WHAT WILL BE THE BREAKOUT USE OF DATA FOR PHARMA MARKETING IN 2018?
DIRECTOR OF STRATEGIC PLANNING
Long gone are the days when a med-device salesperson only had to win over a single clinical champion. Now, value analysis committees hold the reins. Operational and financial decision-makers have more say in what gets adopted. Winning the deal requires data.
So how do medical device companies respond? Traditionally, they have not funded studies designed to show systemic cost savings. Nor have they invested in head-to-head studies to show how their product or service saves on the overall cost of care compared to the competition.
The 2018 breakthrough in data will be from medical device companies that have tapped into health-system data. They will be the ones that track patients beyond a procedure or hospital visit and compile metrics such as length of stay and readmission rates. This will require strong partnerships with health systems and may even require risk-sharing models that go beyond the typical vendor-client relationship.
Importantly, these partnerships will produce that most essential differentiator: outcomes data. In 2018, expect this to be a key difference maker for companies.
This is the age of clinical trials. It will be interesting to see how data-driven approaches to trial recruitment play a role in defining audiences for a therapy or drug. One of the biggest challenges for trials is recruitment. To solve that challenge, recruiters are identifying where patients will likely see promotional information for a trial based on who those patients or caregivers are. That goal should sound very familiar to anyone who’s ever sat through a social strategy presentation.
Potential lies in the tools those recruiters are using, which could yield insights based on larger or different data sets than what brand-side marketers have access to currently. Alternatively, the benefit could be a reduction in overall effort to get brand content in front of the correct audience. If recruitment efforts discover a Facebook group that leads to multiple enrollments, that same group could potentially be interested in a therapy indicated for the condition that trial examined.
SAATCHI & SAATCHI WELLNESS
Up until now, medical marketers have deployed data analytics as a tool of retrospection. Analytics have provided a great way for marketers to look back on what has happened, a prism through which to view — and learn from — historical behavior. But as productive as this has been, it only scratches the surface of data analytics’ potential.
As the healthcare industry continues to pivot toward outcome-based care, medical marketers need to start leveraging data in ways that can provide insight into future patient outcomes. Though they’re not a crystal ball — and shouldn’t be treated as such — predictive analytics can help marketers use all of the diverse data at their disposal to develop highly accurate, customer-level probability estimates – such as whether a particular physician will be interested in a new experimental therapy, or how likely a patient is to adhere to the treatment regimen they’ve already been prescribed.
Predictive analytics will help all healthcare stakeholders — not just marketers — ensure every patient has access to the information they need to make the right decisions about every aspect of their health and wellness.
SENIOR DIRECTOR, MARKETING ANALYTICS
I foresee three notable data and analytics uses in 2018: better data linkage, better predictive models, and more experimentation.
We already capture lots of data, but credibly linking and harnessing the collective potential of these datasets has been a challenge. Vast amounts of data exist in EHR systems, claims, user engagement, social media, search, and so on. However, they are siloed. Many partners have started addressing this situation, and I expect notable progress in 2018.
The data linkage will, in turn, empower building better models that reveal links between marketing stimuli, customer attributes, and context, time, and behavior change. These predictive models – using either standard statistical methods or new methods such as AI – will help guide marketers as to what messages, tactics, and context will best motivate user engagement.
Lastly, I expect more deployment of in-market experimentation and learning. Empirical marketing in the form of in-market testing and adjustments based on observed user responses remains the most direct driver of performance improvement. Pharma marketers have long envied the experimental approaches used by the tech and social media industries, and I foresee more requests and implementation of similar approaches in pharma.
DIRECTOR OF STRATEGY
If Amazon gets into the pharma game, it will be a huge disruption, with the potential to provide a powerful marketing channel to reach consumers. From a pharma perspective, it would put a treasure trove of personal and highly detailed (de-identified) patient information at their disposal.
Amazon has demonstrated its leadership in developing tech and innovative approaches that drastically change how the marketplace sells and delivers product. The company’s ability to look at the items someone purchased previously or at the contents of the individual’s online shopping cart or wish list, combined with its highly attuned predictive analytics, would give pharma unprecedented insight into patients.
For example, Amazon could recommend support books, cookbooks, particular products, and even food items for a diabetic patient that may help drive compliance and patient condition management. This vast amount of information would allow pharma to get deeper and more constructive insights to better inform and scale sets of patient segmentation and behavior than ever before, helping the entire brand experience to be more customized at the individual level.
