Future of Production: Why AI Delivers Video Viewers Want to Watch
Video is the advertising 'medium of the moment' is an insight that probably won’t shock you, given viewing figures for YouTube and TikTok. What might be surprising, though, is the speed at which it’s starting to dominate how consumers engage with marketing messages.
According to Tech Jury, 90% of customers say they rely on video when deciding to make a purchase. Further up the funnel, 79% of consumers like to research a product by watching a video rather than reading about it.
Meanwhile, more than half of consumers (55%) watch video content on a daily basis when they’re online. Even better for video marketers is the claim that 80% of people remember a video ad they saw within the previous 30 days.
It’s clearly a lucrative ad format: 83% of marketers claim video provides good ROI, as well as leading to 49% faster revenue growth than any other approach.
So far, so good. But video content could be even more effective and efficient than that. Let’s take a closer look at why marketers might not be making the most of their time with a captive audience of video viewers.
At present, typical video analysis tools use platform-specific video ad performance data, and almost certainly don’t lean on AI (even if they claim to).
This leads to false insights: the data offers a one-dimensional view of content’s effectiveness. But we know that the way people engage with video differs from one watch to the next, let alone from person to person.
Not only that but - just like watching a movie where you start out believing the narrative, only to later want to quit the cinema because the characters and dialogue no longer make sense - we know that how a viewer feels about the content from one frame to the next changes, too.
If performance data only offers platform-specific metrics like view-through rate, CTR or retention curves based on a surface-level understanding of consumption, crucial elements such as content, messaging and context can clearly be overlooked.
Brands are becoming wise to this oversight - and that’s why they are increasingly tapping into tools that offer a much more granular view of video ad effectiveness.
Creative-Led Video Insight
Looking at video metrics through a creative lens, drawing on data to understand effectiveness, is key. Cutting-edge tools also drive efficiency throughout the production process; crucial for any brand when budgets are being squeezed by ongoing pandemic cutbacks.
So, what are the elements of these tools that provide brands with a much clearer vision of how creative is faring in the eyes of their consumers?
Strategic set-up - by identifying brands’ video content challenges at the start of the campaign, we can tag those aspects within platform to focus on, and drill down into, specific data points required for a better understanding of ads’ effectiveness.
Critically, this means concentrating on elements that can be improved to boost performance. Problem areas can be monitored over time and transformed into opportunities.
Pinpointing preferences - marketers who have wondered whether some parts of their video content resonate with audiences more than others should look no further: now every scene, message, GFX overlay, call to action - and more - can be put under the microscope and run through our proprietary scoring methodology to identify trends.
Closer campaign metrics - one of the most exciting aspects of new video analysis tools is the granularity of insight. For example, promotional content for a new TV series may feature multiple characters; the platform identifies which are more or less popular among viewers. The same can be gleaned for product campaigns, informing future executions.
What the viewer wants – the value of in-depth insight about what resonates is that creative can be optimised accordingly either pre-campaign or while video content is already live in market. By analysing what lands well with viewers and adapting the ads to better suit their needs, brands are truly presenting audiences with video they want to see.
Wrapping in past content - brands don’t always need or want to go back to the drawing board. The new tools enable analysis of previous campaign ‘content libraries’ to pinpoint the most engaging and effective aspects of existing work; further building efficiency into content strategies and the production process.
From input to output - the tools don’t just provide data; the insight becomes the basis of creative optimisation. Reporting determines best-performing segments, topics and themes to inform content recommendations for specific durations, aspect ratios, and themes.
Throughout the process, brands can liaise with analysis teams to take a more data-led approach to developing content strategies for future campaigns.
The Future of Production
The beauty of a modern approach to video ad analysis is that the granularity of insight can be applied in many different sectors and, importantly, across video platforms and formats - informing entire campaign strategies and production ecosystems.
For brands, this means a smarter way to drive consumers through the sales funnel; ROI that’s boosted by up to 50% on average, but often much more; and better navigation of emerging channels of choice such as TikTok.
For agencies, it brings together creative and data to provide guidance on where and how to cut video content, streamlining and removing subjectivity from the process and providing improved results.
And, of course, there are benefits for the consumer, too: optimised content opens more eyes, creating stronger connections and relationships between them and the brand.
The days of churning out video content and expecting it to play well among all audiences, without really knowing what works and why, are over. AI-driven visual content analysis and production tools will be key from now on, helping brands and agencies inform creative to deliver the right messages to the right people - ultimately building engagement and revenues.