Influencer marketing has permanently changed the perception of marketing. Previously it was viewed as an experimental idea that would be nice if it garnered positive results, however now it is a core element of wider marketing strategies, something that has only become more prominent in the wake of the pandemic. Brands would cautiously try to incorporate parts of influencer marketing into their strategy whereas now most rely on working with an established influencer with an already engaged audience. There are now entire business models and companies set up to provide influencer marketing and handle the number of influencers to use, what sort of influencer is best to partner with, a micro-influencer or one with mass appeal, when should campaigns run, and what they should look like? All in the name of encouraging increased conversions.

Influencer marketing is a significant, fast-growing section of the digital marketing industry. Major agencies like WPP and Omnicom now have departments dedicated to it with many companies now focusing specifically on influencer marketing and nothing else. The industry is currently valued at $8bn, and before COVID-19 came along, was forecast to double in the next two years. No matter what happens to the world moving forward, retail marketing automation is here to stay.

However, for some brands, working with an influencer can be a daunting, even confusing task. New influencers are constantly appearing, some even contacting companies directly about forming a partnership, and it can be hard to separate one from the other. Why is this one influencer different from that one? Will working with them enhance or hinder our brand identity are common questions that companies ask themselves before making a decision.

Fortunately, AI influence marketing helps cut through all these issues and break the situation down to a much easier decision making process. So exactly what is the role of AI in influencer marketing and how is AI transforming influencer marketing for the better?

 influencers marketing

How AI is Transforming Influencer Marketing

AI is a game changer for many industries and digital marketing is no different, especially as it relates to influencer marketing. It helps remove the random element from the venture, providing tangible data that can be used to make informed decisions. Brands are now able to pinpoint their target demographic directly, and speak to them from a figure they implicitly trust.

AI has the capability to analyse millions of pieces of content, identify patterns and then match for specific criteria based on a brand’s needs in a matter of minutes, something that would otherwise take hundreds of working hours for a human to do. Not only is this process more streamlined and efficient, but due to the nature of AI itself, the more familiar it becomes with a task, it gets progressively smarter and faster at completing it. This means you can find an appropriate influence instantly, rather than having to wade through huge swathes of potential candidates, most of which are not appropriate for your brand to begin with.

Anything from key interests, language, audience demographic, engagement rate, reach, brand mentions, and posting frequency are just some of the parameters that can help decide if a specific creator’s content will connect with your target audience. An AI powered platform can collect all this necessary data, identify markers and then accurately shortlist creators that would suit the campaign.

However, for all of the inherent and obvious benefits AI offers the influencer marketing industry, there are still risks associated with it. Knowing how AI resolves influencer marketing mistakes is key to ensuring that your campaigns and partnerships are successful. It isn’t just as simple as getting an AI tool or piece of software and using it to give you a name. It is there to inform the process, not become it entirely.


How AI is Eliminating The Problems Faced By Influencer Marketing

In its early days, when Instagram was new, influencer marketing was ruled by gut instinct and simply who had the most followers at any given time. Rightly, it was viewed as the least data-driven part of the digital marketing industry. Many clients and brands were simply happy to benefit from the immediacy of response that influencers were able to create in their dedicated audiences, however, measuring the true impact these campaigns had and the overall return on investment they were getting was next to impossible. In fact, it was not uncommon for many influencers to buy fake followers by the thousand that greatly distorted any potential feedback a brand could get.

Analytics will catch up to everything eventually though. Businesses want to know precisely what they are getting for their money, and, more importantly for the audience, customers want to know when they are receiving sponsored messages and ads. Therefore analytics are critical to understanding the level of engagement between influencers and their followers, as well as the likely impact a campaign with them will have.

Influencer marketing is still mainly a B2C activity, the three main categories focusing on beauty, food, and fashion brands with a wide variety of influencers to choose from. AI helps to determine which of these is likely to lead to the greatest impact at the most cost-effective price. It helps separate one fashion influencer from another for example through metrics like engagement, click through rate and, ultimately, purchases and conversions. However, B2B usage is taking off too, with influencers becoming important in financial services, pharmaceuticals, and technology. Micro-influencers, those with smaller followings, can be an effective partner if their audience is more likely to engage with a campaign or product. The initial thought is to always partner with the influencer with the greatest number of followers, however, a smaller, more engaged audience is likely to yield more conversions at a better ROI.

Another mistake that AI can help prevent relates to the posts themselves. Wrong or missing tags and hashtags can significantly affect the impact of a particular post. AI can help fix these issues by automatically detecting brand names and logos in an image or even video streams. effectively enabling a brand to gather a more comprehensive data set on a campaign, properly measure its final impact. This helps inform future campaigns and strategies through the constantly optimising nature of AI through learning over time.

Final Thoughts

While humans may not be capable of vetting every potential influencer, letting AI do everything is still not the answer. Instead, it’s about using supervised AI to inform the initial vetting process and ensure brands are only considering appropriate, suitable partners before humans make an educated, data-led decision.

Place too much reliance on AI-based technology is missing the key point to influencer marketing. AI may tell you which influencers could perform the best, but it takes experienced marketers to then negotiate a good deal, execute on the objectives, ensure the content meets brand and regulatory guidelines, and keep everything on time and to budget. Technology like AI helps get the most out of influencer marketing by working in collaboration with people, rather than instead of them. It is not a panacea for a marketing campaign but when utilised effectively, understanding how AI is transforming influencer marketing is pivotal to generating success, especially during a time when more people are now online than ever before.