How pharma can use predictive analytics for growth marketingMedSocial, San Jose, California, October 22, 2019
Pharma marketers have realized their traditional marketing approach of direct marketing and pushing people to buy their drugs is not delivering expected results. Normally they approach healthcare service providers and physicians to promote any new drug launches. So their representatives reach out to thousands of physicians who decide the fate of each drug. Convincing each physician has become increasingly difficult due to the abundance of information available on the net. So is there a way to target physicians in specific regions for a particular ailment and get better sales results?
Predictive analytics can provide insights for identifying risks and opportunities in the future. Especially for the pharmaceutical industry, a billion-dollar enterprise, advanced data analytics paves the way for transforming healthcare as we know it. With the rise of Big Data and Artificial Intelligence, pharmaceutical companies now have the power to optimize profits and create value. For example, by integrating predictive analytics in brand marketing, they can forecast sales based on their past marketing ROI data, set up marketing budget estimates for new drugs, track customer activity, perform brand reputation analysis, analyze customer lifetime value, and measure marketing ROI.
According to a Mckinsey report, pharmaceutical companies can utilize advanced analytics to increase their operating profit by 45% to 75%. A significant improvement of 15% to 23% could be realized in marketing alone by leveraging the power of advanced analytics.
Decoding the predictive power of analytics
In simple words, predictive analytics is about using existing data sets to extrapolate information for making predictions about possible future outcomes. Predictive analytics uses data analysis techniques such as data mining, machine learning, artificial intelligence to create predictive models that provide insights on identifying risks and opportunities in the future. These predictive models have the ability to bring into light many unknowns and help visualize future business scenarios.
Each predictive model is made up of a number of variables that are likely to influence a future outcome. After analyzing all the data points for relevant variables, a model is trained to generate predictions from a given set of input data. This model is monitored and as additional actual data becomes available, it is updated to incorporate the new facts and further improve its accuracy.
Why marketing pharma is different and tough
Pharma marketers cannot apply traditional marketing approaches and push people into buying medicinal drugs. Earlier they used to advertise various claims about their drugs without much justification and convince physicians to prescribe them. But now, there are regulatory restrictions on pharma brands on advertising prescription drugs on media platforms like TV, radio, internet, etc. Marketing of medicines is usually carried out by sales representatives who persuade healthcare providers such as physicians to pitch their product to patients. Therefore, in a highly regulated market such as the US, physicians decide the fate of each drug. Every year, a physician typically gets about 2,800 visits by various sales representatives. It translates to a physician being interrupted by a sales representative every single hour at work. With more patients to look after each day, healthcare providers don’t have time for sales representatives.
Predictive Physician Targeting
In the game of marketing pharmaceuticals, traditional data-driven goals focus on generating high prescription volumes and targeting specific physicians. The days of evaluating physician’s performance on the basis of monthly target spreadsheets is a passé now and brands are focussing on predictive physician targeting.Utilizing this technique allows dynamic targeting, segmentation, switch prediction, enhanced payer formulary exclusion, and many more things. Pharmacos can bank on the power of predictive analytics to estimate the market demand for a particular drug by gauging the volume of potential drug prescriptions issued by physicians and following the steps of a patient's journey.
Predictive analytics can help brands to identify who prescribes which drugs at what prices and under what circumstances. By linking what physicians hear, read, and view to what they prescribe can give brands an opportunity to improve targeting and focus their marketing efforts.
Just as a Google keywords planner helping online marketers to finetune their search engine marketing, predictive analytics can pinpoint those niches where there is low competition but a higher chance of ROI. Instead of targeting physicians who generate high prescription values, it helps identify those healthcare providers who will not be swarmed by other sales representatives.
Predictive marketing helps pharmaceutical companies to enhance the power of their CRM (customer relationship management) assets. Brands can create better buyer personas by integrating customer data from various sources. With a better understanding of a consumer, they can create an engaging experience for their consumers, instead of merely pushing generic outbound messages.
According to a research report by Genpact, predictive analytical techniques create a 24% positive business impact, since they provide an opportunity for detailed lead scoring. Brands can score every lead on the basis of their readiness to purchase, thus providing a framework for lead nurturing and conversion.
For marketers, predictive analytics offers lead segmentation on the basis of demographic and behavioral data. It also allows them to target their content in a tailored fashion and create a dialogue with a consumer. The use of predictive analytics in marketing allows companies to predict churn rate and customer buying patterns, upsell and cross-sell, understand product fit, and optimize marketing campaigns.
With the right application of predictive analytics, pharmaceutical companies can surely add value to their drug marketing approaches. It provides clues and directions which not only benefit the brands but also play a positive impact on the customer life cycle. Using the predictive power of data gives brands the power to steer their businesses more efficiently.