marketers have long leveraged data to understand and improve campaign effectiveness. as data-driven media planning has evolved, marketers now have the capability to leverage a new marketing tool: predictive analytics. predictive analytics is a form of analysis conducted by leveraging ai and machine learning to combine the insights generated through various datasets, algorithms and models to predict future behaviors. there are several ways that marketers can incorporate predictive marketing analytics into campaigns to improve effectiveness and enhance marketing: the insights give marketers an understanding of consumer interests based on past interactions.
predictive analytics also allows marketers to qualify and prioritize leads. with so much data available, marketers require advanced marketing tools and measurement capabilities in order to take advantage of predictive analytics. ai and machine learning are poised to play a large role in marketing optimization and are considered to be essential features as marketers select omnichannel marketing tools. to stay competitive, today’s data-driven marketers are leveraging innovations including predictive analytics through unified marketing measurement, marketing analytics software, ai and machine learning.
so to kick off your education in predictive analytics (and to ultimately show your competitors who’s who in advanced marketing data wizardry), grab a cup of coffee and make yourself comfortable, because you’re about to hit the ground running with predictive marketing analytics. you can use this feature to upload a list of the emails of your best customers, based on which facebook starts targeting your ads to people similar to these customers. now that you hopefully have an idea of what you can achieve with predictive analytics, it’s time to look at what the process of getting that done might look like in practice.
once your hypotheses have been tested and either validated or thrown out the window based on your data, it’s time to create a predictive model. it’s up to you to look at the data and turn it into actionable insights. now that you know what predictive marketing analytics is, what you can do with it, and how the process should work, i hope you’re excited about getting your first few models up and running. if you’ve done something cool with predictive marketing analytics already, i’d love to feature you and your marketing team in a future post.
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