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.