Proof in Practice

iMR Case Studies

Case 01 / 06

Quantitative Positioning with iPosition™

Introduction

Our 360º view of drivers and barriers to product success precisely measures what drives brand preferences. The inputs for this strategic model are:

  • Patient treatment behavior
  • Perceptions of all competitors
  • Attitudes, emotions, and heuristics
  • Managed care access

In addition to uncovering drivers of prescribing, iPosition™ can explore an optimal marketing strategy by simulating what-if scenarios. Instead of a trial-and-error approach to marketing strategy, iPosition™ offers an easy, inexpensive, and reliable alternative.

Case Study

Our client in the women’s health arena had an HCP-administered product with a unique delivery. The primary objective of the research was to quantify the drivers and barriers to brand success, informing upcoming changes in marketing strategy and tactics. iMR surveyed both physicians and patients. The starting hypothesis was that stocking and reimbursement were the primary barriers to the growth of this buy-and-bill product.

iPosition™ insights and market strategy simulations determined that stocking / reimbursement were not the barriers. Patient satisfaction, timely reminders to renew prescriptions, and HCP comfort with the method of application were the most critical drivers. Furthermore, targeting primary care physicians (PCPs) rather than specialists and refocusing on specific practice settings could yield the most considerable upside.

Introduction

iS™ is a novel approach providing a deeper understanding of the decision-making process, including the inputs required, the interrelated decision-making elements, the steps to be taken, and the resulting decisions.

It mirrors real-life thought processes, such as seeking an optimal solution, evaluating alternatives, and making informed decisions.

iS™ captures how people learn, connect ideas, and absorb information about a given topic.

It does not assume any specific patterns of decision-making. It is agnostic towards a unique approach to decision-making that consumers may have. It is open to any heuristics that respondents may utilize. This contrasts with classical methods, such as conjoint analysis, which assumes that all decisions are made in terms of attribute trade-offs—i.e., giving up one thing (e.g., paying more) to gain another (e.g., getting the color of the car the consumer wanted).

iS™ is a highly versatile tool. iMR uses it to uncover and explore unique existing and emerging heuristics, guide segmentation, understand the value and preferences for messaging, and improve choice modeling insights beyond what conjoint analysis can do, among other applications.

Case Study

iMR was commissioned to carry out a physician messaging and segmentation study to optimize marketing efforts for a chronic CV disease potentially resulting in hospitalization or death.

Our client’s objective was to determine the optimal messages and prioritize physician segments to focus targeting efforts.

Typically, messaging research is conducted after the segmentation so that the targets are known and understood. Here, the process was opposite, the client first asked us to conduct message assessment and bundle optimization. iMR utilized iSearch Message™ to determine the most impactful messages, the optimal message bundle, and the natural story flow.

Following the delivery of the message insights, the client decided to conduct a segmentation project and assess messages by segments.

iMR combined secondary data with primary research to create statistically significant and commercially relevant segments.

When the segments were determined, iMR projected the segment membership to the entire universe of prescribers. With that exercise iMR was able to break the message project sample into segments and reanalyze the messages by segments.

When message preferences were broken by segments, it was clear that both projects are profoundly connected and that both are valid and reliable since the message preferences were fully aligned as would have been expected by the nature of each segment.

Introduction

Measuring implicit cognition is a relatively novel and promising way to better understand how consumers, physicians, and patients make decisions.

Marketers have been intuitively aware of implicit cognition and attitudes for a long time but could not capture them reliably. With advancements in consumer psychology, including methods such as the Implicit Association Test (IAT), we can now measure these underlying influences, enabling us to explain behaviors more effectively and predict them more accurately.

iSight™ is a version of IAT modified specifically for the pharmaceutical industry. It measures:

  • Attitudes and beliefs that people may be unwilling or unable to report
  • Strength of associations between concepts (e.g., Ford vs. Chevy) and evaluations (e.g., good vs. bad) or stereotypes (e.g., athletic vs. clumsy)

Case Study

In this example, our client in the oncology space had a product where the uptake had leveled off and usage was primarily concentrated in later lines.

Prior research – both qualitative and quantitative – did not find key differentiations across physicians or provide guidelines on how to market the product.

The brand team was seeking a new approach to restart growth by developing a new segmentation and identify hidden barriers. iSight™, a proprietary version of the Implicit Association Test (IAT), was a core component within an integrated segmentation framework that was leveraged to identify physicians who do not use or dislike the product and to determine what could be done to improve market share in the future.

iMR was able to differentiate HCPs by their implicit attitudes and confirmed that these implicit attitudes are predictive of prescribing preference. This enabled us to define actionable segments and develop a tailored approach for each segment.

