Posted: 09 Aug. 2022 8 min. read

Measure twice, cut once: AI in biopharma marketing

By Ira Haimowitz, vice president of product management, Deloitte Consulting LLP

A colleague recently peppered me with challenges biopharmaceutical brand teams often face when using digital marketing to connect with patients and health care providers (HCPs). How do brand teams know where and with whom to engage? What content will patients and HCPs see as relevant and authentic? Where should these teams invest their media dollars?

The expression ‘measure twice, cut once’ immediately sprang into my mind. This phrase encourages careful first steps to avoid extra work later. In other words, consider all the things that could go right (and wrong) before acting. The same advice applies to digital marketing: Carefully plan your data strategy and actionable metrics to maximize your promotional efficiency. Many health care and biopharma companies have been significantly increasing their digital marketing investments in recent years. In 2020, they spent an estimated $9.53 billion on digital—up 14.2% from 2019.1 However, return on investment (ROI) may be falling short of expectations, and some organizations will likely never know if their marketing dollars are having an impact. Few organizations measure their media promotion for insights that can be mined to identify strategies for improvement.

According to Deloitte’s most recent Survey of Chief Marketing Officers, only half of pharma and biotech respondents use quantitative metrics to determine the long-term impact of their marketing efforts. In addition, few biopharma industry respondents said they are investing in artificial intelligence (AI) and machine learning (ML) as part of their marketing-analytics capabilities. This gap presents an opportunity for biopharma companies to explore how AI can help measure success, address persistent marketing challenges, and engage patients and HCPs with more relevant and targeted interactions.2

When I began working for large biopharma companies in the 1990s, marketing was salesforce-driven and primary care provider (PCP)-focused. In the early days of direct-to-consumer (DTC) advertising, media agencies often negotiated mass-market and demo-based media buys for blockbuster brands. Fast forward to the 2020s, where the biopharma salesforce size is dramatically smaller, PCP access is more limited, and products are less about blockbusters and more about niche, genomics-based specialty treatments. Media buying has also changed; it is largely automated, and outcomes driven.

This dramatically transformed environment calls for sustained, omnichannel marketing, robust measurement, and greater accountability to improve reach, awareness, engagement, conversion, and loyalty. However, what consumers and HCPs often receive instead are disconnected, one-off interactions that fall short of promoting long-term brand relationships.3 In addition, many biopharma marketers have limited visibility into which efforts are most effective. Research shows that marketers typically waste 26% of their budgets on ineffective channels and strategies.4

Four common marketing hurdles

Some digital marketing efforts can result in an inconsistent or irrelevant customer experience, leading to a low return on biopharma marketing spend. Here are four common hurdles:

  • Siloed marketing and sales functions: So-called “stove pipe" patient marketing and sales functions can contribute to disconnected engagement.
  • Data access and integration challenges: Promotional data can come from a variety of sources. This can make it difficult to identify, integrate, and leverage data from impression through revenue increase.
  • Theoretical versus experiential business rules: Patient-engagement strategies are often based on rigid and simple if/then business rules. This can make it difficult to identify and optimize engagement drivers.
  • Loosely coupled decision-making and engagement layers: Omni-channel patient engagement should be tied to a robust decision-making layer that can be fine-tuned to support marketing execution.

AI could help biopharma marketers identify the most effective ways to interact with patients and HCPs by analyzing multiple data sources—including medical claims, prescription activity, payer coverage, demographics, and socioeconomics. It could also be used to re-allocate budget to the best-performing digital tactics and placements; and optimize messaging and content for personalized, ongoing relationships.5

When marketing directly to patients, AI could enable personalized, just-in-time content suggestions—backed by scientific evidence—on a patient’s smartphone when he or she enters a pharmacy or reads a medical article. When marketing to HCPs, AI could recommend relevant channels and personalized content to marketing and sales representatives.6 Post-engagement, AI-driven closed-loop measurement could help quantify how promotional efforts, tactics, and activities can lead to conversions. It could also help identify the drivers and cost data associated with these conversions.

Deloitte has been working with a leading global life sciences company that wanted to gain a better understanding of its digital marketing effectiveness, spend allocation, and the tactical combinations to help improve patient conversion. This company had been relying largely on external vendors to provide attribution insight. However, this approach resulted in some inaccurate insights because the vendors did not consider the complexity of the pharma customer’s journey. This company, which has an advanced analytics team, wanted to bring measurement back in-house and was looking for a non-black-box solution to seamlessly integrate into its existing marketing technology stack. By implementing Deloitte’s CognitiveSpark for Marketing, the company demonstrated that by re-allocating spend to high-performing channels, using only the most effective placements, and capping impression frequency, it could generate a 20% increase over baseline conversion while concurrently driving an 11% improvement in budget efficiencies.

I’m an old-school academic nerd with a doctorate in computer science and a long-held fascination with AI and health care. It’s not surprising that I would advocate the use of AI and ‘measure twice, cut once’ thinking to improve biopharma digital marketing. When integrated with a biopharma company’s existing marketing analytics system, an AI-powered engagement solution can generate knowledge and inform marketing spend across multiple channels. It can also boost precision marketing, and provide clarity, precision, and predictability for both brand teams and customers.

This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. 

Deloitte shall not be responsible for any loss sustained by any person who relies on this publication.


1 US Healthcare and pharma digital ad spending 2020, insider Intelligence Trends, Forecasts & Statistics/, September 30, 2020

2 How AI Can Help Drive Biopharma Marketing ROI?, Wall Street Journal, March 23, 2021

3 How and why the new ‘over-time’ is transforming the work f medical affairs,, April 7, 2022

4 Marketers waste about one-fourth of their budgets, Insider Intelligence Trends, Forecasts & Statistics/, March 23, 2018.

5 How AI Can Help Drive Biopharma Marketing ROI?, Wall Street Journal, March 23, 2021

6 How AI Can Help Drive Biopharma Marketing ROI?, Wall Street Journal, March 23, 2021

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