As business planners, strategists, marketers, and advertisers, we have the ability and the opportunity to understand and create connections with people, elicit responses from them, and build relationships with them. By focusing on storytelling, creativity, and messaging, we have been able to make these connections, create products, and build brand experiences.
But, a revolution in big data started in 2012, bringing with it market and organizational changes: With the influx of data now available, measuring marketing and advertising performance shifted from why something was working to focusing only on where something was working — or measuring performance strictly on a micro-focused aspect — the placement or delivery.
By neglecting the why, business planners, strategists, marketers, and advertisers miss half of the equation, and this narrowed focus is ultimately not only shortsighted, but detrimental.
the delivery ≠ the message
The use of big data, analytics, machine learning, and artificial intelligence for performance analysis can be seductive from a binary perspective, and these tools can serve perfect functions in many — but not all — areas. When these methods work properly, they can help identify patterns, remove cognitive bias, and help uncover hidden information. But as we focus on more and more data, we lose sight of the human side of things; we stop looking at why the message, creativity, or positioning resonated with people in the first place.
Data without context is meaningless.
With increased emphasis on the delivery or location of the message, it’s important to remember that if the delivery works but the messaging does not, the message will fail to connect with the target audience. The message, through its use of imagery, storytelling, and creativity, is what connects with people. Compelling experiences that engage and connect with people are what people remember; these components can truly affect people, impacting recall, consideration, and influencing action.
Using big data to track engagement, micro-interactions, and performance is important, but it will only help provide observations about the interaction. By focusing on the right data, we can draw insights and uncover opportunities. Smart data is specific, actionable information; data that actually makes sense in the real world.
observations ≠ insights
Observations can tell us what worked, where it worked, and when it worked — but they can't tell us why it worked; big data can't tell us who we connected with on a human, emotional, or psychographic level. Only smart data, and a deep understanding of consumer psychology, behavioral economics, and strategic, creative messaging can provide insights into why something is working.
No measurement tool, data point, or algorithm can factor in all the complex components of our humanity.
These mechanisms are unable to consider the impact of our past experiences, social and emotional preferences, psychological perspectives, and the internal and external influences we continually face. Moreover, these data-driven tools are not fool-proof solutions: Partial, incorrect, or irrelevant signals can skew or provide misinformation. Even worse, these systems are often incapable of removing or correcting misinformation from the equation, further skewing performance down the line.
The only way to truly understand, contextualize, and properly make use of data is to use smart, contextual, and relevant data by drawing insights from it with a human perspective.
Combining INSIGHTs and observations,
both Qualitative and Quantitative
This is not an either/or situation: Data intelligence is a powerful, valuable tool that helps enhance and inform strategy. But, it shouldn't be the sole factor in determining performance and impact. There needs to be a dynamic, delicate balance that helps humanize the information and its interpretation. Reducing decisions to data points ignores the fact that an audience is made up of individual, dynamic, reactive human beings.
A narrow focus on pure data can overlook millions of other factors; ecosystems and equations are far more complex than even the most advanced system can comprehend. To create a true differentiator in business strategy, humanize your observations, insights, research, analytics to create true insight and understanding:
Spend time researching your audience’s experience to uncover actionable insights from external viewpoints.
Adopt role-playing and mental modeling — become method actors — to see how your audience(s) views things, then probe and examine these views to gain an internal perspective.
Question available research and data, both qualitatively and quantitatively.
Perform focus group testing and user studies to understand how people think about, feel, perceive, and respond to your brand, product, or experience.
Combine your internal and external perspectives with qualitative and quantitative research.
Examine data, messaging, creative, and effectiveness from a holistic, human-centered point of view to create actionable insights.
Smart Data > big data
Leveraging data is important, but it’s even more important to interpret and humanize the information. People are complex and dynamic, impacted by innumerable internal and external factors; data alone is not enough to truly understand marketing and advertising performance.
Big Data is a broad, general phrase that encompasses a variety of angles for information capture. Large swaths of statistics and numbers bring little benefit if there is no humanized intelligence to draw from it. Smart data is specific, actionable information; data that actually makes sense in the real world. We need to understand and draw insight from all facets: Who, What, When, Where, How, and Why.
“The problem with data is that it says a lot, but it also says nothing. ‘Big data’ is terrific, but it’s usually thin. To understand why something is happening, we have to engage in forensics.”
- Sendhil Mullainathan