One of the reasons why Bayesian was previously largely overlooked was the sheer complexity in its application in anything but the simplest problem.
Whilst the actual mathematics that goes into a ‘Bayesian’ model is still pretty challenging, technology now helps some of the pain out of the number-crunching. We have conducted significant R&D over the last three years to develop our own proprietary ‘Bayesian’ modelling platform called BayesIQ™ which you can find out more about here.
However, there is more to developing a ‘Bayesian’ model than sophisticated technology and clever mathematics. The model needs to be grounded in the context of the prior knowledge that exists around the problem in question. This is where our team’s experience of working across many industry sectors, as well as significant in-house marketing experience, plays a key role in working with our client teams to uncover and incorporate the existing insight, and real-world limitations that can help develop a more accurate model.
Far from being a ‘black-box’ solution, our analysts then carefully adjust our models to see how much reliance is placed on the data versus the prior knowledge. We then work closely with the client team to review the model’s predictions and translate them into clear and actionable marketing insight.