Consumer engagement and the power of nontraditional data.
The journal Health Affairs estimates that the U.S. spends nearly $500 billion annually on pharmaceutical treatments. Focusing on clinical value alone isn’t enough to meet business growth targets — customer experience plays a critical role in long-term brand success.
But experience doesn’t occur in isolation: To win trust and boost spending, pharma brands must use data to drive consumer engagement.
This isn’t a revelation — traditional data sources form the core of many healthcare marketing efforts. To capture consumers’ interest where, when and how they live, it’s critical to ask the right questions, find the right sources and deliver drug discovery insights at speed.
“It’s critical to ask the right questions, find the right sources and deliver drug discovery insights at speed.”
Ask and you shall receive
The sheer amount of data available — including clinical outcomes, patient profiles, social determinants of health and other critical health data — creates a unique problem for pharma companies: It’s far too easy to cast too wide a net or to miss the mark with overly specific marketing efforts.
Healthcare and life science companies need to start with the big questions: What are the desired business outcomes? What are the targeted market segments?
From there, they must narrow the focus of their inquiries to determine the key characteristics of potential buyers, what drives their decision to purchase and how competitors are performing in the market.
General questions help define sharper queries, and sharper queries increase target specificity and brand success in the marketplace. They also reveal critical gaps and help set the boundaries for what organizations may be open to discover while creating critical opportunities for nontraditional data sources.
“Ninety percent of healthcare professionals are now incorporating wearable data into treatment.”
Consider the emerging use of wearable data in healthcare delivery. A survey conducted by the Healthcare Information and Management Systems Society reported that 90 percent of healthcare professionals are now incorporating wearable data into treatment and management workflows for issues such as diabetes, hypertension and smoking.
For pharmaceutical companies, analysis of nonidentifiable data from wearables could drive marketing efforts for anti-smoking campaigns. By pairing this data with information on known stresses, companies could better target addiction-management product marketing to maximize impact.
Weather is another example. Even small changes to local weather can “make demand for a product spike or disappear or make an advertisement effective or irrelevant,” Forbes writes.
But what does this mean for healthcare? As the Mayo Clinic notes, people plagued by migraines report that changes in weather — such as high humidity or pressure or extreme temperatures — can trigger migraines.
Through IBM’s cognitive capabilities, we’ve uncovered research that suggests migraine headaches could also be triggered with a certain radius of lightning strikes. This is the specificity that is required to engage people where they have the greatest need.
The need for (variable) speed
What do wearable data and weather data have in common? They’re both (nearly) real-time sources. That’s the key value proposition of many nontraditional data sources — and, in many cases, what holds them back.
“To solve the problems posed by big data, companies need — believe it or not — more data.”
To drive consumer engagement, variable data speed is key: Companies must combine real-time information with sources that are updated regularly, often and rarely to create stable modeling profiles.
In practice, this means combining minute-to-minute weather data with weekly updates from IBM’s Explorys and monthly data from insurance claims agencies. Together, these sources produce a baseline for consumer behavior and the capability to react quickly if conditions change.
How much is too much?
Healthcare data is exploding, and the deluge of data from nontraditional sources only complicates pharmaceutical marketing efforts.
To solve the problems posed by big data, companies need — believe it or not — more data. But more data, more problems — particularly poor segmentation and results blindness.
In the case of one sleep-aid brand that worked with IBM to solve these problems, poor segmentation led to broad consumer categories that ignored key demands such as fast relief and smaller, more cost-effective product offerings. Leveraging IBM’s Watson capabilities let the company tap $23 million worth of missing value.
Another example: Using IBM’s Watson Natural Language Understanding to analyze thousands of conversations around gastric bypass surgery, analysts uncovered a phenomenon called “shame substitution” — patients who underwent the surgery looked great but still felt shame because they couldn’t lose the weight on their own.
Here, results blindness could affect pharma uptake: Outside success might not match the emotional impact.
“Healthcare organizations must leverage new data sets with speed, scale and specificity.”
Leveraging new data
Driving consumer engagement in healthcare requires pharma companies to cut through complexity by combining data at the anonymous insight layer, which will allow them to protect patient privacy and identify key pockets of marketing opportunity that are informed by real-time events and supported by existing data sets.
Traditional marketing is no longer enough. As the treatment becomes the message, organizations must leverage new data sets with speed, scale and specificity to increase sales and marketing precision.
This article originally appeared on IBM’s THINK blog and was republished with permission.
Every morning, wake up to the blog that gives you the latest trends shaping tomorrow.