Have you adapted your insights strategy to today’s disrupted market?

Consider the rise of digital healthcare, value-based healthcare, the growth in payer and patient influence, or the pressure to innovate faster. This shifting environment requires a more holistic approach to decision making across all life cycle stages.

More accurate predictions are needed in order to adapt your sales, marketing and innovation strategies to today’s competitive landscape.

Drive better decision making across all product life cycle stages

Pharmaceutical, biotech, and medical device companies rely on SKIM insights from the earliest stages of product development, through the launch, growth and maturity phases.

SKIM’s healthcare solutions blend traditional methods (e.g. conjoint analysis), digital techniques (e.g. mobile implicit swiping) and data fusion  approaches (i.e. integrating hybrid data and information sets). By combining proprietary advanced analytics research techniques, with behavioral research approaches and specific industry context, SKIM is able to delivers more accurate and actionable insights.

SKIM healthcare market research services

The SKIM healthcare teams includes analytics, behavioral science and indication area experts. Every day we team up with leading companies, such as Bayer HealthCare, Eli Lilly, Pfizer, Sanofi-Aventis, and Philips to tackle questions like:

How great is the market potential of your product? How should we position our new device to physicians, patients or caregivers? Which product features should we leverage in HCP communications? What will persuade formulary committee members to recommend our product?

Early-stage research insights

  • Comprehensive market understanding to drive New Product Development strategy
  • Gain a deeper understanding of market sizing, segments and dynamics for innovation decisions
  • Evaluate and prioritize new concepts and product features to gain a competitive edge
  • Determine the market, pricing potential and perceived value of new products to maximize profits
  • Accurately predict the uptake of products considering the influence of HCPs, regulators, payers and patient groups via advanced analytics techniques
Johnson Johnson Product innovation research AI

Launch research insights

  • Robust forecasting, communications and digital solutions to achieve rapid uptake and set a high-growth trajectory
  • Develop product messaging and understand HCP/patient drivers to improve brand performance
  • Discover the influence HCPs, payers and patients have in prescribing decisions utilizing digital techniques (e.g AI, chatbots, voice technology, and in-the-moment mobile research)
  • Uncover which traditional and digital channels HCPs/patients use to optimize marketing strategies
  • Better leverage connected and educated patients via online patient communities

Post-launch research insights

  • Sophisticated pricing, brand communications and digital solutions to maintain market share and slow down declines
  • Better predict the impact of competitor introductions
  • Monitor brand performance in a more dynamic way to better prioritize marketing strategies and determine salesforce effectiveness
  • Optimize product messaging and understand HCP/patient drivers to ensure long-term growth
  • Identify and untangle today’s physician and patient healthcare journeys to better align marketing investments

Latest healthcare research from SKIM:
Impact of digital healthcare on the patient experience

COVID-19 triggered a massive change in behavior across the entire healthcare spectrum – putting the digitization of pharma in a pressure cooker. Telehealth, during the first lockdown in particular, served as an accelerator to rethink and prioritize digital strategies without delay. The SKIM Healthcare team explored patients’ attitudes about the shift to telehealth during COVID-19 in Europe and the U.S.. Download the report to learn more about the effects of telehealth on patient care and implications for future pharma digital strategies

Pharma and consumer health product forecast with decision influence modeling