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As AI revolutionizes how advertisers work, media agencies are adopting the technology to drive revenue amidst slashed client budgets and shrinking margins.
Agency leaders overwhelmingly feel that AI will have a significant and positive impact on the advertising industry, with 82.4% believing that AI will be the most influential trend to shape digital advertising in the next ten years. At the same time, media agencies have a bit of a leg up when it comes to familiarity with AI, given that they’ve relied on the technology for longer than many other players in the industry via programmatic advertising (and programmatic optimization tactics like bid shading and machine learning optimization.)
As AI develops at a rapid pace, there are an ever-expanding number of ways agencies can employ the technology to save time and increase efficiency. To make the most of AI for driving revenue and staying competitive, media agencies may want to pay particular attention to AI-powered opportunities supporting campaign planning and optimization.
One of AI’s most meaningful impacts on marketing is its ability to organize and analyze huge amounts of data in a fraction of the time it would take for a human to do so. This AI-powered capability has already revolutionized the media buying space, most notably through the advent of programmatic advertising. Today, AI is growing increasingly effective at pulling insights from audience and historical campaign data to help marketing teams craft more impactful campaign strategies. And generative AI is opening new possibilities for supporting and accelerating the campaign planning process, with 6.4% of marketers reporting that they use generative AI for tasks related to media buying strategy, and a flurry of new tools emerging that look to expand that number significantly.
AI-driven social listening, for example, is becoming table stakes for marketers. Manually sifting through social media to gain insights on the top concerns of consumers looking for a certain type of product takes hours—but AI-powered social listening tools can get it done in a matter of minutes. Using these tools, advertisers can easily track their competitors online as well as quickly generate clear insights into consumer sentiments, preferences, and trends. They can then use those insights in the planning process to ensure their campaigns are attuned to both competitor activity and consumer sentiment and behavior. For example, Fulham Football Club uses social listening to gain a more segmented and nuanced understanding of their fanbase according to their online activity, which opens up opportunities to target those segments with personalized messaging. This heightened attunement to their audience helps Fulham spend more efficiently, which in turn drives revenue.
Moreover, these types of tools aren’t exclusive to social—AI listening tools can pull data from search touchpoints and synthesize data from consumer reviews as well.
Beyond customer listening, media agencies and their technology partners are finding more and more ways to refine campaign planning processes using AI’s data synthesis capabilities. For example, some advertising platforms can employ AI to synthesize data from all the campaigns that run within them, and provide advertisers with insights into performance benchmarks and budget distribution trends amongst marketing teams working in the same vertical. AI can also accelerate the forecasting process, enabling advertisers to predict available inventory based on specific criteria and implement new strategies using the precise targeting parameters from their forecasts.
Media agencies are also mitigating signal loss by using technologies like CDPs equipped with AI to quickly gather, standardize, and leverage consumer data to pull audience insights and track the customer journey to plan their campaigns more strategically as well.
Overall, leveraging AI to implement audience and competitor insights in the planning process can help media agencies save time and craft data-driven strategies that are finely attuned to their target audiences’ needs and preferences as well as market trends, helping them better drive ROAS and deliver revenue for their clients.
AI-powered campaign optimization has been around for a while, but new innovations in this area offer media agencies a variety of ways to allocate campaign assets and budgets more effectively. In fact, AI is moving the advertising industry closer to a world where teams will spend very little time on manual campaign optimization, freeing them up for more strategic and fulfilling tasks.
Tools like bid shading and group budget optimization, which automatically make campaign adjustments to improve win rates and drive increased ROAS, have begun this process and are growing more widely adopted. As AI continues to progress, more tools such as these are expected to emerge and help advertisers drive revenue by allocating their dollars towards the tactics, channels, and properties where they’re most impactful.
Major adtech partners are also rolling out offerings that include AI-driven campaign optimization features, such as Google’s Performance Max and Meta’s Advantage+. However, these walled-garden offerings don’t come without trade-offs—the most significant one being the transparency media buyers are used to. While it’s important for advertisers to test and learn on these tools, media teams must assess whether they are actually accomplishing their goals, rather than setting and forgetting their campaigns.
Dynamic creative optimization (DCO) is another developing area that’s helping media teams save time and spend more effectively, allowing media teams to serve high volumes of diverse creative that’s personalized to specific audience segments, which makes it more likely for ads to resonate with more consumers. One Jack in the Box campaign, for example, used DCO to generate 135 different ad variations and saw a whopping 85% increase in CTR compared to the campaign’s benchmark.
DCO not only reduces time spent on manual creative optimizations, but also provides media teams with extensive insights on how all those creative variations perform, allowing them to tweak their strategies based on those learnings. The speed and efficiency with which AI can process and analyze data, and generate new content based on its findings, will doubtless enhance creative optimization technologies moving forward: Creative optimization was marketers’ third-most popular response when asked what part of the digital marketing process they expect to be most impacted by AI.
These are just a few of the many ways in which AI is helping advertisers to automate and speed up the campaign optimization process, and there are plenty more coming down the line as the technology advances. When used effectively (and carefully monitored by human teams), these tools hold tremendous promise for increasing efficiency and personalization—and thus for driving revenue for media agencies and their clients.
With over half of marketing leaders believing that AI will make marketers significantly more efficient at their jobs within the next three-to-five years, AI-driven workflow automation is another major area of opportunity for media agencies.
Indeed, all the AI-driven campaign planning and optimization functionality detailed above can help contribute to overall workflow automation, in that they automate parts of the campaign process and reduce manual workloads for marketing teams. But there are other applications as well: For example, some agencies are turning to AI copilots to automate their workflows. AI-driven copilots are LLMs that are integrated into existing tools and platforms and collaborate with the marketers using them. They improve efficiency and accelerate specific workflows, such as by detecting inconsistencies across different media formats.
By adopting AI-driven tools throughout the campaign life cycle that automate manual tasks, advertising leaders can streamline their workflows and save time. This is an application that’s been of interest to marketing organizations for some time already, with 61% of marketers reporting that their organization has invested in technology to automate or streamline processes in the past year. And adoption is set to increase, with 66% of marketers saying their organizations have plans to invest in this kind of technology within the next year.
In an era where media fragmentation, signal loss, high turnover rates, and many other factors are making agency work more difficult for marketing professionals, AI’s ability to automate manual tasks and streamline workflows is one of its major benefits for media agencies looking to save time, drive efficiency, and increase revenue.
Media agencies have a unique opportunity to leverage AI to drive revenue and enhance efficiency, at a time when such results are critically needed across the agency landscape. AI-powered planning and optimization tools are two areas that offer particularly strong benefits.
Additionally, the AI-driven campaign planning and optimization functionality detailed above can pair with workflow automation technology to help drive wider agency efficiency, reducing manual workloads for teams across the organization.
In exploring and integrating these types of AI into their operations, media agencies can open new avenues for growth and innovation, and position themselves at the forefront of an increasingly AI-driven industry.
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Curious to learn more about how advertisers are navigating AI adoption? Get all the latest insights in our report, AI and the Future of Marketing.