The biggest tech companies in the world are also the best at customizing their offerings for customers, and predicting what they want. Amazon, Google, and Netflix have been consistently using AI and predictive marketing analytics to first achieve and then maintain their supremacy. Their internal knowledge, matched with large quantities of structured data and a laser focus on what ‘good’ looks like, have been the drivers of their success.
However, in life-sciences marketing, reality has not caught up to the buzz of self-learning systems (AI) and predictive analytics. However, adoption is increasing (albeit slowly), and more and more leaders are excited by benefits their investments may bring.
Our 2017 Multichannel Maturometer revealed that only around half of major life-sciences companies have an integrated customer database across all channels, and digital teams are only slowly being integrated with their IT partners. And as a further challenge, only 20% are claim to be ‘very comfortable’ with measuring HCP engagement.
For companies to really embrace the future of analytics, it is crucial to move from “predictive guessing” to “predictive knowing”. A well-integrated customer database across all channels, a good understanding of what means success, large-enough datasets, ... are just some of the key components for this transition.
In this webinar, we will talk about:
• How does predictive analytics differ from prescriptive analytics?
• When can predictive analytics become relevant (and when not)?
• What are the different enablers for engaging in predictive analytics?
• A few examples to get inspired