Columbus, OH— It’s 2017, and we’ve come to the point where the digital and physical worlds have become one. Nearly every action we take leaves some kind of digital footprint— all these likes, views, buys and downloads leave a trail of information out in cyberspace.
Luckily for those of us who are marketers, hidden within these measurements are stories: little insights into the people we serve, who they are and what they care about.
With their every action, customers are telling us how we can better serve them.
Maybe they’re hinting that our content is confusing by exhibiting abnormally high bounce rates— or they’re telling us they need more information on disease state and treatment selection by searching for those phrases more often.
The stories that arise from these interactions point to areas for improvement and new opportunities for engagement. But when we merely measure activities at face value, it can be hard to hear these stories.
The Rise of the Data Scientist
Data science is an emerging discipline that is determined to help brands better tune into these stories. Some brand leaders unfortunately mistake the discipline as a re-branding of the IT department. They’ll nonchalantly claim “Oh yea, I have a data guy,” and point to a massive excel file with tens of thousands data points.
To do this is to ignore a fundamental shift happening in our digitally-enabled world. Marketing measurement and analytics is no longer solely about the data… it’s about tuning into, making sense of and acting on customers stories.
Insight-Driven Decision Making
Data and analytics alone isn’t as useful for decision making as we might think. Sure, it is important to understand which piece of creative got the highest click-through rate— or what the sales revenue was for 3rd quarter. But if we don’t understand why or what that means, we’re ignoring the voices of our customers and merely optimizing a small subset of our content or getting a macro view of the business.
Stories, on the other hand, activate other parts of our brains that facts or data alone just don’t engage. When we are being told a story, not only are the language processing parts of our brain activated, but any other area that we would use when experiencing the events of the story are also engaged.
Research has shown the neurological effect of this activation:
“When the woman spoke English, the volunteers understood her story, and their brains synchronized. When she had activity in her insula, an emotional brain region, the listeners did too. When her frontal cortex lit up, so did theirs. By simply telling a story, the woman could plant ideas, thoughts and emotions into the listeners’ brains.” –Uri Hasson, Associate Professor of Psychology and Neuroscience, Princeton
Storytelling is essential in creating empathy— a proven tool for improving customer experiences and a starting point for innovation. The field of data science is taking note and making a concentrated effort in leveraging its power:
“To drive impact, data scientists should tell stories that connect the macro to the micro and engage the decision maker both rationally and emotionally. As the hype of big data subsides and companies start looking for real impact to the bottom line, it behooves data scientists to become better storytellers. This is vital to drive action, not just macro education.” –Sandeep Sacheti, Vice President of Customer Insights, Wolters Kluwer Corporate Legal Services
In a changing pharmaceutical industry where business leaders want to understand return on investment and target spending to the highest-impact opportunities, tuning into these customer stories has never been more important. But are we really listening?
Hearing Customer Stories
To fuel insight-driven decision making, simply gathering data on customer interactions isn’t enough. We need to be strategic about defining what we measure, how we measure and why we are measuring it. Some feel like they need to collect as much data as they can— hoarding an endless amount of metrics about anything and everything.
Taking the ‘all data is the data we need’ approach can wash out the stories we’re listening for, turning them to white noise as meaningless numbers overwhelm the metrics that matters. The discipline to decipher the signal from the noise is increasingly relevant as more and more data becomes available with the internet of things colliding with healthcare.
Getting alignment on KPIs, clearly defining supporting metrics and structuring our measurement infrastructure are key to being able to hear what customers are trying to telling us.
Seeing Opportunities
After we’ve structured our measurement approach, we should work to engage another one of our senses. Advancements in data visualization and automated dashboards have helped us see opportunities in ways we previously could not. They enable us to find meaning and relationships between data points that go beyond statistics. Visualization helps us better understand information.
“Insights aren’t always easy to hear, but they should be easy to understand.” –Joe DeSalvo, Head of Marketing Analytics, inVentiv Health Communications
Taking Action
Once we’ve seen these opportunities, it’s time for action. Fueling our strategic processes with insights discovered from customer metrics grounds our decisions in evidence. It helps us identify what we should do and why. It can be a source of continued inspiration for innovation.
Analytics + Strategy = Better Decisions
At first, they said computers could never beat humans at chess. Then AI toppled the chess master. Now, the ultimate chess player is a human with the aid of an AI program.
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This duo combines analysis with creativity; data with neurons. We should approach strategic planning processes the same way.Why This Matters
Healthcare is changing. The blockbuster era is over. Marketing budgets are tightening and leaders are expecting their investments to go further and have a larger impact than ever before. Customers are rapidly shifting their behaviors and new models of engagement seem to be popping up every 6 months.
Measurement initiatives that don’t enable brands to understand and respond to this changing environment leaves them disadvantaged. Customers are telling us what they want, and we have to design our analytics capabilities to hear those stories, visualize opportunities and take action.
It’s easy to become complacent and claim, “Yea, sure… we gather and analyze data”. Moving beyond ‘is this working’ will require more discipline and increased dedication. But the opportunity to uncover insights that answer deeper questions about our customers and marketplace is worth the extra effort.
