Posts Tagged ‘big data’

Pharma Marketing: What’s the difference between Customer Insight and Customer Intelligence?

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 v IntelInsight 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.

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Filling the Digital Gap for Pharma

Whenever there is a major paradigm shift in business, there is both a capability and a capacity gap.capacity 2 Rarely do companies have the right people, and enough of them, to fulfill the demands of a new business environment.

This is particularly true of digital marketing for pharma. Pharma management is looking to marketing to build the necessary digital channels to deliver content to healthcare professionals and patients. But marketing is experiencing digital capability and capacity gaps.

Capability: “Do we have the right people to do the work?”
Capacity: “Do we have enough of the right people to do the job?”

Most digital Centers of Excellence (COE) or centralized pharma marketing operations groups are lacking in one or both.

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Four Unique Strategies for Data in Pharma

A significant share of our business focuses on data. We build and manage marketing data analytics and reporting platforms for pharmaceutical brand leaders. What we’ve learned is that this effort requires much more than just data wrangling. It also involves a commitment to nurturing the right kind of “data mindset” among our clients.

We’ve worked with numerous pharma marketing operations and centralized digital marketing teams over the past few years. As a result, we’ve developed a clear appreciation for the range of commitment levels to data analytics. Based on that understanding, we know what makes for a successful data engagement. And it starts with a minimal level of organizational readiness.

Organizational Readiness
When we are discussing a new data reporting or analytics initiative with a client, we’re looking for “organizational readiness.” Putting one’s commercialization organization on a data analytics platform involves considerable change. It introduces a new experience of marketing transparency and insight. That can threaten conventional assumptions about channels, messages, agency partners and targeting strategies.

Not every marketing organization is ready for these changes. We’ve experienced our share of difficult engagements when working with a client who isn’t ready.

Mindsets imageBut we also know what it’s like to work with committed leadership that is ready and willing reinvent their future.

We’ve begun to recognize patterns across these experiences. This has led us to identify four distinct strategies or “mindsets.” These mindsets often foreshadow how transformational a marketing data analytics initiative will be. Read Full Article Now »

The 3 Questions that Data Should Answer for Successful Pharma Marketing

In a recent posting I introduced the idea of a “master data vortex.” The one place where we gather enough data from enough customer activities to derive truly actionable insight.

If we’re only looking at one set of tactics, we’re only seeing one set of behaviors and attitudes about that channel. But what we really need is a data vortex that can suck in everything. Multiple streams of behavioral and activity data will deliver a much better representation of our customer’s DNA.

Marketing Analytics
Once we have that the data, we move on to the next step, marketing analytics. This is when we start to make informed choices. Decisions about budget investment and channel selection. Choices about how we should talk to customers, what messages to send them, and what we’re asking them to do.

At closerlook, we’ve been building a set of robust insight and analytics tools that ride on top of our “master vortex.” These tools allow us to look at a customer across all marketing channels to try to understand them better.

Who What WhenThree Questions
At the heart of the matter, all this activity focuses on answering three basic questions about our healthcare audience: Who cares? What do they care about? And when do they need to know?

Who Cares?
When we look at a population of physicians, the first question we need to ask is, “Who cares about our product?” And it’s not going to be everybody. This runs counter to the traditional marketing assumption. “If these doctors have patients that are sick with our kind of disease, then of course they’re going to care about our product.”

The reality is that not everyone does care. A physician may feel a product is too new, too redundant to what is already in the market, or too expensive. Maybe it’s a new class of drugs for which the physician was never trained. Or maybe the physician just feels a particular loyalty to a competitive product. It almost doesn’t matter. The first job of any true marketing analytics platform is to distill the entire population down to those who DO care.

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Pharma Marketing: The Heart of Software and the Face of Services

Is the future of digital marketing primarily services or software? That is of course an overly simplistic question, but it’s one I think about frequently. My conclusion? It will be both. In the future, pharma marketing has to have the heart of software and the face of services. Head and Heart 1

Not just software
It can’t be just software — we’ve seen that movie before. Companies create a software application for pharma marketing and sell it to them, but pharma marketers become frustrated because they’re not trained to manage software. Marketing doesn’t think that way.

Not just service
But pharma marketing in the future can’t just be services either, even though that’s traditionally the way it has been sold. There’s too much great data available to rely solely on creative. Read Full Article Now »

Pharma Data: Expose It to Understand, Embed It to Transform

In my last blog, I talked about the technical challenges of  getting customer data from multiple agencies all in one place. Oh yes, and the corporate culture challenges, too! Challenging but not impossible.

So now what? How do we go about making sense of this bolus of customer data? What’s the process for making data actionable? How can we help pharma brands change the relationship they have with their physician customers?

What we learned is that there are three steps to building a strategic framework.

First, expose the data and the underlying framework of customer behaviors. Second, build a predictive model based on that data. Finally, integrate the model back into the customer experience in a way that’s seamless and automatic.

Exposed Data1. Expose the Data
For decades, finding a link between advertising and customer impact was almost impossible. Direct response marketing offered a step in the right direction, but as soon as more than one marketing tactic was involved, it became difficult to attribute dollars spent to customers created.

