How AI enhances programmatic ad targeting
Currently we are in a digital context where Artificial Intelligence is transforming many aspects and Programmatic advertising is not left out of them.
Automating ad media buying was already a big leap in the marketing world and now, the environment where users are constantly generating data and third-party cookies are disappearing is constantly evolving. Companies are looking to find relevant audiences in terms of volume but also precision. This is where AI comes into play and starts to make a difference.
From basic audience segmentation to predictive models
Audience segmentation is defined as the division of a group of individuals based on certain characteristics of interest. We can divide a group into subgroups according to age, gender, geographic location or specific interests, among others and use it to target them in our campaigns.
With the advent of Machine Learning and AI, there are models that, in addition to segmenting by who is most likely to interact with the brand, allow us to predict why they would do so or when and where they are most likely to do so.
These are trained algorithms capable of detecting complex patterns and identifying signals that allow predicting user behavior.
For example, a user who at night interacts with certain types of content on social networks and in the morning browses price comparison sites, one of these models could recognize him/her as someone in “shopping mode”. This could happen even before the user himself/herself knows it. This allows advertisers to target users at the most opportune times and increase the effectiveness of their campaigns.
Learn more about how AI is transforming the ecosystem in our article on the future of programmatic advertising.
Real-time targeting
AI-based systems and models learn continuously. Therefore, another novelty that AI brings to programmatic advertising is the ability to adapt targeting in real time: adjusting audiences, bids, creatives or devices depending on how the campaign is performing in real time. This gives us the advantage of obtaining a campaign that optimizes its strategy in real time, which translates into a better return on investment.
Beyond look-a-like
Look-a-like audiences were already a breakthrough in terms of automation within this ecosystem. Artificial Intelligence is an improvement in this area. It is able to build predictive profiles based also on context or external signals such as weather, local events and even market and economic trends.
This, with the disappearance of third-party cookies, becomes very important as we seek to build audiences focused on first-party data and AI allows us to take advantage of this data and the context to obtain a highly specific segmentation, while respecting the user’s privacy.
AI and privacy
Since we are dealing with models for learning certain patterns, it may seem that all this entails less privacy. The reality is that many of today’s technologies allow working with aggregated, anonymized or even decentralized data, which guarantees user privacy at all times and complies with regulations. Therefore AI can be an excellent tool to do better targeting without compromising user trust and privacy.
Fears may arise that AI will replace marketing professionals or media teams. The truth is that if used well, it can provide us with many tools that allow us to make faster, more accurate and data-driven decisions that empower our campaigns.
In an environment where every impression counts and every campaign is measured in detail, integrating AI into the targeting strategy can take programmatic advertising to the next level.
