As marketers attempt to harness a myriad of easily accessible customer information, the influx of data has made their jobs more complex. For those creating video content to reach consumers, artificial intelligence tools hold promise as a way of analyzing the wave of data to quickly make content decisions as well as save time and money, experts say.
Many marketers have AI-based hyper-personalization on their minds, but only 9% of marketers have used these tools, according to Ascends2’s Hyper-Personalization Strategies Survey Summary Report. Video is already essential to marketers, because the medium delivers high conversion rates and builds strong connections with consumers. The question marketers have to answer going forward is how to get the most insights out of the data they obtain. Most businesses aren’t doing well on this front so far, according to interviews with several experts, and may welcome the help of AI, although it comes with its own set of challenges.
"A lot of the hype is, 'buy the AI and forget about your problems.' And I've read a number of vendors' statements that this makes it easy, and that simply isn't the case," Mitch Ratcliffe, partner at Metaforce, told Marketing Dive.
Disappearing barriers
For marketers and advertisers, a big attraction for using artificial intelligence tools to create video content is the potential to save time and money, according to Tim Parkin, president of Parkin Consulting. The real-time feedback offered by AI tools allows marketers to shave off the time it previously took to find out which ads or branded content work in which market, he noted.
Gavin Twigger, chief creative officer of Ansira, noted that AI video software also saves time by automating content creation processes such as color correcting across different frames, audio level monitoring and frame selection.
"It's almost come full circle for me where some of the things I wanted to do years and years ago, 12, 13, 14 years ago when we were working in the direct to consumer space, we were limited by the speed at which we could get the information back," Twigger told Marketing Dive. "Those barriers are gone now."
By taking your assets and starting to recombine them, you extend the investment you made in content production, because you're reusing it in so many different ways.
Mitch Ratcliffe
partner at Metaforce
Advertisers can also tap AI tools to make different versions of videos with varying special effects and transitions. Marketers want to be able to compare which clips perform well at the beginning or the end of Facebook video ads as well as which transition effects perform better on the platform across different market segments, Parkin reported. Using AI tools, advertisers can conduct these experiments at scale without asking their video team to spend hours testing out different videos.
"[The payoff comes] once the AI gets to a point where it can help you discover what’s working and can get that feedback loop closed in terms of, 'Okay, I produced a video. Tell me which ones were good and which parts of it were watched,'" Parkin explained.
Extending investments
For companies with a library of content, AI tools can also provide a competitive advantage, because they can create new video content quickly for various platforms without having to send out the same videos too frequently — something that can be a turn-off for consumers — Parkin continued.
AI enables advertisers to pinpoint where customers stop watching videos and what information was discussed before they stopped viewing the video enabling them to recut ads almost in real time based on how viewers interacted with it, Metaforce’s Ratcliffe told Marketing Dive.
"By taking your assets and starting to recombine them, you extend the investment you made in content production, because you're reusing it in so many different ways," Ratcliffe said.
Taking the brand message and flavoring it for a local audience using all of those inputs — you can't do that on a piece of paper.
Gavin Twigger
chief creative officer at Ansira
In a follow-up email, Ratcliffe pointed to a network marketing company he co-founded that used AI to equip newly hired sales representatives with custom content to share with prospects. As the sales representatives sent content to potential customers, the client used AI to see when changes in wording in the audio and video increased customer response rates.
"Within a month of launch, the client’s sales success rate within the first two weeks of a rep's career with the company had increased 60% over pre-launch," Ratcliffe wrote. "That is, 60% more of its salespeople closed a first sale within two weeks of joining the company."
Still just a tool
Although AI tools can reconfigure video content in different ways, marketers and advertisers must continue to create quality content and have an extensive content library, according to Parkin. AI tools may be able to develop variations of the same video, but it’s important not to "throw garbage into a tool and rely too much on the tool to turn it into gold," he said, adding that, when handled correctly, machine learning can tell companies where they lack content that leads customers toward purchasing information or other useful material.
As marketers measure the effectiveness of branded content and ads, AI and machine learning distill massive amounts of information to inform them how and which audiences to target next, Twigger said.
Marketers can also hyper-personalize their content to target audiences based on data points like geography, weather or traffic. Geographic targeting is particularly useful for franchised brands, Twigger noted, because marketers and advertisers have to craft content that resonates with local consumers while adhering to the umbrella company’s messaging.
"Taking the brand message and flavoring it for a local audience using all of those inputs — you can't do that on a piece of paper," Twigger said.
Overstepping with hyper-personalization can come across as creepy for consumers, especially as concerns around data privacy continue to grow. With this in mind, Ratcliffe suggested marketers use AI and machine learning tools to not simply persuade consumers but to listen to what they want. Companies that don't respect consumers’ privacy and rely on these tools as a way to control consumers could see a pushback, he added.
"We’re on the verge of an explosion of storytelling in society," Ratcliffe said. "If we found a way to be privacy respectful so that we weren't strip mining one another of our personal data in order to sell that data … we'd be in a much more trusting and potentially transparent marketplace."
