The expanding use of AI in our lives has, without a doubt, split people’s opinions, and the same is true for the world of marketing. With privacy issues coming to the fore, many are wary about the potentially intrusive nature of AI. And the prevalence of AI in social media applications especially highlighted such problems.
AI thrives on aggregated user data—the bread and butter of emerging technologies, including social media. AI in social media, for instance, helps marketers identify the peak times to post ads for certain demographics and locations. The technology automates market research for digital professionals, which, unfortunately, borders on knowing a little bit too much on customers. Machine learning (ML) algorithms, for example, can profile users based on the posts of friends they interacted with from within their social networks.
Of course, AI can’t be all that bad. AI and social media marketing, for sure, can mix without infringing on a person’s privacy. We’ll explore that later in this post, but first, let’s take a look at the best use cases for AI in social media.
AI in Social Media: Innovative Applications
ML enables marketers to zoom in on details that they can’t achieve organically through social media sites’ built-in analytics platforms. The examples below illustrate this elevated functionality better.
One-to-One A/B Testing
Marketers can derive more accurate A/B testing results from hyper-personalized campaigns with AI software. An example of this is Persado One, which enables marketers to automatically generate ad copy and images based on a user’s past emotional engagement. The system uses ML to look into how users reacted to former campaigns. This software doesn’t rely on online proxies, such as purchase patterns and demographics, to create an emotional profile of a customer.
AI-powered applications allow marketers to identify influencers that can provide them with the greatest bang for their buck. Ad fraud is a real problem for brands, and many bogus influencers have fooled a lot of big-name brands in the past. By using AI-driven applications, brands can determine influencers that speak their language through natural language processing (NLP). They can also weed out influencers with fake followers and engagement using AI software.
AI allows marketers to know the exact part of an image asset that customers gaze at so they can craft better visuals. Eye trackers are used to record this information, and neural networks use the resultant data for training. The neural networks, in turn, predict which points in an image draw viewers more.
How Marketing Professionals Can Avoid Trouble
The use of AI in social media, indeed, demonstrates several benefits for marketers. To remain compliant with data privacy regulations and such, one important thing that they can do is remain transparent about how they handle customer data. In short, marketers should practice good “AI hygiene.” They should secure their users’ sensitive information, and audit the content the AI has access to. That can help prevent algorithmic bias, and potential data loss, among other things.
Marketing thought leader and bestselling author Erik Qualman once said, “We don’t have a choice on whether we do social media, the question is how well we do it.” While the lines between user data aggregation and invasion of privacy are still a bit blurry, marketers can do their part by being sensitive to red flags. Marketers should act as gatekeepers, even if they have the choice not to.