Home Data-Driven Thinking Unlocking The Power Of AI In Contextual Targeting: A Guide For Agencies

Unlocking The Power Of AI In Contextual Targeting: A Guide For Agencies

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Rob Silver, EVP, Head of Media at Razorfish

The rise of AI is rapidly changing the way agencies and marketers must approach media. Technology companies have developed AI solutions that inform how they shift budgets and strategies toward contextual solutions that bypass the need for any third-party data. 

However, a change is occurring as platforms pivot and push hard at AI-driven optimizations. Advertisers got used to having complete transparency as we moved from managed to self-serve programmatic. And we dove deep into understanding every aspect of the bidding algorithms to drive optimizations and business outcomes. But with AI, a transition to black-box optimization requires agencies to build and develop new skills, ways of working, custom tools and processes. 

Only then can we better understand how platforms are optimizing AI to communicate insights and ultimately put proper guardrails on the algorithms. 

Winning in the future

To future-proof marketing strategies and prevent spending on third-party targeting from spinning out of control, marketers must not only invest in first-party data capabilities but make a hard turn toward contextual-based targeting. This will help them take advantage of their platforms’ native AI capabilities by implementing strong controls and governance.

Previously, marketers’ options for contextual targeting were limited, focused on linking ad creatives to publishers’ content to reach an assumption of their target audiences. Over the last few months, however, major advertising platforms have introduced AI-powered solutions to help provide marketers with deeper actionable intelligence to build contextual campaigns. These solutions can pull insights based on how ads perform depending on placement, searches and audience performance.

While these tools are extremely useful, they are still somewhat limited in their analysis capabilities, and there are still plenty of gray areas in terms of how the AI is making adjustments.

Controlling AI

To achieve optimal performance, marketers need to create workflows within their tech stack. This will help them gain additional visibility into how ads are actually showing up in different networks, identify relevant searches to appear in and derive deeper insights from audience targeting and delivery.

When using new AI products, advertisers should focus customization on approximating the same optimization levers and layers of control that are available within existing solutions. It’s also important to provide audience suggestions based on what the platforms know about their current customers. These suggestions are the same signals that the AI will use to find similar audiences, so it’s worth understanding them.

These audience suggestions, when combined with the right segmentation strategy, can teach advertisers more about who their ads are resonating with and which creative messages are most effective. Additional automation can also help advertisers address brand safety concerns and make real-time exclusions when analyzing where ads are showing up.

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Obsess over testing

As marketers move away from third-party cookie targeting, they’ll need to account for a robust testing road map to identify areas of friction. 

A comprehensive testing approach looks at three key areas: identity solutions, contextual targeting solutions and cookieless targeting solutions.

The payoff of the investment in testing campaigns with these new solutions is to better predict post-cookie campaign outcomes. These predictions should not only improve the relevancy of the content being delivered but enhance the timeliness of the delivery.

AI will emerge as the connective tissue to accomplish testing on these metrics at an advanced scale. But advertisers setting the parameters will be critical to accomplishing this with maximum efficiency and ROI.  

As marketers continue to navigate the uneven path toward a privacy-first working model, it’s crucial to stay ahead of the curve and not let ongoing platform delays instill a false sense of security. This wave of AI solutions is the new frontier to master targeting and maximize impact. With the right strategic shifts, marketers will build a resilient foundation for future growth and success.

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

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