DESTRY SULKES, M.D.
CHIEF DATA OFFICER
WPP HEALTH & WELLNESS
Linking clinical and non-clinical datasets is the next big advance for pharma marketing. Most predictive analytics in use today focus on either clinical or non-clinical data, for very different use cases.
There are many examples of both clinical researchers and pharma marketers analyzing clinical data to uncover predictors of health outcomes. For instance, when HbA1c levels trend upward over multiple years, there is a clear association with an increase in the frequency and severity of comorbidities. In parallel, marketers outside of pharma analyze non-clinical datasets to identify drivers of purchasing decisions. For example, when millennials consume high volumes of social content on mobile platforms, they tend to spend disproportionately to their income on items such as luxury gyms, healthy foods, and travel.
In 2018, we will see the beginning of pharma marketers linking these datasets to find new patterns that connect non-clinical behaviors to clinical outcomes and guide the development of the right messages, content, and channels for specific segments of clinicians, patients, and consumers.
PRESIDENT AND COFOUNDER
While mathematicians have studied AI for decades, 2017 felt like its rebirth. Suddenly, AI promises to make our daily lives better. For life sciences marketers, the AI resurgence hasn’t significantly changed how we work – but we’re getting closer. The data companies use to make sense of their customer relationships needs improvement before AI becomes a reality in this industry.
In 2018, data will drive the industry to new heights of efficiency. Real-time and accurate physician preference data will enable marketers to finally leverage AI to tailor their messages more precisely and deliver them in a more desirable manner. Marketers will better understand their customers’ preferred method of engagement, from face-to-face to phone to conferences, or virtual interaction via email, video, or websites. Companies will use this data to inform their marketing investments and sales resource deployment. So, as more life sciences companies deploy multichannel capabilities and systems that can capture better data, this could be the year AI truly takes off for pharma marketers.
VP, STRATEGY AND ANALYTICS
In 2018, traditional market research will take a back seat to data science. The fuzziness of focus groups will no longer be the primary driver of marketing decisions. The application of data science means we can get into market with greater precision, while learning and optimizing performance in real time.
Traditionally, critical marketing decisions have been based on various forms of self-reported feedback. There has always been too much room for interpretation and bias. Our confidence in the data was based more on familiarity than reality.
We are at an inflection point because of the sheer volume of data available and because it’s more connected than ever. Data science is now making all of that connected data meaningful, useful, and valuable. Predictive and adaptive modeling techniques allow us to learn from the entire market, as well as to forecast behavior, anticipate, and customize response.
For pharma marketers, the application of data science means you are:Making decisions rooted in reality; anticipating what your customer will need and do next (instead of waiting to learn what they thought); learning fast and optimizing the spend for maximum impact; and getting into market faster with more confidence
CHIEF OPERATING OFFICER
As marketers, we have been obsessively building personas and segments to abstract our audiences. These abstractions are efficient for communicating at scale and in audience acquisition, but are not authentic. And, more profoundly, they are simply metaphors for audience needs and wants, and do not enhance retention. The challenge is they do not satisfy patient and HCP expectations that we respond to them in a deeply personalized way with direct knowledge of their individual needs and wants. This is confirmed by research that found consumers expect healthcare brands to provide a brand experience comparable to Amazon or Netflix.
To craft these experiences, build stronger audience relationships, and foster lasting engagement, we must be more individualized in our targeting, and more personalized and authentic in voice and content.
The hidden insights, the very weak but extremely important signals that make this possible, are within the data. The breakout use case will be the transition from the persona to the individual, led by the emergence of dialogue-based interfaces and screenless web browsing. By 2020, 30% of all web browsing, such as searches executed via Siri or Alexa, will be screenless. Brands will craft personalized experiences using existing data and cheaply available analytical tools, such as machine learning and AI.
PRESIDENT, LIFE SCIENCES AND CHIEF CLIENT OFFICER
WUNDERMAN HEALTHThe breakout uses of data in 2018 will be data experts evolving their application of insights to create a more comprehensive, 360-degree view of customers and determine what inspires them to take action. Combined with personalization and customization, tapping into motivation and humanizing the customer journey has proven to drive a significant lift over traditional behavioral targeting marketing. Also, expect to see more AI solutions emerging next year in health and wellness marketing, especially in education, customer support, and services.
