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The 3 P’s of Demystifying AI for Marketers

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It’s math, not magic!

AI can often appear daunting, but it is the key to driving marketing efficiency and effectiveness in today’s digital landscape. As marketers, we’ve got more data than ever available to us; data is retrievable from virtually every source of marketing that we do, from real time clicks to customer experience and interactions on our website. So the question is not how we access the data we need, but rather how do we break it down and use it to drive actions that deliver results?

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So what are the three P’s of AI, actually?

Instead of putting data strategy, AI, and machine learning into the “too-hard” basket, marketers need to understand that it’s math, not magic. In the digital age, there are three P’s that form a vital pot of information to help marketers achieve an essential goal – really understanding their customers and predicting what business’ next best customer looks like.

Step 1 – Patterns:

Pattern recognition provides the groundwork for AI to be used effectively in marketing. By analyzing data around demographics, web browsing behaviors, and past purchases, marketers can detect common attributes and understand segments of consumers. These shared attributes can be amplified by identifying customers that display similar behaviors.

Step 2 – Preferences:

The next step is to connect your marketing to the consumer and individual. Key to this conversation is consent. When asked, most consumers actually prefer more personalized experiences. To do this well, consumers need to be part of the conversation, providing us with consent over their data so we can deliver them more relevant products that align with their preferences.

Step 3 – Predictions:

The third step in using AI effectively for marketing is taking those patterns and preferences and turning them into an actionable predictive engine. By using AI and machine learning to score variables ahead of time, marketers are able to predict a range of actions a user might take next. Central to this in a consent-first world is having authentic, real time first party data, so predictions can update as preferences change.

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While it’s mostly math, there is some magic to it all

AI technology is already embedded into a score of MarTech tools available today, but many marketers are reluctant to use it in more of their strategies. Part of this reluctance stems from not understanding what AI technology actually is, a lack of trust, and confusion on how to bring AI into the marketing mix.

Machine intelligence makes the impossible possible by providing the speed, scale and accuracy needed to build unique predictive models for individual advertisers, and continually optimizing campaign delivery to drive optimal outcomes while adhering to campaign setup parameters.

Marketers often think we know who our consumers are, but AI and machine learning takes the guesswork out of understanding online behaviors.

AI is no longer a newfangled concept; it’s become a must have tool that frees marketers up to focus on the value-adding activities they were meant to do in the first place as humans such as strategy, creativity and ideation.

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