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Blog, Comment & Insight

For Pharmaceutical Marketing Analytics

How to Use AI to Create Value for Physicians, Not Just Target Them

You may have read my blog about predictive precision targeting and how, by using big data and Artificial Intelligence, we can identify which physician has the potential to write a script for your product this week (or even today), which physician has the highest potential number of patients who need your product and even which physician is a priority to see this week.
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How to Avoid Cannibalization in a Product Portfolio and Supercharge Your Results

Many of our clients have a challenge. They have multiple brands with the same indication and more coming through in their pipeline. To maximize business results, it is critical that each of these products occupy their own clearly defined space within the indication and not cannibalize the biggest product in the portfolio. But how do you know which market space is the right one for each that will maximize sales, and how do you understand how the market dynamics are being changed by the new entrants?
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7 Ways to Predict Whether Your AI Initiative Will Fail

Are you confident that your initiative will succeed? Most pharmaceutical companies we come in contact with are enthusiastically adopting AI for elements of their work – be it in discovery, R&D, clinical trials, regulatory, market access, or sales and marketing. Many pharma executives are aware that AI will disrupt pharma business but they are not sure how to ensure that their business is positively disrupted. In order to succeed, AI initiatives must be planned and executed effectively. Choosing a supplier is only the first step in achieving a successful scalable project. Assuming that a large company will achieve a good solution may not always be the case.
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Applications of AI in Rare Disease

Every year more companies enter the rare disease space due to heavy competition in the larger disease area and a faster path to market due to smaller trial sizes needed and greater precision medicine treatments of the conditions in smaller targeted populations. Rare disease is classified as being a rare disease when it affects fewer than in 1 in 2000. Although over 7000 rare diseases have been identified, for the majority of these, no treatment is available. Many of these are from childhood and persist throughout the life of the patient (whether that life is short, or long).
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Boosting results using AI for multi-channel resource allocation

Traditionally pharma sales reps selling to physicians was the largest slice of the sales and marketing pie but this has been shifting to a more integrated multi-channel approach. The challenge for many pharma marketers however, has been the constant addition of more and more channels to the pie, but not an addition of budget. So how should I marketer decide on where and how much to spend their allocations across the channels without wasting any of their budget and spending the right amount where it needs to be?
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Can You Find Your Patients? Using AI for Faster Patient Identification and Treatment

Artificial Intelligence is a valuable tool to aid pharma in both finding where their patients are (which physician) and aiding the physician in faster diagnosis if the condition is one that is more difficult to diagnose.
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How AI Is Changing the Pharma Sales Force Model

Pharma sales reps historically have faced numerous challenges. Access is difficult with a recent survey showing that 49% of physicians placing moderate to severe access restrictions (up from 45% in 2013)[1]. This access situation continues to get worse due to factors such as physicians simply having less time, physicians being part of a larger integrated healthcare group, the Affordable Care act shifting away from a fee for service to a value/outcomes model, the implementation of the Sunshine act, and physician convenience.
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Are Alexa and Siri the Future of Data Analytics in Pharma Marketing?

Pharma marketers have access to more data than ever before. Big data can bring together patient registry data, social media data, claims data, sensor data, CRM data and a wide array of other big data sets. And technology has advanced to be able to sort through this vast information.
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Using Artificial Intelligence to Improve Patient Adherence Results and Patient Outcomes

Pharmaceutical companies spend a significant percentage of their marketing budgets to capture initial market share. Since the majority of spend goes towards attracting new customer, efforts at retaining existing customers are given short shrift, with a paltry percent of budgets focused on these. By focusing mostly on new customers, companies are missing a valuable opportunity to increase sales and market share.
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Predictive messaging, Big data & Artificial Intelligence: how to personalize multi-channel pharma marketing

People make decisions quickly online. They are bombarded with content and messages and so if your message is not right for them at that point in time, the journey you are aiming to lead them on will not be started. The marketer has numerous channels to utilize for their various messages but each customer will need different focus from the messages, and different channels to go through in a different sequence to be most engaged and get to believe in and become loyal to your brand faster.
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