EVP, PERFORMANCE ANALYTICS AND DATA SCIENCE
CMI/COMPASMachine learning offers the missing piece that enables us to better understand what moves audiences – in real time, at the individual level. It enables us to analyze massive amounts of data in real time, and we are seeing incredible impact for our clients. We are able to use this tech to show clients which actions are working and which aren’t, identify patterns we often wouldn’t have expected or wouldn’t have seen, and pivot to be more effective as the campaign continues.
DIRECTOR, ADVANCED ANALYTICS LAB
INTOUCH SOLUTIONSThe insanity around big data, one of the most over-used and misunderstood industry terms, is over, and it’s time to get real about data science. In 2018, we’re looking forward to helping more pharmas find the stories hidden in their data that create competitive advantage.
Data science is upending the idea of segmentation. Clustering with means-based (organization by numeric averages) and other techniques, such as hierarchical clustering, is replacing the traditional waterfall segmentation process for more descriptive and relevant profiles. Predictive modeling is forecasting the future so critical marketing decisions can be made early enough to matter.
For example, we’re predicting which physicians are most likely to prescribe a drug and be the best target for a campaign. We’re calculating when patients are most likely to switch. Advanced algorithms — neural nets (mimicking brain functions), linear and logistic regression (for predicting values and determining classifications such as yes or no), and decision trees (a path with a series of yes or no decision points that reaches a conclusion), to name a few — that are taught and continually learn will be the key drivers in developing the models that find those physicians and keep those patients.
EVP, STRATEGY AND ANALYTICS
PUBLICIS HEALTH2018 will be the year of the outcome economy. To succeed, pharma companies must create intelligent service ecosystems that enable all stakeholders to work together in delivering personalized, connected interventions that generate superior health and business outcomes. These ecosystems will be fueled by a combination of data and AI, and will ultimately help both patients and their care teams make smarter, outcome-based decisions.
How? Data enables pharma brands to gain an unprecedented level of familiarity with every customer and patient. Data is the DNA of human behavior, and tells us not only what people do, but also how they think, feel, and what they value. Every stakeholder in the healthcare ecosystem has the power to capture different data, share it across the ecosystem, and transform traditionally fragmented health interventions into well-orchestrated care plans.
Data can then be fed back to each patient and their care team in near real-time in the shape of an actionable and easily digestible narrative that both informs and motivates the best decision and course of action.
This requires mining and managing a significantly expanded volume and variety of both structured and unstructured data, expanded use of AI, and advanced data-driven storytelling.
RAZORFISH HEALTHThe breakout use of data for pharma marketing will be hyper-targeted dynamic optimizations in non-personal promotion and personal channels. With the combined cry for deeper personalization and marketing efficiencies from pharma companies, it is more important than ever to enable data to eliminate waste in marketing spending – and at the same time, reach customers in a specific and relevant way.
This requires advancements and investments in data infrastructure, including a deeper integration between database analytics, tech solutions, and marketing automation. Further, although there has been a boom in data analytics and access to rich data, many pharma clients struggle with the use of data driving hyper-targeted dynamic optimization because it continues to be siloed across platforms and departments.
As we enter 2018, I expect we will see shifts in these challenges, with more pharma companies prioritizing non-personal promotion and efficiency plays. By recognizing the role data must play in personalization and targeting, pharma companies will drive stronger marketing engagements with their customers.
MANAGING DIRECTOR OF ANALYTICS
W2OPharma, not unlike almost every other industry, treats data in a silo. Applying proprietary analytics techniques that bring together data from social media, market research, and paid and owned channels can supercharge media activation. When those sources are brought together, we can develop:
- A greater understanding of our audience by leveraging real-time behavioral data from social media and applying advanced statistical techniques to understand audience interest and affinities. This leads to better targeting and better content.
- A better narrative or customer experience through the use of linguistics and correlation analysis. We can know, specifically, what the key trigger words are and what creative variables will most likely engage the target audience.
- A more effective activation plan that puts emphasis on the right channels based on the development of an analytically backed blueprint of where every target audience engages.
- A measurement program that’s centered on the audience and the funnel, as opposed to the channel-centric approach our industry has always taken.
2018 will be the year we make the idea of paid, earned, shared, and owned insights real.
