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Use AI to optimize Ad serving and drive revenue growth


The application of artificial intelligence (“AI”) in online advertising is growing fast. An IBM survey in the US reveals 63% of major ad tech companies are embracing AI, including powerful algorithms, data models and machine learning, to unlock actionable consumer insights and automate ad campaigns.

AI has drastically improved the performance of optimizing ad serving in many different ways. Let’s get into the details below.


Ad serving without AI

Before the advent of sophisticated smart technologies like AI, marketers could only rely on manual efforts. They thus experienced various restrictions when it comes to ad serving, ranging from high latency, forecasting limitations, vague targeting due to insufficient data processing, and unscalable audience bases. They then turn to AI for efficiency and effectiveness.

A good example of AI in action is the AlgoAD ad serving solution. With the help of AI, it enables ad publishers and media owners to monetize and maximize the yield of their advertising inventory through automating the selling of advertising space and tailoring of audiences’ experiences.


AI in advertising action

  • Inventory forecasting gets smart

Having an adequate amount of ad inventory on hand against the backdrop of a rapidly changing environment is essential for advertisers and publishers. Inventory forecasting looks at trends, past data and other inputs to predict the right inventory level needed to meet future needs.

AI automatically sifts through this information to make the process of inventory forecasting more accurate and flexible and quicker, which reduces the risk of campaigns being sub-optimally delivered and increases retention and engagement.

With smart inventory forecasting, ad serving engines can deliver ads more evenly and with better reach, as well as better use available ad slots, lowering wastage and preventing overselling.


  • Machine learning boosts click-through-rate (“CTR”) optimization

Another area that’s benefiting from the application of AI is click-through-rate (“CTR”) optimization. Many marketers value the CTR of the ad as it can more precisely evaluate campaign performance. Therefore, some advertising campaigns are moving to the cost-per-click (“CPC”) performance-based pricing model, and away from the impression-based cost-per-mile (“CPM”) pricing model.

Improving CTR is one of the fastest methods of increasing conversions and ultimately generating more sales. A higher CTR, usually a crucial advertising campaign KPI, means the delivered ads are more relevant to target audiences, which is very important for achieving better sales and return-on-ad-spend (“ROAS”).


  • Look-a-like modeling algorithm uncovers new audience

To help advertisers find audiences who behave similarly to their best converting customers, look-a-like modeling algorithms are used. They will first analyze the profiles of users who convert, deriving a set of shared characteristics, and then find potential targets that exhibit the same characteristics.

The tech is enabling publishers to extend their audience segments by uncovering new audiences with similar attributes. In this way, they can deliver targeted ads to bigger customer bases in the privacy-first era.


AI is transforming the data-heavy digital advertising world. Don’t miss the key to unlocking business growth, contact HKAI today to learn more about our AlgoAD ad serving solutions.

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