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Blog, Comment & Insight

For Pharmaceutical Marketing Analytics

Why AI will soon be indispensable for pharma sales teams

on Oct 16, 2019 3:09:29 AM By | Dr. Andrée Bates | 0 Comments | Sales Force Effectiveness Marketing Effectiveness
We have the technology … We can make him better than he was.  Better, stronger, faster.
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Can Artificial Intelligence Increase Sales Productivity in Pharma?

on Sep 23, 2019 4:05:21 AM By | Dr. Andrée Bates | 0 Comments | Sales Force Effectiveness Marketing Effectiveness
If your reps aren’t hitting their sales quotas, you are not alone. Timetrade report[1] that since 2007 sales quota have risen by 33% while the percentage of reps hitting their quotas has fallen by 25%. And according to Aberdeen[2], two-thirds of sales reps fail to meet their annual sales quota goal. The problem could be that they have too many tasks keeping them from actually engaging their prospects.
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16 Examples of Successful Applications of Artificial Intelligence in Pharma Marketing Part 3

Part 1 of this article can be found here. www.eularis.com/blog/16-examples-of-successful-applications-of-artificial-intelligence-in-pharma-marketing-part-1 and Part 2 can be found here www.eularis.com/blog/16-examples-of-successful-applications-of-artificial-intelligence-in-pharma-marketing-part-2  
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16 Examples of Successful Applications of Artificial Intelligence in Pharma Marketing Part 2

Part 1 of this article can be found here. www.eularis.com/blog/16-examples-of-successful-applications-of-artificial-intelligence-in-pharma-marketing-part-1 I will continue listing examples to stimulate your mind as to what can be done, and has been done, with AI in pharma sales and marketing. The examples in this article series are by far not the only ones and only the tip of the ice berg.
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16 Examples of Successful Applications of Artificial Intelligence in Pharma Marketing Part 1

I recently presented the plenary session at the ePhMRA annual conference in Warsaw. Covering how AI is transforming pharma sales and marketing, I provided examples Eularis had completed for pharma client projects.   Several of the attendees sent me emails afterwards wanting to know more about the specific examples I gave, which were as varied as our client product needs. It was interesting to learn how few of these types of applications they were familiar with, and I thought the readers of this blog would want to know about them, too.   I’ve written about many of these topics before, and I’m including those links at the end of each section in case you are interested in digging deeper into a specific topic.
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Which Segmentation Method Will Yield the Strongest Business Results for Your Brand?

Customer segmentation has always been something pharma have implemented. But until now the most common traditional approaches were either based on how much of your brand they use, or by personality profile or market research response, or by demographics, or a combination of these.
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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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