MERKLE HEALTHIn 2017, pharma has shifted focus to a more digital ecosystem for HCPs, payers, providers, and customers. 2018 will begin to see the effects of pharma’s connected customer data marts and data warehouses, audience platforms, and decision-optimization tools.
Pharma giants are investing in themselves and building data solutions in-house in an effort to capitalize on first-party data, automate decision-making, and increase relevant comms that are targeted and delivered based on the insights gathered.
- Data capture will be broader, enabling pharma companies to identify key customers across multiple devices and identities.
- Measurement will be comprehensive, with added visibility into new digital channels, allowing for more accurate touchpoint attribution.
- The go-to-market strategy will be more calculated, with analytic modeling driving optimal marketing plans at the individual customer level.
- Increased focus on HCP campaigns with the ability to target and deliver based on insights gathered from actions the HCP is taking toward ingesting product information.
Data will be more connected to each individual and comprehensive of transactions across off and online activity. Pharma companies will have a complete view of customer activity, increased innovative measurement, and drive higher Rx impact.
EVP AND MANAGING PARTNER
PRECISION XTRACTThe use of quality measures to better understand payer and integrated delivery network capabilities and interests.
The development of predictive models for payer coverage that begins with an understanding of individual payer difference on an individual HCP’s prescribing behavior.
The capture of data from EHR systems to better understand the patient treatment journey, as well as the causes of gaps in care, whether it is diagnosis, treatment, or adherence.
VP OF MARKETING ANALYTICS
SYNEOS HEALTH COMMUNICATIONSA mainstay in similar regulated categories, the use of AI should see substantial growth with pharma and healthcare marketers. Employing machine learning techniques may provide a multitude of benefits – right-time patient support programs may shift to offer prediction of adherence challenges and assistance-seeking behavioral signals, as well as connect parties in the care chain (including the manufacturer). Retroactively analyzed, existing data may offer an understanding at the individual prescription experience, exploring what combination of genomic and behavioral factors relate with the best achievable quality of life.
In 2018 and beyond, we see marketing data becoming increasingly premium due to a number of factors: global data protection prioritization, growing use of ad blocking, legacy data systems, and an empowered patient audience. With data breaches becoming common news, the emergence of block-chain tech within the cryptocurrency market may offer an opportunity for the patient to take control of their own health data. As the era of personalized medicine is rapidly approaching, the use of personalized, permission-based marketing tech may allow brands that earn access to enjoy more meaningful interactions.
GROUP ENGAGEMENT DIRECTOR
HEARTBEATWe are finally on the cusp of understanding the influence of digital media placements on physician prescribing activity — in near real-time. Currently, a pharma marketer might be working with two siloed data sets — media performance metrics and prescriber habits — and having to make pretty big assumptions on how one might affect the other.
However, we’re partnering with a company that is uniting this data and enabling us to optimize campaign performance against actual HCP actions. We’ll be able to test different media mixes against different prescriber types and monitor what audience-engagement combination drives the best returns. Ultimately, marrying these disparate data sets will allow marketers to stop settling for digital media metrics (impressions and clicks) as key performance indicators and start measuring and optimizing against real-world outcomes.
INTOUCH SOLUTIONSOnce pharma marketers realize what data they’re sitting on and the infinite possibilities of how it can be used, we’ll see a revolution in applying data science in marketing. One of the most mystical aspects of data science is its power to predict. Using the right data and the right techniques, we can now predict the behaviors of many different types of customers and take appropriate action. For example, we can forecast how a payer will contract and cover a medication, how a physician will prescribe it, and when a patient might switch to or from it. We are also seeing pharma use data to create better, more customized experiences for professionals and patients alike. That’s something we can all celebrate.
VP, STRATEGY AND CLIENT ENGAGEMENT, LIFE SCIENCES
LEVLANEA few years ago, the buzz was all about big data – but this was never about the size of the data, it was about the value. The value of the data to effectively and efficiently outmarket your competitors. Four simple steps derive the value of marketing data: planning, aggregation, refinement, and optimization.
Many people think data planning is about achieving certain benchmarks, but it’s really about building measurement into campaigns, developing a marketing hypothesis, and testing that hypothesis through the accumulation of engagement metrics and brand results. Data aggregation is not about collecting all the data. It’s about collecting the right data and building a custom decision model to support brand goals and objectives.
