August 2, 2017 / By Cynthia Ramsaran
In a prior blog post, we explained how Artificial Intelligence (AI) has become an important tool that offers brand marketers the potential for cost savings, increased efficiency, and business improvements. Now, another way to demonstrate AI’s benefits for marketers is in influencer campaigns. By using AI to identify the most relevant influencers for their brands, marketers can significantly enhance their return on investment.
The traditional approach to influencer marketing is for brands to retain specialty companies and talent agencies that help match influencers with brands. This approach, however, has not been without its flaws. Among the most notable: the lack of control brands have over chosen influencers, selecting influencers without a strong sense of the type of influencer the brand would like to work with, and relying on a talent agency’s pool of influencers, which are not always the most relevant match for a particular brand. Also, as the number of social media influencers continues to multiply, brands are finding it increasingly difficult to find the right influencer(s) for their influencer marketing campaigns.
But AI is creating a paradigm shift in how influencers are matched with brands by uncovering the most efficient and effective pairings between brand and influencer. While it may seem counter-intuitive for machines to excel at identifying influencers, machines are capable of taking in significant amounts of data in a relatively short time period and are much more efficient at identifying patterns or connections than humans.
To determine ideal pairings, a three-pronged approach is utilized that involves a combination of demographics, contextual relevance, and psychographics:
• Demographics can identify factors such as age, gender, geographic location, and race to help identify the ideal influencer for a brand.
• Contextual relevance determines if an influencer speaks about a particular brand or company on their social feed, or if their interests align with the brand’s image and content.
• Psychographics and augmented intelligence are then employed to match brands or companies through personality traits and archetypes.
IBM Watson, for example, uses a Personality Insights API (Application Program Interface) and Natural Language Processing ( computer programming that understands human speech as it is spoken) to help companies make the best brand/influencer matches. It takes the last 22,000 words that any influencer has spoken on Facebook, Instagram or Twitter, and identifies, on a scale of 1 to 100, how those influencers index on the Big 5 Personality Traits. It then further analyzes this data against the social handle of the brand to ensure the influencer is a psychographic match for that particular brand.
While the use of AI to identify and select influencers is relatively new, brands already involved in this process see great potential in producing ideal influencer matches that result in greater engagement, loyalty, and purchase decisions.