By: Maria Williams

Today’s audiences are tired of ads — in fact, SurveyMonkey reports that 74% of consumers say they see too many ads, with 44% of those ads being irrelevant to them.

Combine these negative sentiments with ad blockers, ad-free video streaming and competition for time from video games and other media, and it’s clear that reaching audiences isn’t easy.

However, this doesn’t mean it’s impossible to reach audiences in natural, authentic ways. In fact, as Ricky Ray Butler, CEO of audience and content intelligence tech company BENlabs explains, AI technology can prove key to reaching (and appealing to) ad-wary audiences. The following are just a few of the ways AI can help advertising become more natural, authentic, and appealing.

Improved Customer Segmentation

“Today’s audiences are more fragmented than ever before,” Butler explains.

“Back in the day, you could reach pretty much everyone with just a few TV channels. Now, we have a thousand Hollywoods – hundreds of TV channels, dozens of streaming platforms and social media options, and 300 million global creators and influencers — quite often, it’s hard to find your audience in the first place. AI relieves this burden by analyzing an incredibly large swath of data, both structured and unstructured data, which are the images, videos, audio, and large groups of text that don’t fit inside a spreadsheet, to segment your audience based on relevant interests, prior engagement with your brand and other factors. It helps you both find and speak to your target audience.”

With a deeper level of segmentation, marketers are better positioned to develop more individualized campaigns that appeal to each group’s interests, wants and needs, greatly increasing their likelihood of conversions. AI helps identify different audience segments and where and how to reach them.

A/B Testing of Advertising Messages

Along with segmentation, AI can streamline the process of A/B testing advertising messages to find the ads that will have the greatest impact on audiences. Machine learning can leverage the standard principles of A/B testing but at a much larger scale than would be possible with human-led data collection.

Even more valuable, AI can quickly implement and draw conclusions from multivariate testing to quickly fine-tune campaigns and run through several options to find what would work best. This makes it easier for marketers to make their messaging feel more natural and compelling to each audience segment. AI can even help A/B test which platforms will be most effective for reaching these audiences in a natural and unobtrusive manner.

Superior Social Listening

“One of the biggest advantages of AI is that it helps us gather insights from qualitative data that would otherwise be hard to quantify,” Butler explains. “Social listening is a great way to gain insights into your audience, but when there are so many people all saying different things, it can be hard to turn that into meaningful data. AI helps us spot the patterns, trends and correlations by using machine learning to truly understand audience perspectives.”

As AI draws from social media, forums, blogs and more, businesses can gain a greater understanding of customer sentiment, even in conversations that don’t directly tag the brand. Analyzing data can provide insights into how audiences view a brand and its competitors, what actions they want to see from the brand and more.

Driving Campaigns With Predictive Analytics

“AI’s predictive capabilities are one of its most important assets in redefining advertising,” Butler says. “By leveraging both the structured and unstructured data, AI can forecast trends and predict how audiences will respond to different campaigns. Essentially, it can tell us if the target audience will like what they see and how they will respond to that message. By understanding what’s going to happen before it happens, we can make data-backed decisions that influence everything from the messaging to the type of placement.”

According to VentureBeat, 95% of companies currently use predictive analytics in marketing — but 90% say they struggle to make data-driven decisions on a daily basis. Issues such as incorrect, incomplete or outdated data and models that aren’t tailored to marketing goals can greatly limit the power of predictive analytics. Because of this, a good toolset catered to your audiences and marketing goals is essential.

Delivering Greater Personalization

Personalization is key to reaching ad-wary audiences — in fact, 81% of Gen Z say they like receiving personalized ads. Despite this, research from Gartner indicates that 63% of businesses struggle to provide personalized experiences. As Butler explains, this is yet another area where AI can become a real game changer.

“AI can draw on social listening, predictive analytics, A/B testing and segmentation to deliver messages and placements that are going to be relevant and appealing to each individual,” he says.

“Contextual AI-powered targeting makes it easier to reach the right audience at the right place and time, while other AI solutions can automatically adjust ad content and language to better reflect the interests and desires of individual audience members. It goes much deeper than just plugging a customer’s name into a script, and when done right, it creates a lasting favorable impression for the brand.”

AI Is Key to Advertising’s Future

While AI will undoubtedly be used in the creation of some marketing content in the years to come, this isn’t where it is necessarily going to have the greatest impact on audiences.

As Butler’s insights reveal, using AI data and analytics to drive human-led creative actions can make advertising far more effective and appealing to all audiences.