Data refinement is similar to insight development, which was the engine that drove brand marketing for years, but goes deeper for channel insights, content impact, timing, and offers, along with traditional looks at brand messaging.
Finally, data optimization is about ongoing marketing implementation as part of your never-ending quest for marketing perfection. The insights change the implementation and drive back to planning to allow for the testing of newly derived marketing hypothesizes.
WHAT MISPERCEPTIONS ABOUT PHARMA’S USE OF DATA NEED TO BE ADDRESSED IN 2018?
DIRECTOR, INNOVATION, LIFE SCIENCES
LEVLANESunlight takes eight minutes to reach us here on earth. We see the sun as it was, not quite as it is. It’s kind of like that with marketing data. A macro trend – for instance, the surge in “best product” and “near me” mobile searches – surfaces only after a complex web of interconnected, interdependent events drives individuals to adopt new behavior patterns with sufficient frequency or intensity to move the needle.
So we see the result of these complex processes, the aggregate of millions of micro-moments, after the really interesting stuff has happened, and we’re already playing catch-up. That’s what happened when the world suddenly moved to mobile devices. People were pretty cavalier about creating mobile experiences in our industry around 2010-2011. Available data showed modest mobile traffic to typical branded properties, and mobile was still a bit of a novelty to many. We know how that worked out.
We’re in a similar spot now. Consumer-fronting ambient computing devices and systems are reaching the sophistication and scale needed to reshape marcomms. Sensors are replacing screens. It just hasn’t shown up in your engagement data yet.
PRESIDENT AND COFOUNDER
VEEVA SYSTEMSOne common misperception is that more data is better. As consumers, we are swimming in data created by our shopping, shipments, machines, appliances, and even our bodies – and it’s hailed as unleashing limitless potential. So it’s easy to get excited about the volume of data available today and its potential to make the world a better place.
However, for pharma marketers, “bigger” data isn’t necessarily better. Competitive advantage is driven by clean and meaningful data, not the volume of information available. With reliable, relevant data, companies can intelligently analyze it so it becomes more valuable.
The other misperception is that AI alone can improve performance. AI depends on two things. First, the data analyzed must be relevant and accurate. Second, the insights from AI must be delivered to systems and people who can make it actionable. The life sciences industry needs to invest upstream in the right data sources and downstream into insight delivery tech to make AI meaningful and an important reality.
INTOUCH SOLUTIONSThere’s been an incredible amount of hype around data, AI, chatbots, and the like. Some of the hype is deserved and some is absolutely overdone. I fear a number of marketers are discounting the buzz around the use of data due to the buildup. But data is more than a trend. It’s more than a chatbot. This is a new way of marketing. And if marketing leaders aren’t figuring that out by now, they’re already behind.
EVP, STRATEGY AND ANALYTICS
PUBLICIS HEALTHMany healthcare brands operate under the assumption that, due to HIPAA regulations, they can’t use data in the same way consumer brands can. They believe HIPAA regulations prevent the healthcare industry from implementing people-based marketing or the practice of identifying and communicating with specific individuals across screens and devices, rather than with personas or segments.
But that’s not true. With the proliferation of data and advancements in identity resolution and management, we can now obtain millions of data points from first- and third-party data sources about each consumer. HIPAA-protected data can be matched and modeled to provide both deterministic and probabilistic health insights. It’s possible to identify and target patients who are undiagnosed with a rare disease, know when a patient’s disease is progressing, communicate with them during the short time period they are considering their next course of therapy, and know what content they will care about most.
People-based marketing is not only viable – it’s also critical. A people-based approach is important because it enables brands to understand their consumers in a way never before possible by using person-level data to stay relevant across the entire patient journey. The more brands know about their patients as people, the more they can drive improvement in both revenue and health outcomes.
SENIOR DIRECTOR, MARKETING ANALYTICS
OGILVY COMMONHEALTHA key misperception of data usage in pharma pertains to personally identifiable information (PII). Many think pharma marketers access, analyze, and target individual patients with advertising, like what exists in tech and social media. Despite the expectation of full audience insight and personalization, pharma marketers have strict regard for PII. Unlike retail consumer information, patient information is not seen, and analyses are based on non-identifiable and aggregated datasets. Privacy remains very important to pharma.
