For new brands, directly allocating advertising budgets to platforms like Meta can yield a better return than hiring traditional ad agencies. These platforms' powerful algorithms and reach can develop more effective campaigns than human-led creative teams, democratizing access to high-quality advertising.
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The next evolution, the Generative Ads Recommendation Model (GEM), aims to fully automate ad creation. Marketers will simply provide an image and a budget, and the AI will generate the entire ad library. This shifts the marketer's primary value from ad creation to optimizing the post-click customer journey and offer.
As ad platforms like Google automate bid management, an agency's value is no longer in manual "button pushing." The new competitive edge is the ability to feed the platform's AI with superior client data and insights. Agencies that cannot access and leverage this data will struggle to demonstrate value.
The largest advertisers on platforms like Meta launch over 10,000 new creatives a year, equating to more than 40 per workday. This massive scale of experimentation is manually impossible for most companies, creating a clear market need for AI platforms that automate and scale video production.
By paying a creator a flat monthly fee (e.g., $900) for daily posts, brands can achieve a cost per thousand impressions (CPM) of around $2. This is a significant discount compared to the average $6 CPM on platforms like Facebook, representing a major marketing arbitrage opportunity.
A new AI tool in the Partnership Ads Hub analyzes organic creator content performance before it becomes an ad. This allows brands to make data-driven decisions on which creator posts to boost, removing guesswork from influencer marketing and ensuring ad spend is allocated to content that has already proven its effectiveness.
Agencies are optimized for efficiency, stifling the creative experimentation needed for platforms like Meta. Top-performing brands employ an in-house strategist whose sole job is generating a high volume of diverse, "wacky" ad concepts—a function that can't be effectively outsourced.
Previously, marketers told Meta who to target. With the new AI algorithm, marketers provide diverse creative, and the AI uses that creative to find the right audience. Targeting control has shifted from human to machine, fundamentally changing how ads are built and optimized.
Instead of testing individual ad variations, advertisers can use the "Dynamic Creative" (for leads) or "Flexible Creative" (for sales) toggles. This allows combining multiple top-performing images, videos, headlines, and text into a single ad unit, which Meta’s algorithm then mixes and matches to find the optimal combination for different users.
With Meta's Andromeda algorithm automating audience targeting, the primary reason for poor ad performance is no longer incorrect targeting settings. Wasted money is now almost exclusively a result of insufficient or non-diverse creative, making creative strategy the most critical component of a successful campaign.
A new Marketing API feature allows Meta's AI to allocate up to 5% of ad spend to placements explicitly excluded by an advertiser. This signifies a major shift towards autonomous campaigns, reflecting Meta's confidence that its system can identify performance opportunities even in channels that human advertisers have ruled out.