One of the most interesting applications of AI-based machine learning has to be influencer marketing.

Companies that use AI-based machine learning have a tool unlike any other to connect with the best possible influencers in the marketplace. And while social media influence has turned into a billion dollar industry in its own right, social intelligence is only the beginning.

More and more industries are applying AI to their marketing strategies to see results, and as adoption continues to increase, the possibilities are endless.

Hyundai and Artificial Intelligence

For a good example of a company creatively using machine learning, consider Hyundai and its recent application of the Influential platform. Aside from the company’s desire to engage with influencers who could spread the word about the brand, the company sought to use the platform’s advanced AI to better define the target demographic for its new SUV product launch. The company credited the advanced machine learning capabilities of the Influential platform in making this possible.

Of course, AI-based machine learning hasn’t yet entered the public mainstream, meaning that the full applications of the tools haven’t yet been explored. But as Hyundai demonstrated, companies can use machine learning in numerous ways to pursue their marketing goals.

Marketing Applications of Machine Learning

Market segmentation and audience analysis is one of the most promising areas for AI-based marketing. Audience segmentation is all about reviewing data sets and identifying patterns in the noise—the perfect application of machine learning.

Of course, machine learning solutions aren’t without their limitations. As of now, its application still requires human supervision and works best with familiar data sets. But as time goes on, machine learning may become the marketing norm across numerous areas:

  • Smart lead acquisition: Building off machine learning’s current role in social intelligence, consider how this system could increase the quality of leads found for each marketing campaign. By assessing hundreds of thousands of user profiles, marketers will be able to laser in on which markets will be receptive to their messaging—a stark contrast from the segmenting options available today.
  • End-to-end campaign relevancy: Applying machine learning to the entirety of a marketing campaign (from lead generation to nurturing to conversion) creates new possibilities for relevancy. Right now, many marketers struggle to address each customer at the appropriate stage of the buyer’s journey with messaging that appears fresh and relevant to their needs. With machine learning, platforms will be able to proactively understand where each customer is in the marketing funnel and automatically send them the messages best suited to their experiences.
  • Content Analysis: Content quality is essential to digital marketing, particularly for inbound strategies. As conversational computing increases in efficiency and machines become better at identifying which metrics contribute most to the performance of marketing copy, it’ll open the doors to an entirely new form of automated content analysis.

The Future of Machine Learning In Marketing

At its core, machine learning is all about problem solving. This makes it the perfect fit for marketing, which, at its core, is merely a series of problems waiting to be solved. And as machine learning increases in accessibility, we expect companies of all sizes to begin exploring the different ways AI-based platforms can improve marketing campaign performance.