By Matt Hertig, CEO and Co-Founder of ChannelMix
The rise of commercially available AI technologies could not come at a more perfect time for the advertising industry. The slow demise of cookies will finally reach its terminus: Google is steadfast in its commitment to eliminate support by the end of 2024 and we see no reason why that would change in the next 12 months. In fact, starting last month, Google started blocking cookies for 1% of Chrome users.
The robust targeting that has built the modern advertising industry, especially that of programmatic advertising, is going away. As such, the advertising market will look very different at this time next year. But marketers have a powerful tool at the ready to recapture some of that targeting functionality: artificial intelligence. The ascendency of AI is here to help marketers make smarter decisions with less data than they might have had in the past. And just in time because the third-party data they have depended on is going to trickle away.
There is only one challenge: AI models need to ingest significant amounts of data to be useful. For example, ChatGPT and the other competitive generative AI models that have delighted consumers with their robust answers to any question under the sun are only able to do so because of the incredible amounts of data that trains them. The visual AI generators like HuggingFace can only create the odd fever dream images you’ve asked them to make (e.g., Socrates playing Fortnite on a Xbox) because the model has studied drawings of Socrates and pictures of Fortnite and Xbox).
So advertisers that are understandably excited about AI need to take two important steps if they want to maximize the technology’s potential. First, they must rein in their data and centralize it. With the cookieless horizon in site, few companies are prepared. Now is the time to take control of and ownership over relevant data, including offline media, sales data, and more. Then they must clean it and activate it in a reporting stack that AI can access and influence. Given the messy nature of marketing performance data, this is a task best handled by industry experts, not your IT team.
Only then can a company feel confident that AI-driven targeting and reporting will be accurate and value additive.
But the beauty of AI models is that they can continue to learn and train themselves to become even more accurate over time. Once you accomplish that, it’s time to use AI in the context of your data ecosystem to drive powerful insights. But there is a specific roadmap you should follow if you want to unlock the true potential of AI.
Four steps to manage AI
- Plan: Marketers’ historic concern has been understanding how much budget they’ve been given and then work to spend that optimally to drive ROI. AI offers the opportunity to flip this on its head. They can now ask “How much should we spend to maximize impact?” and be able to demonstrate to executives how that spend will translate into organizational KPIs. Put another way, AI enables users to build their budget based on the target goal they want to achieve. Instead of spending until you reach a sales goal (or more likely fall short because you didn’t have the right allocated spend), you can start with what you need to achieve and your models can help make the case for the budget you would need to deliver.
- Predict: How can AI near-guarantee results? It delivers multiple scenarios in real-time, predicting results and ROI. You can run the numbers on each scenario to know which budgets will create the optimal results. If there are uncertainties in your plan, you can toggle up and down variables and see how that affects the overall campaign.
- Prescribe: Once you’ve established a plan and AI has predicted efficacy through modeling, AI can then suggest a media mix that will reach your targets as efficiently as possible. It can zoom in on the most likely channels to convert and the most effective platforms to advertise on, avoiding or eliminating waste. It tells you exactly how to spend in each marketing channel and platform. It also helps you understand where the holes are in your data, reining in data points you need to run even more effective campaigns in the future.
- Pace: Advertisers have learned in recent years how important it is to monitor ad effectiveness in flight versus a postmortem where you can no longer make adjustments. But doing so manually is a laborious process where campaign managers may struggle to identify actionable insights. AI, on the other hand, keeps track of how well its predictions are performing and can deliver daily insights to ensure the plan stays on track. As conditions change, AI will discover how they impact your campaigns and can even make adjustments on the fly without requiring human interaction.
The cookieless future needs AI to maintain ad effectiveness. But have no fear, that future is here (and will only get better month-after-month). Now is the time to get your data priorities straight and invest in advanced technologies and experiments, so you’re ready for the huge changes coming this way. Now begins the sprint to the AI future – make sure you’re among the first to embrace the technology that will change the future of advertising.
