This Is How Artificial Intelligence Is Revolutionizing Influencer Marketing
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Artificial Intelligence (AI) has the potential to change the business world significantly. The International Data Corporation (IDC) notes that industries are expected to shell out as much as $110 billion by 2024 on AI. Monetary investment in AI already hits close to the $50 billion dollar mark. But what do businesses get out of this investment? Is there any positive change in how those companies interact with their consumers as a result? One of the newest ways to use AI is to help companies identify viable influencer-marketing channels. Before we see how AI changed the influencer-marketing game, we must first examine how widespread influencer marketing is today.
A brief summary of influencer marketing
Sprout Social defines influencer marketing as a social-media channel that leverages a popular personality's audience on a particular platform. In the early days of the influencer-marketing craze, businesses had very little to go on. They'd look at which users had the most followers and pitch them to promote products. As social media grew, businesses became wiser about who they partnered with. The choice of an influencer could reflect poorly on the company if the influencer found himself or herself involved in a scandal.
The catch to finding an influencer
Businesses have now realized how powerful influencer marketing can be. With the entire world having to deal with social distancing in 2020 and part of 2021 so far, influencers are some of the most consistent marketing tools brands can utilize. Unfortunately, it's more complex than just finding a user with the most followers anymore. Influencers primarily operate within the niches of beauty, fashion and food. Lifestyle marketing is how those influencers make an impact on their audience. They sell people the idea of a great life. Unfortunately, finding the right influencer for a brand means delving into that influencer's posts and his or her followers' engagement. For a human, that could take hours on any social-media platform.
The role of artificial intelligence
Marketers have gotten used to rolling dice. Much of the early days of marketing were random. However, as technology advanced, we saw more targeted marketing to remove the random element. The same thought process is behind the use of AI to pinpoint marketers that fit particular brands. Artificial intelligence is an iterative technology. At the start, it will take a while to figure out what works and what doesn't. However, with each new project it takes on, it learns from its mistakes. Like a professional in a field that can cut down his or her working time to a fraction of that of a newcomer, AI can do the same when compared to the average human being. What's more, the AI engine can cross-reference several dozen metrics across the follower count effortlessly. Data that would fill multiple spreadsheets can be crunched down and simplified to a recommendation or a suggestion to move on.
The question of follower count is contentious. While some marketers look at it as a guide, others realize how prevalent the sale of follower accounts is. Follower numbers may be inflated, but engagement still can't be faked to any significant degree. What's more, studies on social-media engagement and brand impact note that smaller follower counts might be positive for marketing. Smaller follower numbers mean that the influencer has more of an effect on each individual follower. From a brand's perspective, this could easily translate into turning a small influencer's fan base into brand evangelists. AI can help find these micro-influencers and see if their follower counts fall within the company's core demographic for their target audience. While this is a simplified methodology, the basic premise remains unchanged.
Using AI is more complicated than it looks
Many businesses make the mistake of thinking AI is a cure-all for their problems. AI is more than just a plug-in that just works. You can't just give it a social-media platform and the criteria you want to conform to and let it loose. AI is a learning system. It needs to be guided to find the correct hits. The engine can quickly pick up on a channel's YouTube views, then drill down on the subscriber data in a matter of seconds. However, once it locates a candidate, it can consistently do that faster with each iteration. The catch to this approach is that the business must already be aware of the things it needs in an influencer. What makes an influencer applicable to the company? What core traits does the audience of said influencer need to display? Finding the first influencer success sets the stage for all the others. It allows the AI engine to learn what the business is looking for.
Marketers get excited about the potential that AI has to find the right influencers. Unfortunately, they misplace their trust in the engine's infallibility. AI is a black box. A marketer can't command it to find the perfect influencer for a brand within the criteria. Instead, they can take inputs and check the results. Then, on the second pass, the marketer can refine the instructions and rerun the algorithm. With each pass, the results get better. However, like all programs, it's only as good as the instructions the marketer gives it.
AI does have the potential to save a company's influencer marketing as well. Sometimes, with the amount of social-media posting that happens from a single account, influencers may misplace tags and links. AI can scan the posts and correct those mishaps with brand names and logos automatically. Posts can be redirected to the company's social-media page for better consumer engagement. In some cases, AI bots can even field the basic interactions with consumers, passing them to customer-care agents if the requests become too complex.
A happy balance between humans and AI
Before a brand starts throwing all its weight behind AI influencer location, it's important to note the technology's shortcomings. An AI still needs a human to guide it. Letting an AI do its thing on its own will give you largely unspecialized results. Without the correct guidance, those results will continue to be useless. Humans need to vet the products and give positive feedback to the AI so it can improve. AI can do a lot of things, but only if it has a human to help it. Striking that balance between human handlers and an AI-suggestion engine is crucial to success.