Aritra Das co-authored this blog post with Sonal Singh.
The oncology market has become increasingly crowded and complex incredibly quickly. As an oncology market researcher, you might be feeling a lot of pressure to up the analytical sophistication in your research and capture nuanced decision-making, all while getting insights to your key stakeholders faster. Have you ever wondered how AI could help solve some of the burning challenges that you’re facing, and help you get robust answers to your questions quickly to help you keep up with the rapidly changing market? Here’s how AI can help.
Carolyn Morrow co-wrote this blog post with Aritra Das.
Pharmaceutical companies face numerous obstacles when conducting primary market research in the oncology space. For one, the complex and nuanced clinical data that’s being presented to oncologists can cause decision paralysis, making it difficult for traditional market research to reliably predict future market outcomes. Second, various cognitive biases create a gap between how HCPs respond to a survey and how they actually behave in real life. Third, real-world group decision-making (tumor boards, for example) can’t be adequately mimicked in a one-on-one market research capacity. Lastly, to add to it all, overcrowded markets are creating an overload of research requests directed at the same set of HCPs, which causes survey fatigue and leads to lower-quality responses and lower response rates.