CHIEF OPERATING OFFICER
We need to stop talking about gathering data and start focusing on how we’re putting data to use. We are facing an embarrassment of riches in data and analytical tools. Data is streaming in from our key communication activities. A common misconception is that the data is readily available to – and has been thoroughly analyzed by – all capable experts. The challenge is that the data is often siloed in agencies, departments, and databases.
Frequently, data is unknowingly abandoned or rots in storage because of a lack of accessibility. Marketers may not know it is available, or clear pathways for providing the raw data to agency and internal partners for deeper analysis may not exist. Although many analytical tools such as AI and machine learning have become cheaply available, there is a critical shortage of people with the talent and vision to apply them. This necessitates a broadening of our ideas about who should have access to data.
It will take several years to develop the capabilities and capacity to maximize this opportunity. Given the lag in talent and process, it is essential to aggregate and store information today so we have a sufficient pool of data once we achieve the capabilities to leverage this valuable resource.
MANAGING DIRECTOR OF ANALYTICS
W2OThere are three things the analytics industry needs to address in 2018. The first is the consistent fear we hear from marketers regarding big data and how to use it. Marketing functions do need to establish strong partnerships with IT because they can help deliver scale, but they do not need data scientists to take advantage of it, nor do they need to capture every data point under the sun.
The second misperception is that pharma companies cannot collect data on individuals and their behaviors, and use that data for targeting. There are limits to what can be collected on an individual, like in any other industry (personally identifiable information), but to assume pharma companies cannot collect data from first, second, and third-party sources for the purposes of media targeting is inaccurate.
Lastly, we need to dispel the myth that social data is only applicable for research purposes. Pharma brands can use social-listening data to develop content in real time. Even with regulatory concerns, it’s all about defining what real time means for your brand and target audiences.
SAATCHI & SAATCHI WELLNESSSeveral years ago, big data became an industry buzzword everyone was using but few people actually understood. If you’d asked five different marketers to define it, you would have received five totally different responses. AI has turned into a similarly nebulous buzzword in 2017. As a result, the tech is on the brink of tumbling into the so-called trough of disillusionment.
In order to rehabilitate AI’s reputation in 2018, marketers need to recalibrate their expectations of what AI can — and cannot — do. The most effective way to secure a robust ROI on AI-based tech is to use it to tackle very specific, well-defined business problems. All of the hype around AI has led to the mistaken assumption that it is the perfect solution to every imaginable problem, when in reality, it’s an incredibly powerful tool that is well-suited to some situations and ill-suited to others.
VP OF MARKETING ANALYTICS
SYNEOS HEALTH COMMUNICATIONSWe’ve all encountered pharma marketing that is inapplicable or showcases a medicine we don’t need for a disease we don’t have. But even more unsettling is a message that’s too accurate. With the uniquely personal nature of any data connected to one’s health, it’s easy to think pharma already tracks patients at an individual level, using data to invade everyday interactions. While engagements from data shared with pharma companies can be used to provide a personalized experience, pharma’s highly regulated nature means personal information – especially health information – is limited in its application, often resulting in sophisticated reach and awareness tactics that are poorly executed.
Regulation meant to limit the danger of misuse and misinterpretation of data may have forced disruption to come from outside pharma (23andMe, PatientsLikeMe, and Mango, among others) to become trusted sources and raise the understanding of healthcare-centric data application. In a category historically reliant on data from clinical trials, we may be missing an opportunity to raise data literacy and transparency to equip patients and caregivers to make informed decisions and be a trusted data source.
PRESIDENT, LIFE SCIENCES AND CHIEF CLIENT OFFICER
WUNDERMAN HEALTHWhile strong healthcare marketers use data to inform strategy and creative, as well as to optimize marketing performance, some shy away from leveraging data to personalize and customize preference-based content. They believe it’s too complicated, difficult, and challenging to implement within their organizations. Often, this belief is underpinned by legacy communication systems and platforms, which require infrastructure and marketing transformation, as well as organizational alignment – both to best meet the needs of customers and organizations’ business goals.
A success imperative is that organizations are themselves ready to break down their barriers to make sure data and insights flow through the organization. At the core, data is an accelerator for organizations to become the customer-centric companies consumers are expecting them to be – after all, we live in the world of Amazon. If they don’t make organizational changes to modernize roles and workflows, then the customer experience will suffer and the data harvested will not have the business impact it potentially could.
DESTRY SULKES, M.D.
