporting contextualized enough to produce meaningful insights?
Standalone data will not answer who, what and why. Context must exist around your essential digital marketing metrics like conversions, bounce rates and open emails to understand real performance across segments and channels over time and with campaign variations. Metrics should also be linked in some capacity to enable data story telling across things like customer touch points.
Do I receive data in a timely manner in order to make adjustments to my digital marketing programs before it’s too late?
While AI & predictive campaign management is still elusive to most organizations, being quickly reactive is the next best option. A lack of data velocity can devalue marketing reporting efforts since opportunities are normally time-sensitive.
If you are struggling to answer any of the above questions and are investing in digital marketing, it will be worthwhile to setup a quick call to chat about the state of your Digital Marketing Analytics. We enjoy exploring with our customers what opportunities exist, small or large, to enhance their capabilities.