If you are a marketer running advertising for your brand that includes digital advertising, programmatic is essential. This digital ad practice uses AdTech software to automate purchase, delivery, and measurement of digital ads across sites and apps.
Programmatic allows you to reach users across all devices, including mobile, desktop, TV, and connected home.
The dynamic partnership of AI and media buying elevates advertising results. AI strengthens programmatic advertising by handling complex tasks faster and more accurately than manual methods. An AI and Programmatic partnership sharpens targeting to reduce wasted impressions, personalizes ads in real-time, and optimizes bidding and ad budgets.
In the end, the partnership of the two gives you more relevant messaging, stronger engagement, and improved ROI.
Learn the pros and cons of connecting artificial intelligence and programmatic buying.
6 Benefits of Using AI in Programmatic Advertising
If programmatic advertising is already automated, why should you include AI in the process? There are a number of additional benefits to partnering your programmatic ad buys with AI.
- Efficiency: AI automates manual tasks, which enables you to expand your campaigns more quickly.
- Precision: More accurately optimize ad campaigns to limit wasted impressions and improve engagement.
- Personalization: Real-time large data analysis produces hyper-relevant ads.
- Cost-Effective: AI supports smarter bidding, which leads to lower CPMs, maximizing budget use, and improving ROI.
- Testing: AI can test an endless number of creative combinations and targeting parameters in real-time, rather than relying on traditional A/B testing results.
- Creative Deployment: AI accelerates creative iteration cycles, allowing you to update creative more quickly
Best Practices & Recommendations
Many of the best practices you should implement for your AI/Programmatic partnership are similar to those of traditional media buying.
- Set clear goals and KPIs
- Know your audience
- Prioritize privacy targeting practices
- Connect media and messaging
- Test and Learn
- Maintain human management
At some point in the not-so-distant future, AI may be able to manage all programmatic advertising stages autonomously, but for now, it is critical for media managers and marketers to retain human oversight, at a minimum, to check for strategy and brand safety.
Dr. Gregg Feinerman, owner and Medical Director of Feinerman Vision, coordinates his business’s programmatic advertising efforts. He learned firsthand how valuable the test-and-learn approach can be to advertising success. By partnering AI and Programmatic for his practice, he discovered a unique timing opportunity that falls outside the traditional seasonality of his business.
“Our system showed timing trends that go against standard medical marketing wisdom. Implementing AI into our programmatic advertising showed September has a 67 times higher conversion rate and costs 43% less per click than the standard January timing we traditionally focus on.”
Dr. Feinerman was also able to tap into segment intelligence. “Older patients have more free time during weekends and evenings, which is why traditional marketing targeted those times. Our AI data observed something different with ideal conversion results on specific weekdays and morning hours that led to conversion rates jumping from 3.1% to 12.3%. This intel has driven us to move 70% of our cataract ad spend to those weekday morning times, which led to an 89% increase in consulting room bookings.”
An additional best practice is implementing explainable AI tools that reveal how and why AI makes the decisions it implements. These tools help you retain ownership and make ‘black box’ decisions rational and transparent.
What to Watch Out For With AI.
AI effectiveness begins with clean, privacy-compliant data. Humans need to ensure that regulatory procedures are managed when using any type of automated system.
Depending on the AI system you are working with, it may not be completely transparent. This may lead to difficulty deciphering targeting or placement rationale. Giving up too much control to AI can endanger your brand.
AI is also known for bias. Until artificial intelligence guarantees that segments are neither excluded nor reinforced, humans should closely watch output and ensure campaigns are run with ethical placement.
Ad fraud and quality of inventory are additional issues users should consider when partnering AI with programmatic. AI is not always able to identify ad fraud, where fake clicks and conversions occur to improve results. And not all AI-driven tools have eliminated placement on made-for-advertising sites. These sites are created solely to make money by feeding up large volumes of ads without much, if any, beneficial content provided.
Despite the number of positive results marketers can achieve by marrying AI with programmatic ad buys, there is still a need to keep human hands on the controls. Without human oversight, you may achieve mixed or negative results, not knowing which you’re dealing with.
Todd Stephenson, Co-Founder of Roof Quotes, recently tested AI to guide how they buy media programmatically, looking for faster optimization. Todd reported, “Although the system was able to shift spend across channels in real-time and quickly identify clusters of homeowners searching online, the downside came when AI pushed too aggressively toward short-term conversion by over-indexing on branded keywords and retargeting pools.”
Todd quickly saw lead quality dip in favor of cheaper, poor-quality clicks. He had to dial back the autonomy and add human checks back to the system.
“This experience taught me that AI enhances ad buying only if you build in controls and review performance.”
4 Tactics for AI Ad Setup and Buying
Taking into account the downside to AI, applying it to ad setup and buying processes, AI introduces smarter, data-driven methods that streamline planning and execution. These tactics make campaigns more efficient and impactful.
- Forecasting and Predictive Analytics – AI can support campaign planning with recommended budget pacing and KPI outcomes based on predicted campaign analysis.
- Automated Real-Time Bidding (RTB) – although not exclusive to AI, automating RTB with AI can reveal bid values based on predictive modeling and past data, taking advantage of data-driven decision making.
- Segmented Targeting – in addition to human-led segmentation, AI segments audiences using contextual, behavioral, and demographic data, accelerating personalized ad delivery at a significant level.
- Creative Optimization & Dynamic Personalization – AI is able to customize creative files in real-time based on performance, offering scalability in testing and improved results.
Including AI in your programmatic advertising strategy enhances precision, automation, and scale, and can be a game-changer for reaching and exceeding your goals.
When managed responsibly, AI can be a valuable tool to improve the efficiency and outcomes of your campaigns. However, it’s imperative to find the balance between AI and Human management to navigate the challenges still provided by AI, like obscurity, bias, and control.