CHIEF DATA OFFICER
WPP HEALTH & WELLNESSThe top misperception about pharma’s use of data is around data privacy and security. Today, 61% of patients with chronic ailments are concerned about their health data being used without their permission, while approximately 46% of cross-industry decision-makers agree data security is an issue for online and remote healthcare services.
Given the increased scrutiny in Europe, ongoing consumer data breaches such as at Yahoo (3 billion consumers affected), and health-related data breaches such as at Anthem Blue Cross (78.8 million consumers affected), the public is increasingly suspicious of pharma’s potential misuse of data. There is a ticking time bomb around pharma’s current uses of clinical claims and EHR datasets that are used in a HIPAA-compliant manner to create look-alike segments for consumer outreach and develop targeting strategies for HCP outreach. This could appear very creepy if suddenly unveiled out of context.
Pharma has a great opportunity to proactively showcase how its consumer and HCP outreach maintain the strictest data privacy requirements across all industries – not to mention simultaneously improve health.
Additionally, given the public’s historically low trust levels in the pharma sector and allegations industry growth is coming from price increases on old drugs (rather than real advances and new patient benefits from new drugs), there is an opportunity to clear up some misconceptions and improve trust. It is not well known that pharma companies are constantly using epidemiology and public health data to identify unmet needs and using clinical and scientific data throughout research and development efforts to address them.
Hence, pharma has a great opportunity to educate the public about the clinical and survey data used to learn which conditions cannot be treated with existing therapies, the additional data used to build AI platforms that identify molecular compounds most likely to succeed in these conditions, and the benefits of using all of this data to deliver innovative treatments and improve care.
MERKLE HEALTHThe impact of data security can be misperceived. Data should be used to inform targeted communications to consumers and physicians in a compliant manner. It’s important to work with a reliable agency that understands regulatory and brand goals to create the best outcome – data informed targeting and messaging that creates better consumer experiences.
The way data is used can also be misperceived. Data can be leveraged to better understand a doctor’s propensity to write a script in addition to the needs of patients and payers. It’s important to understand the value of Rx activity for insights to increase adherence, propensity, and patient reported outcomes.
ELEVATE HEALTHCAREThere is still a need for broad understanding that data is not a strategy. Data informs, shapes, and even helps execute a strategy, but it is never the actual thing you are trying to do.
Your strategy could be “raise brand awareness.” One way to follow it is to get information out to HCPs located within the white space of physicians. This can be done through your opt-in email list. However, if you don’t have a way to identify which HCPs opted in to receive your emails and haven’t been called on by your sales force, your email list will not help you carry out the strategy.
At that point, someone may ask, “What data do we have?” Suddenly, the focus shifts to combing through that data in order to target future messages. While that is definitely an important exercise, you can’t lose sight of the goal to raise brand awareness. That danger needs to be top-of-mind because data is easy to get lost in. Large chunks of time will fly by as data analysis continues, and you have sent zero messages about your brand out into the world.
EVP, PERFORMANCE ANALYTICS AND DATA SCIENCE
CMI/COMPASData is only meaningful and valuable if it’s used in the right context. It’s not really the data pharma has that will give it an edge, but what the industry does with it. Sharing the data with partners – such as agencies – and integrating the data and knowledge of those partners with pharma’s can only give the industry further advantage and an opportunity for more powerful actions.
DIRECTOR OF STRATEGY
DiDAre AI and machine learning the missing pieces that will allow pharma to better process and synthesize the big problem with big data?
Historically, pharma has not been the best at leveraging the multitude of inputs funneling into big data in the most meaningful ways. AI has the potential to help pharma marketers make sense of the data in more human terms, piecing together elements of the personal stories behind it and enabling them to connect with patients emotionally, at the right time, and with the right message.
On its own, AI has limitations. While it can help develop insights and solutions based on data, it is not equipped to grasp the emotional impact of decisions or understand how to act on them correctly. It cannot be ignored that medicine and healthcare are deeply connected and intertwined with emotion and understanding. People will still be an integral part of the entire process, from determining what inputs to include and helping interpret the output, to determining what numbers, algorithms, and statistical analysis cannot, keeping the “care” in healthcare.
EVP AND MANAGING PARTNER
PRECISION XTRACTThe industry must address the perception that internal IT groups or consultants are able to master payer and health system data well enough for use in critical business decisions – when they have no experience in using the data for such purposes.
This article originally appeared on MMM online