Introduction

iMR hybrid segmentation approach integrates various data sources:

  • Implicit attitudes and decision heuristics: Underlying preference for treatments that HCPs may not necessarily be aware that they hold
  • Treatment behavior: Patterns of treatment across a spectrum of targeted patient types
  • Practographics: Physician specialty, supporting staff, years of experience, type of organization, etc.
  • Explicit attitudes: Self-stated and in-depth exploration of product beliefs and treatment philosophy

Case Study

In this vaccine case study, our client’s product was closely competing with a similar product. Traditional approaches (both primary and secondary research) have been unable to differentiate healthcare professionals (HCPs) who could be prioritized and targeted.

The main objective was to uncover segments of HCPs who could be targeted to boost product utilization by discerning physicians’ true preferences. Furthermore, we needed to identify the physicians who do not vaccinate or who are hesitant about our client’s vaccine and what makes them unique.

A primary obstacle to secondary data analysis in categories such as oncology or vaccines is the lack of physician-level data on prescribing. Sales are tracked per account, but there is no straightforward way to distribute products to the physician level. To resolve this issue, iMR used a proxy analysis approach. Later, when conducting primary research, we found that our approximation of individual-level vaccine prescribing aligns with physician self-reported prescribing.

iMR leveraged iSegment™ integrated segmentation approach, combining account-level sales data and behavioral economics-based survey exercises.

iMR confirmed that traditional approaches to understanding HCP vaccine preferences/attitudes were not differentiating. However, leveraging behavioral economics exercises using iSearch™ and iSight™ enabled the measurement of HCP implicit attitudes about vaccination and preferences between the two competing products. This integrated approach identified distinctive segments with apparent differences in how they can be motivated to prescribe more.

Case 05 / 06

A New Approach to Brand Tracking: ATU 360™

Introduction

iMR brand tracking program is focused on what matters to the brand, with a reimagined, laser-focused approach to tracking that features added agility to monitor emerging issues as they arise.

ATU is probably the most often-used quantitative market research.

Unfortunately, it is often misdirected by tracking less relevant issues, inundated with numerous questions that are difficult to respond to, overly focused on attitudes and perceptions, and utilizes simplistic analyses.

Case Study

For this project, the client was preparing to launch a new virology brand. The client team approached iMR seeking new ideas for conducting ATU research to improve the quality of insights delivered to key stakeholders.

We applied behavioral economics principles and best practices developed via the “Research on Research” initiative conducted a few years ago. The resulting tracking program was focused on capturing respondents’ product preferences, key market metrics, implicit thinking, and actual market behavior by collecting patient cases.

iMR’s ATU 360™ addressed all key metrics needed by the client team for launch tracking. Additionally, an empirical approach to prioritizing items for tracking helped maximize the utility of the ATU Pulse surveys.

Through this unique process, iMR grew a database of patient charts that provided a means to answer emergent business questions without fielding additional surveys.

Introduction

Precise and insightful forecasting is one of the most challenging project types in the pharmaceutical industry. It is a combination of forecasting science (i.e., proper method for the purpose) and art (i.e., understanding competitive context and intricacies of that therapeutic category).

iMR developed a comprehensive toolbox, ranging from analog models using the Bass diffusion marketing model to advanced patient case-based econometric choice models.

Methods rooted in behavioral economics form the basis of predicting consumer, HCP, and patient preference for new product(s) and adjusting for their potential overstatement of product use.

The most often used forecasting approach is iF Patient Case Forecasting™. It is designed to:

  • Mirror actual behavior by engaging physicians in treating realistic patient cases
  • Provide a 360-degree view of new product drivers/barriers by integrating actual market behavior with brand beliefs and treatment heuristics
  • Withstand the test of time by being analytically flexible and continuing to provide value over time
  • Adjust for overprediction using behavioral economics
  • Support and defend the forecast with in-depth insights and analyses focused on patient types, product quality, and physician types
  • Utilize an extensive benchmarking database across hundreds of products and different therapeutic categories

Case Study

In a rare disease category with a highly engaged patient population, our client had an existing product approaching the end of its lifecycle and was preparing to strengthen the portfolio by launching an innovative new product.

The research was conducted with both physicians and patients.

iMR was asked to provide a revenue forecast for both the in-line and new product and to develop insights to inform portfolio strategy (conversion or co-positioning). The iForecast patient case exercise was conducted among healthcare professionals (HCPs) and patients in the US and key global markets to test the hypothesis that the new product would be significantly preferred over the in-line product, warranting a conversion strategy rather than a co-positioning strategy.

Using our proprietary iF™ method, we were able to conclude that a co-positioning strategy would be optimal given the unique patient types of the In-line vs. New Product. Positioning the New Product to compete with Competitor A would maximize the total opportunity for this asset.

Additionally, leveraging the richness of the available survey data, iMR conducted two segmentation analyses, identifying two distinct segments: complacent patients and HCP loyalists to Competitor A, who will require targeted education and messaging before strongly adopting the New Product.

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