As data analytics tools become increasingly accessible, healthcare marketers need to make a concerted effort to ensure that they’re leveraging those tools to answer the right questions.
At Saatchi & Saatchi Wellness, everything we do is rooted deeply in data analytics. That said, the crux of our success is our recognition that data analyses are only useful if they’re undertaken in response to the right questions.
While the healthcare marketing industry at large has been fairly slow on the uptake when it comes to data analytics, many companies have finally started to see the light in recent years. In practice, this has involved a rush of healthcare marketers scrambling to brush up on the countless ways one can measure patient engagement in the digital sphere — a KPI crash course, if you will.
Setting aside the fact that most healthcare marketing analytics programs still gauge success based on surface-level KPIs like click-through rates, gross rating points, and survey-based intent, it’s important to understand that even the best, most penetrating analytics programs only produce tangible business value if they’re aimed in the right direction. Just as an archer who (unintentionally) hits the bullseye on a target adjacent to theirs is unlikely to win a blue ribbon, a data analyst who produces granular analysis in response to no business question in particular is unlikely to win significant market share.
To avoid falling prey to this kind of fruitless perfection, healthcare marketers need to shift their initial point of focus from key performance indicators (KPIs) to key business questions (KBQs).
This is not to say KPIs aren’t important, just that marketers should diligently select KPIs based on the KBQs which are most important to them given their brand’s lifecycle stage and position in the marketplace.
Learning to Ask the Right Questions
At SSW, each and every one of our analytics projects kicks off with an in-depth discussion about the specific strategic objectives our client wants to achieve. Do they want to increase patient starts in a certain geographic region? Do they want to build brand awareness among a certain patient group? Do they want to reduce medication non-adherence among long-time users?
A brand’s goals serve as the starting point from which analysts can begin to formulate the questions they will ask of their data. Such questions may take any number of shapes, and it’s essential to evaluate, critique, and evolve them even as they arise. For example, certain inquiries may be highly actionable, but hold little potential for meaningful business impact. Conversely, the answer to another inquiry might have the potential to transform your business — but ultimately be inactionable.
As highlighted on the priority map below, high-value KBQs are those that have a high business impact and are highly actionable. Pipe dreams, curiosities, and incremental improvements are all situationally valuable, but the brands that consistently drive meaningful results spend the bulk of their energies pursuing high-value KBQs.
KBQs First, KPIs Second
By beginning with big picture KBQs, healthcare marketers ensure that they — and their clients — don’t miss the forest for the trees. With today’s near-endless parade of martech streaming into the marketplace, it’s incredibly easy to get so caught up in the nitty-gritty details of data analysis that you forget to consider whether you’re favorite new analytics tool is actually improving outcomes.
This problem is only exacerbated by the inherent dynamism of KBQs. When a brand is preparing to bring a new product to market, it needs to ask questions that will illuminate the market niche it’s attempting to occupy — for instance, “Who are the other players in the niche and how are they presenting themselves to patients?” Once the brand establishes a foothold in the market, the nature of its KBQs will inevitably shift. Now it needs to ask questions that will help it reach a new set of patients or a set of HCPs grouped under a new GPO or IDN — for instance, “How likely is a certain type of physician to prescribe different kinds of therapies?”
At SSW, we’ve empowered brands with analytics programs built around KBQs, not KPIs. For instance, our machine learning-based predictive HCP targeting system, TrueTargetML, resulted from answering the following KBQ for various clients:
“Can we predict HCPs that are most likely to try, adopt, and remain loyal to my brand – and design a cross channel promotional strategy to drive productivity?”
TrueTargetML, can be tailored to any brand’s specific goals, whether the brand is trying to predict the likelihood of a product trial, product adoption, product loyalty, or some combination of the three.
Similarly, our medication nonadherence forecaster, LapsePredictML, resulted from answering this KBQ we found recurring across various clients:
“Can we predict patients at the highest risk of lapsing therapy, and design programs to change behavior?”
LapsePredictML, is designed to deliver highly actionable insights to mid-stage brands and late-stage peri-LOE brands alike.
Ultimately, the pivot to KBQs doesn’t eliminate the need for KPIs so much as it prevents healthcare marketers from putting the cart before the horse, so to speak. Brands need to know what they’re trying to achieve before they can select the best tool (i.e. KPI) for the job, and asking KBQs is the only way to guarantee that they pick the right tool on a consistent basis.