This led to an industry-wide acceptance of marketing opaqueness. Very frustrating.

However, digital technology now underpins most marketing activities. With the ability to attribute responses from most marketing tactics to individual customers, true marketing analytics is possible. Making decisions based on truth is now possible.

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On Creating a (Healthcare) Whole Bigger than the Sum

platform, noun 1. A raised level surface on which people or things can stand.

When I think about a platform, especially in business, I imagine a foundation for building an integrated solution or a value proposition.

From an investor perspective, when a private equity firm looks at a market and sees an unmet need, they will develop an investment thesis. And from that, they will build a platform strategy.

Creating a Platform Strategy
The first thing a private equity firm does when executing against an investment thesis is to find and buy what they call an “anchor company.” Then they make a series of smaller, bolt-on acquisitions and integrate them to form an end-to-end solution that’s bigger than the sum of the parts. Efficiencies from the integration, synergies in the collective capabilities and the impact of strong leadership help create this impact.

We need more of this kind of thinking in healthcare.

Healthcare solutions can be more effective when companies partnerIt doesn’t all need to be acquisition-oriented like it is in the private equity world. Healthcare could focus on partnerships, which is often a more nimble approach. For example, pharma could partner with a mHealth app, a data analytics company, a disease management firm and a regional care center or ACO to create an integrated approach to supporting a diabetes or asthma population.

This would create a healthcare whole that is bigger than the sum of the individual products and services.

For example…
For example, four companies recently partnered to win a White House Ebola Grand Challenge to provide a “precision medicine” approach using wearable, wireless health sensors, a wireless vital signs monitoring platform and advanced analytics technology to monitor and analyze multiple vital signs of patients either suspected or confirmed to be infected with the Ebola virus. This wouldn’t have been possible if any of these companies had tried to do this on their own.

My only question is, why wasn’t there a pharmaceutical company in this partnership?

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What will make Patient Data Meaningful to Patients and Physicians?

In my last blog posting I noted that the thousands of health apps available today are beginning to generate good, accurate patient data. But just because the data is accurate doesn’t mean it’s meaningful. Especially when it collides with the real world of the healthcare professional.

There are three important issues that need to be addressed before this surfeit of personalized patient data becomes useful and meaningful to both consumers and physicians.

Data Overload
The first concern is just data overload. As patient devices become interoperable with each other and with EMR systems (a good thing), they will dump raw data, whether it’s heart rate, blood pressure, glucose level, etc. right into the physician’s office. And frankly, doctors just don’t have enough hours in a day to be able to look at and process that information.

If you follow most internists today, they’re in the office all day seeing 15, 20, even 25 patients and then in the evening they’re spending three hours reviewing their notes and lab reports or they’re logged onto their patient portal site to respond to the two dozen patient emails they received that day. We can’t ask them to now review and respond to potentially dozens of patient data streams. Read Full Article Now »

Good patient data is not always meaningful patient data

I’ve been thinking recently about some of the newer sources of health data, namely patient-generated data. My working headline is something like “Good patient data is not always meaningful patient data.”

mobile3I have the distinct sense that our rapt attention to mobile devices, mobile health, patient data, patient-generated data, etc. is all really exciting for those of us who are in technology because we love the idea of sensors and capturing data that could never be captured before and building massive databases and doing all this great regression analysis on it to look for tipping points and trends and turning it into cool graphical reports. It’s fun and exciting and sexy!

But patient-generated data often breaks down when it meets the physician. And here’s why.

There’s a tidal wave of patient generated data from apps and devices that is only increasing. When you read stats about how many tens of thousands of medical health apps there are in the Apple Store and how new devices are being launched every other week, it leads to a deluge of patient data.

Data from patient apps and devices – activity level, heart rate, blood glucose, etc. – is all “structured” within its environment, that’s good, but it’s not interoperable with any other data. This means that the data is seldom integrated with any electronic medical records system (EMR) at the physician level. That’s a problem for doctors wanting (required) to leverage these systems to interact with their patients.

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The Nature of Superpowers

I recently spent two hours in a conference room with some really smart people and three accomplished musicians from a young, innovative Chicago-based chamber orchestra called Fifth House Ensemble. We talked about the nature of the professional musician and what it takes to become world class.

The leader of Fifth House suggested that the world’s best musicians have four “superpowers” in common:

Self Knowledge

“I picked this path, and I’m committed to it.”Superpowers

Professional musician generally choose their artistic path as early as four years old. Most of the rest of us are not picking our careers when we’re that young, but the concept is still very relevant. Do we know exactly who we are, what career we’re creating, and what kind of impact we’re having in the world?

2) Self-Discipline

Musicians all over the world practice two to six hours a day every day just to maintain their skill. More practice time when they are learning a new technique or piece of music. And they do this from the time they’re four years old. It’s really good for creating muscle memory, but it does require extraordinary self-discipline to spend hours every day in a solitary practice room. This single-mindedness begins to affect how they observe and experience the world, putting much of what they see and hear in terms of music and rhythm, tone and emotion.

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