When a business idea makes the cover of Harvard Business Review, McKinsey Quarterly, and the Nottingham City Council website, you can bet it’s become a buzzword. Analytics-driven “customer insight” has become ubiquitous from business schools to board rooms.
While it’s certainly true that consumer insight will change the way an organization builds its business and customer strategies, there are limits to its operational effectiveness.
In reality, no organization can manage new “insights” every day, every week or even every month, because then they’d be reevaluating their product mix, business focus, target customer and marketing communications all the time, which besides being impractical would obviously be silly.
Insights that emerge from data are valuable to setting organizational and market strategy. This is the value of companies like ZS Associates and IMS Health that create annual or biannual studies for territory alignment or for refreshing a decile analysis for the pharmaceutical industry.
But I would argue that an equally valuable capability is operational decision support, supported by what could be called “customer intelligence.”
Insight is episodic, but decision support is ongoing
Insight-driven goals and metrics are developed for how a product, given certain business assumptions, should perform in the marketplace. Insights are distilled from market and customer data.
Insight is used to achieve differentiation. It’s critical to defining and creating value. Insight, I would suggest, is at the segment or persona level. But once the marketing strategy is determined and we know where we’re going, what our product is and who our target audience is, then customer acquisition and activation becomes the focus, driven by individual customer intelligence.
Customer intelligence is an operationalized decision support process at the individual and segment customer level. It determines messaging, targeting, channel and pacing for all of the practical weekly and monthly marketing campaign decisions.
Example of a Product Launch
For example, if I’m considering a new product launch, I’m seeking insights into unmet needs, white space, and workarounds that healthcare professionals and/or patients are managing and that my product could address in a unique way. I’ll use insights about the therapeutic environment, existing and future competition, payer and PBM expectations, and the needs of healthcare professionals to create my product positioning.
But once I’ve determined the positioning and I’m beginning to prepare my pre-launch activities, I’ll be building a multi-channel strategy to gather and analyze usage data at the individual customer level to manage my communications.
Insight will define the product positioning strategy, but intelligence will help me win in the day-to-day market competition.
Drawing a Clear Distinction between Art and Science
As we think about big data and marketing insight, it’s helpful to draw a clear distinction between insight (used for competitive positioning) and customer intelligence (multi-channel-based insight at the individual customer level that helps us make decisions around targeting and messaging channels).
To me, insight is the art of marketing, and customer intelligence is the science. We use insight to create hypotheses about the true value drivers or unmet needs in a particular marketplace. In many ways, the process is creative, personal and subjective. The best marketers use their intuition, experience and pattern recognition to glean unique insights from the data that will differentiate a product in the marketplace.
As marketers, we make certain brand-related channel and media assumptions, but then we need to use science to measure how people respond and then use that data to make adjustments. These marketing adjustments aren’t at the insight level. You’ve already asked, “What is our market?” or “Do we have the right product?”
These marketing decisions are based on a more defined set of customer criteria. “What segment is this particular doctor in, and where is she on the adoption path to becoming a regular prescriber? What does the data tell us about her channel preferences and content needs?”
Insights come from data at the segment, persona or category level and are used to understand our broad market opportunity.
Individual consumer-level data is about how we’re reaching a specific person or group of people with our product and marketing strategies.
Customer access is the result of executing well on both fronts, but marketing intelligence gives us the operational decision support for how we talk to a specific healthcare professional in a way that earns our right to access.
Why is this important?
Knowing the different between insight and decision-support is important when setting expectations with internal teams and with external agencies.
For example, a brand’s AOR is typically responsible for initial branding, positioning and messaging, but they are seldom equipped to manage customer-level intelligence or make operational decisions about changes in channel and messaging.
To sum up, insight happens at a strategic level, and is really about defining product differentiation, the unique value proposition and the segment of the healthcare professional audience we will target.
But at the operational level, intelligence earns you the right to access. It shows you what audiences need what message through which channel – in a consumable way that enables healthcare professionals to practice better and enhance the relationship between physician and patient.
Individual, multi-channel customer intelligence will deliver the access you ultimately need to successfully market and sell a product in the marketplace.