Programmatic ads, what really are they?


Programmatic advertising, in simple terms, is the automated trading of online advertising space. It leverages Machine Learning (ML) and Artificial Intelligence (AI) to buy and optimize online campaigns. This reduces manual effort and negotiations with publishers, ensuring the focus stays on optimizing campaigns in real-time.
The process is smart and instant too. Here’s how it works:
Programmatic ads can be useful for companies across industries. Back in 2014, Kellogg’s saw some impressive results. It ran programmatic ads in the digital space to drive offline sales. The brand enjoyed +70-80% impressions and 2X improved targeting. This was topped up with hyper-targeted ad campaigns.
It is estimated that 88% of US digital ad spending will be programmatic by the end of 2021. It offers a more efficient and effective strategy for marketers looking to better their performance and returns. The major advantages are:
4 key types of targeting work in the world of programmatic advertising. Let’s take a look:
As we saw above, there are different types of programmatic ad targeting strategies but they all have some dependencies on user data. This, however, is not true for contextual targeting.
Let’s say you have clicked on an advertisement or simply visited a website. An ad of that particular brand might appear many times as you surf the web, leading to ad fatigue and poor user experience. Often, these ads appear on random websites too.
This is the problem with audience targeting and retargeting strategies. Even if you consider website targeting, the marketing universe could sometimes become a little limited. For example, assume that you are a brand selling luxury cars. There are only a limited number of sites that you can list down for website targeting.
With contextual targeting, you can expand your universe to list down relevant sites like fashion or lifestyle. These categories will help you reach your target audience in a smart, well-rounded manner, while still being relevant. It helps look at the complete context of a website and undertakes a human-like analysis of the page and all its elements. Text, video, imagery, URL – all of these are analyzed in totality to understand the context well. Hence, the ads can be placed in a way that matches the environment around them.
A good contextual advertising tool can help take your brand places. In fact, it can help you take your brand to all the RIGHT places, guaranteeing better marketing ROI. Your brand can leverage the power of AI and ML to optimize ads and keep innovating. Contact us today to know how!
Find answers to get the most out of Seedtag.
Neuro-Contextual Advertising is an evolution of contextual advertising that uses AI to understand interest, emotion, and intent within content. Instead of relying on personal data, it helps brands align advertising with the moment people are experiencing in real time.
Contextual advertising places ads based on the content a person is engaging with, rather than personal browsing history or identifiers. Neuro-Contextual approaches go beyond traditional contextual targeting by understanding audience interest, emotion, and intent.
CTV advertising refers to ads delivered through Connected TV environments, including streaming platforms and smart TV applications. It allows brands to reach audiences across premium video experiences using more contextual and privacy-first targeting approaches.
Liz is Seedtag’s proprietary Neuro-Contextual AI, designed for full-funnel advertising across premium open web, video, and CTV environments. Grounded in neuroscience, Liz understands contextual signals such as interest, emotion, and intent in a human-like way to deliver relevant advertising experiences in real time while respecting user privacy.
With consumers increasingly wary of data collection and cookies, privacy-first advertising focuses on delivering personalized and relevant ads while respecting user privacy. Neuro-Contextual advertising enables relevant advertising experiences without relying on personal data or third-party cookies.
Leveraging neuroscience principles, Liz recognizes patterns, interprets context, and responds dynamically to user interests, emotions, and intentions. This creates a more cohesive and intelligent system capable of delivering more relevant advertising experiences.