MMx: Transforming Pharma Marketing for the Digital Age

Introduction

The pharma industry is increasing its investment in marketing and advertising efforts, with digital ad spend alone crossing USD 6 billion in 2022 ^[1]. Research has even shown that the industry has overtaken the tech industry to become the second-largest sector for ad spend in 2023 ^[2]. With these investments on the rise, it is imperative for companies to evaluate the impact of their promotional activities. Enter Pharma Marketing Mix Modeling (MMx) – the ultimate solution for companies aiming to optimize their marketing budgets, boost product sales, and expand market share.

In this article, we will dive deep into modern-day marketing mix modeling and how it is helping pharma companies get the most out of their promotional efforts.

Marketing mix in pharma

The traditional approach to pharma marketing was largely product-centric. Physicians were seen as the key gatekeepers of sales to patients and, therefore, the most important points of focus. Direct marketing efforts mainly attempted to convince physicians through sales representatives and free samples, backed up by traditional marketing channels such as medical journals, mail, or medical conferences. There was a focus on scientific information as marketing material, targeted heavily toward healthcare professionals, peer-to-peer interaction, and providers.

Today, however, the typical pharma marketing channels also include sales force, direct-to-customer (DTC) advertising (TV, print, media), websites, social media, as well as medical conferences, and much more. The proliferation of new mediums and channels for marketing now requires the right approach to make sure that businesses get the most out of their investment. This naturally leads to advanced analytics and technological innovations such as AI and ML becoming increasingly integrated into the marketing mix. Let’s look at some of the ways a modern marketing mix is helping the pharma industry today:

1. Spend optimization on promotions: One of the primary purposes of a marketing mix is to optimize spend on various marketing activities for which promotions play a major part. A modern marketing mix should be able to provide an idea of which channels and segments in the market are delivering value, through which marketing spend can be optimized. For example, a marketing mix should be able to tell decision-makers if calls and social media ads are leading channels for physician loyalty and consequently report an ideal spend allocation plan that prioritizes these leading channels while keeping other channels and budget constraints in mind.
2. Impact measurement: Pharma companies want to be sure that their promotions will result in increased sales. A marketing mix takes historical data into account to analyze the impact of implemented promotions. Pharma companies will also be able to measure the impact at the campaign and sub-campaign levels.
3. Spend simulation: Apart from analyzing past promotions, pharma companies can benefit a lot from a marketing mix that integrates spend simulations to test the effectiveness of promotions in different channels in a controlled environment. Simulations can become increasingly important in planning for abnormal market scenarios, new product launches, and market expansions in new regions.
4. Market segmentation and resource allocation: Pharma companies must target multiple customer segments with different products and messaging within the constraints of their budget. They need to make sure that they are targeting the right areas and allocating the right amount of resources. Take, for instance, that an analysis of a company’s marketing mix reveals that TV advertisements have been very effective in the past. An effective marketing mix, then, will be able to provide optimal recommendations for budget allocation on future TV promotions by looking at their historical spend on the same, alongside the company’s current annual budget and considering notable market events and business requirements.

There are countless other ways in which an effective marketing mix modeling process and constant optimization can maximize ROI for pharma companies. However, depending on specific channels and segments being targeted, the method used may vary widely. Thankfully, marketing mix methodologies and approaches can also be incredibly flexible to any company’s needs due to the variety of possible market scenarios. A few of the methods commonly used are:

1. Regression analysis: A traditional approach to marketing mix modeling that helps quantify the impact of different marketing inputs and factors on sales and prescription behavior. It is also used in Attribution Modelling to help understand the influence of various marketing touchpoints.
2. Structured Equation Modeling (SEM): This method measures the interaction between different channels to measure the impact of marketing pathways, such as how TV ads might influence search traffic.
3. Bayesian Networks (BN): Bayesian network methodology is a probabilistic graphical modeling technique that can represent and analyze complex relationships, such as how prescription patterns and patient demographics might impact market entry for a particular product.
4. Multi-state: Also known as multi-state Markov modeling, a multi-state methodology goes beyond traditional marketing mix models by considering the various stages or “states” that a consumer goes through before making a transaction. It is particularly suited to the pharma industry due to the complex and multi-stage nature of patient and HCP decision-making.

Looking ahead

Recent years have shown that pharma companies are willing to innovate and adopt technology such as AI and ML that will push them further forward. Innovations such as Generative AI may well be the next step in the industry’s innovative process as it builds upon the data-driven approach and AI adoption that pharma companies have come to be familiar with. For example, while AI can process large volumes of HCP data to identify behavioral patterns that correlate with adherence, such as medication refill rates, appointment attendance, and online interactions, Generative AI can use the gained insight to predict which HCPs are more likely to be inconsistent in prescriptions and then enable pharmaceutical companies to proactively target interventions to those HCPs and align these changes with already existing HCP segmentation and targeting data. Employees could also easily access these insights through virtual assistants that understand natural language and generate visualizations on the fly, thanks to the capabilities of Generative AI.

Generative AI is just one example of how technological innovation can keep driving the evolution of marketing efforts in the pharma industry today. The onus is on companies to make sure they can fully harness the potential of these modern-day innovations.

Interested in learning the basics of marketing mix modeling and why it is still relevant? Check out our article on the marketing technique here.

Bibliography

[1] Lutcher, Les. “Pharma’s Digital Ad Spend Tops 50% For First Time.” Pharma’s Digital Ad Spend Tops 50% For First Time 02/28/2023, February 27, 2023. https://www.mediapost.com/publications/article/382924/pharmas-digital-ad-spend-tops-50-for-first-time.html.

[2] Taylor, Nick Paul. “Pharma Passes Tech to Climb to 2nd Place on Ad Spend Leaderboard amid Boom in Digital Promotions.” Fierce Pharma, April 13, 2023. https://www.fiercepharma.com/marketing/pharma-passes-tech-climb-2nd-place-ad-spend-leaderboard-amid-boom-digital-promotions.