Our proposed solution
Conduct primary market research to identify potential drivers of vaccination and understand people’s attitude towards the flu, vaccination and health. Develop a (logistic regression) model to predict vaccination rates based on the outcomes.
Together with a research agency and Imperial College London (as part of a PhD dissertation), a research study (by a partner MR agency) was run in the UK, France and the US, addressing 1,000 adults in each country. As the project was part of a PhD programme, the questionnaire was carefully designed in line with existing literature on possible drivers of vaccination. The questionnaire covered an extensive variety of attitudes towards the flu, vaccination, medication and health in general, as well as characteristics of the respondents in terms of age, gender and health conditions.
When developing the (logistic regression) model to predict the vaccination rate, we worked together closely with Imperial College to make sure that the approach was in line with previous academic research. Where necessary, we deviated from or updated previous methodologies to fully utilise the information captured in current data sets. Before progressing to the final predictive model, we ran through several data exploration steps (factor and correlation analysis) to narrow down the potential list of drivers to avoid overfitting the model.
"What are the drivers that influence people’s decision to get vaccinated?"
Results and benefits to our client
One of the main outcomes of this project has been a user-friendly tool in Excel, built by boobook, that allows the pharmaceutical company to predict future vaccination rates if key drivers of vaccination were to change (e.g. a change in attitudes, or more people suffering from a certain condition).
Due to the success of this project and the insights is has delivered, it has been rolled out to several other countries as well.