How Artificial Intelligence Can Transform Influencer Marketing

Influencer Marketing is the newest breakthrough to have shaken up the Digital Marketing landscape. Once an experimental channel, it has grown exponentially over the past few years – up to $6.5 billion this year and projected to rise to up to $10 billion by 2020. Now a mainstay of Marketing organizations, the key success factor is figuring out how to get the most from it.

Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) are revolutionizing the way brands conduct Influencer Marketing. AI-powered Influencer Marketing tech is helping brands in three key areas: identifying the right creators, suggesting impactful workflow actions, and creating more relevant content. With the digital universe continuing to expand, the true advantage of Influencer Marketing enhanced by Data Science lies in its ability to consider an inordinate amount of data in each recommendation.

Identifying the most suitable influencers is one of the biggest obstacles for marketers. In a world where customers are flooded with ads, presented to them wherever they go, brands need to redefine content to beat the masses. Over the years, it has been reported that the average person is exposed to thousands of brand messages every day. With the explosion in digital content across multiple devices, brand exposure is at an all-time high today. Brands need to deliver the content that resonates with their audience and cuts through the noise of the digital space. AI/ML can do this in three ways:

NLP AI analyses the content of a creator’s posts and generates things like interests, industries, demographics, and brand affinities from them. Influencer platforms use these classifications in ever-evolving discovery search engines. Visual search AI analyses the visual content of the creator’s posts to do much the same thing.

Similar to how AI processes and draws insights from the content of posts, it can also assess the content and gauge the sentiment of comments (and the posts of the commenters) to draw conclusions about the creator’s audiences. Similarly, sentiment analysis AIs can understand the reaction to a piece of content based on comments and engagements.

3. Magical “Relevant” Creator Suggestions Based on an Inhuman Volume of Inputs

Based on a brand’s goals, past Influencer Marketing efforts, and provided inputs, Influencer Marketing platforms can suggest creators that would be most successful for campaigns. This saves dramatically on one of the most time-consuming portions of the Influencer Marketing workflow: initial discovery before qualitative vetting.