Generative AI, an Essential Tool in Pharmaceutical Marketing

Written by Carla Bellver, Manager of Business Insights at SDG Group

The Accelerated Digital Transformation and the Rise of Generative AI in Pharmaceutical Marketing

The COVID-19 pandemic had a great impact on many companies. Mainly because they were in the process of digital transformation, which was hastily accelerated by the needs of business continuity beyond the usual operational processes. This rapid adaptation led to all kinds of digital strategies to keep the consumer's attention at a time of great economic uncertainty. The marketing departments of all companies, including those of the pharmaceutical industry, went from doing all their commercial activity in person to starting out in the field of online marketing.

Traditionally, marketing departments conducted mass campaigns directed at physicians with low adoption results, as the sales force was focused on face-to-face interactions. Today, the pharmaceutical industry increasingly values personalization of contact, both in form and content, and online channels have gained more traction than ever.

In this sense, Generative AI is becoming a very powerful tool for online marketing, and is helping to deliver quality marketing campaigns while optimizing the necessary resources. According to estimates from a McKinsey study, Generative AI has the potential to contribute $4.4 trillion in annual global productivity, 75% of which is concentrated in marketing and sales departments.

In addition to the more standardized use cases that can help day-to-day operations–such as translation and adaptation of content, or campaign automation–Generative AI is making it possible to increase quality at a strategic level through different applications in the pharmaceutical industry:

Content Generation

The generation of new content usually involves many interactions with marketing companies until the final content is distributed. Artificial intelligence is helping to generate an initial carousel of ideas that can be used as a starting point, based on a simple description. Also, the generation of text to accompany the image, using text previously used in other campaigns, is making it possible to create the final content much more quickly.

Audience Segmentation

Personalization in marketing campaigns is a significant differentiator, and correctly identifying audiences and adjusting content to their preferences is key to the success of communication. To this end, SDG is working on different types of segmentation to be much more precise in interactions:

Digital Persona Segmentation

Understanding the doctor's channel or channels of preference will help the efficiency of the campaign to be a success. Using the history of all the activities carried out by the field force and applying segmentation models with advanced analytics, we can understand the type of response the doctor has had and thus group them by channel affinity. For example, when a physician receives a personalized email, engagement tends to increase. By automatically generating an email proposal including the key messages that have the highest affinity with the HCP, the marketing team gains time and effectiveness in its action.

Attitudinal Segmentation

This consists of dividing physicians into groups based on their attitudes and beliefs towards your products. This type of segmentation goes beyond demographic or behavioral characteristics and allows for an understanding of what motivates HCPs to prescribe the product. Understanding this factor allows marketing campaigns to tailor their key message more accurately. For example, one doctor may feel more value in providing information from medical studies to justify the value of a particular pharmaceutical brand, while another may empathize more with a message that focuses on the patient's wellbeing. This is the best example of the importance of specifying and getting the key message right. 

Survey Data Analysis

The free text of surveys is often not analyzed because it is very tedious and difficult to automate. AI is allowing us to process this text and transform it into analyzable feedback. The most interesting part is to be able to identify the sentiment conveyed by the respondent in their answers and thus obtain additional, more subjective information from the surveys.

2024 will be the year where many pharmaceutical companies will make the leap to Generative AI to optimize their processes and improve their marketing strategy. As data experts here at SDG, we always recommend starting by defining a roadmap and identifying the cases that can bring more value to the marketing department, for example, calculating the ROIs of each use case, in order to have clear priorities for action. This avoids making large economic investments if the expected return is not received. Finally, we recommend performing concept tests to validate the real value they add to the strategy before working with the final solution. 

Translated from original article in Spanish in PM Farma, here.