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What Are the Problems With Influencer Marketing, and How can AI solve them?

by Sarah O'Neill, on 28 April, 2021

Anyone can be an influencer. Everyone and their mum has an Instagram page selling weight loss teas. Sharon down the road has given up her job as a solicitor to pop balloons on TikTok. I'm buying protein bars on the recommendations of a person I've never met. So, what's going on?

 

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“From a PR perspective, Influencer Marketing is the shift in recognising there are new ways to reach your audience or publics.

 

"Traditionally, that used to be high net worth individuals or journalists. Now it can be anyone with their own network or media” says author Stephen Waddington, of Wadds Inc.

 

A report from Mediakix suggested that the influencer marketing industry global ad spend was projected to reach $5-$10 billion market in 2020. And, as influencers become more readily available, and profitable, brand dollars have flooded the space. Brands are now set to spend up to $15 billion on influencer marketing by 2022. 

 

Alongside this change, marketing has become more and more based in algorithms, data, analytics and specificity. So, the 'spray-and-pray' approach is never going to be the most effective with Influencer Marketing. Instead, brands have to figure out how to target the right audience, with the right individuals.

 

This is where AI and Machine Learning tools come in. So, what we'll do is go through, step by step, what problems can arise with influencer marketing, and how our robot friends can help. Sound cool? That alright with you? Yeah, all good with me. You sure that's okay? Alright. Let's get started. 

 

 

Wanted: Influencers of Quality and Quantity.

As said before, influencers are everywhere. They're on Instagram, TikTok, Yahoo Answers. There may even be an influencer standing behind you. Right now. 😱

It's understandable, then, that this ready availability of influencers can often lead to a lot of dead ends - from fake engagement or tracking actual engagement rates, to irrelevant or unreliable content. 

These are things AI and machine learning tools can solve. Let's start with engagement. An algorithm can take engagement activity from an influencer's previous posts and determine their engagement score. This can then show the likelihood that an influencer will be useful to a brand. However, it doesn't just scan the influencer's previous actions - ML can be turned inward too. Searching through a brand's previous campaigns, previous influencer marketing, and goals, ML tools can point marketers towards the creators that could be most useful to them. This saves a bunch of time on scouting.

A few platforms even let you sort influencers into groups, using not only by type of influence, but by physical features. Though this might sound a bit creepy, if you're a hair care brand that specialises in curly hair, you're going to want an influencer with that hair type. 

AI tools can also help identify relevant social media influencers, and develop an understanding of both an influencer and their audience. If an influencer posts an image of a specific brand, and this is embraced by their community who share and like to their hearts content, then these posts can be tracked by the brand itself. This can also help the influencer themselves better understand their audience, and in turn, allow for more solid and consistent influencers that brands can hire and utilise. 

ML and AI-powered platforms can even help identify fake followers and inauthentic engagement. Often, an influencer's price is based on their engagement metrics, so bots can throw a spanner in the works. According to recent research, popular brands are being exposed to a high proportion of fake followers because of these false numbers. 

But most of all, AI tools can be used to streamline the job of marketers, so they can get back to the quality of content, and the human element of influencer marketing. 

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Identifying an Influencer's niche

Looking for a fishing influencer with a side interest in coffee shop art, interacting mainly with a female audience aged 34-46? Then you need AI tools.

Brands can use ML tools to identify an influencer's niche and expertise. It is vital for a brand to find an influencer with a persona that matches their tone and values. Plus, it is necessary that the influencer's audience matches the brands target customer, in order to ensure the marketing campaigns are reaching the right people. ML and AI can aid in ensuring brands only connect with influencers who are impacting the people they want to impact. By measuring influencer metrics, such as gender, age, interests, locations etc. etc., the brand can track down the right person for the job. 

Then, a brand can use further metrics such as engagement, traffic and activity, to make sure the ad is reaching as many of the right people as possible. ML tools can even look through the comments, and the commenter's own posts, to figure out details on the audience. This can be useful in determining whether this is the right demographic, or even just to learn more about the interests of this targeted group.

An influencer can often influence a 'sub-segment' on top of their niche area. So, they might be an expert in fashion, but specifically people gravitate to them for advice on socks. ML tools can step in and extract these deep insights from their posts, and direct the brand to the influencer with the most relevant experience. 

The Problems with Photos: Is that Latte Authentic?

Many social media platforms rely on image, and video, based posts. But most published images lack identification, be it in hashtags or text, so it can be difficult to track their authenticity or footprint. So brands have to learn how to analyse the image content. ML powered systems and tools can be utilised to do so, through sorting and identifying valuable and valid content. 

AI can save marketers a good deal of time through its ability to process huge numbers of images, and identify discrepancies quickly and effectively. Image recognition can be used in a number of different ways, including identifying relevant social influencers and understanding audience interactions. ML tools can even trawl through thousands of images searching for mentions of your brand or product, saving the effort of having to slog through every post ever to tag yourself. 

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Timeliness is Next to Godliness

Timeliness and quality of content is always a point of anxiety when working with influencers.

Introducing an algorithm into your influencer marketing means you can analyse an influencer's previous content production. The algorithm uses image recognition strategies and processes to analyse the creators frequency of posts, and the timeliness of their content. Brands can then identify consistent creators that could maintain quality content over an entire campaign. 

Choosing Channels

If you're an influencer, the likelihood is that you're on EVERY social media channel. Content creators are encouraged not to rely on one specific form of revenue, due to the transitory nature of the industry. BUT this does not mean that an influencer successful on Instagram will be successful on TikTok. Look at all the Vine 'stars' that migrated to Youtube. Eep. 

So, brands have to discover not only who the influencers are that are best for their ads, but where they are. ML algorithms can enable brands to calculate influencer engagement on each channel, and can allow them to make an informed decision on who they use, or which platform they use. 

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Influencer marketing and AI tools are a match made in heaven. Users who trust influencers, might not trust brand generated content. But on the other hand, due to the human aspect of Influencer marketing, it can be time consuming, and even inaccurate. But by introducing a little bit of robot magic, with a human touch, marketers can approach the space with detail, speed and efficiency. 

Topics:MarTechMust seeinfluencer marketingAI

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