Seedtag, the leading Contextual Advertising Company, introduced Contextual Profiles today, a solution that allows advertisers to deliver effective performance campaigns using real-time contextual signals without cookies or any personal data.

As the amount of time people spend online has increased, so has consumers’ awareness of the ways in which they are being tracked online. Most consumers don’t feel they are receiving any value in return, meaning the possibilities of ads receiving attention and converting into sales are increasingly limited. By leveraging Seedtag’s Contextual Profiles, brands can directly impact users at the right moment and in the most relevant content. This leads to improved immediate feedback, and ultimately, better performance.

Seedtag’s Contextual Profiles combine two types of real-time signals to evaluate the likelihood of a user being receptive in that moment and thus taking action:

• Web-context signals (human-like understanding of content based on AI-driven text and visual analysis).
• Situational context signals (eg. location, time of day, weather or screen orientation, etc.).

When users are surfing the internet looking for something that they are really interested in, the best chance for a brand to get user’s click isn’t serving them an ad related to what their browsing history suggests they might buy. The smart move is to serve them an ad that helps them choose something directly related to what they are searching for in real time, that is where web-context signals play an important  role.

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But Seedtag contextual profiles go even further. Seedtag can comprehend what content users are viewing, and use the context of their actions to predict their habits and behaviors. By using advanced situational signals such as scroll speed, the weather or even screen orientation to not just serve a highly relevant ad, but ensure it is in the perfect spot on the page.

Combining these signals allows Seedtag to gain a better understanding of the users’ interaction with the content they are consuming, to really know when the user is “in-context” ie. when they intend to take action based on that content they’re currently engaged with.

For example, Seedtag has recently worked with the world’s largest furniture retailer to help them increase awareness and drive sales of their new outdoor furniture collection. Seedtag was able to offer Contextual profiling as a solution, allowing the client to know when the users were “in-context” and likely to visit the webpage. Seedtag analysed the impact weather had on the campaign and integrated the results in the activation as a key contextual variable. It was proven that web page views increase when there was bad weather and that people were more likely to buy outdoor furniture when the weather forecast was going to  change from bad to more favourable conditions. This resulted in a 67% reduction in the cost per session and established the client as a leading provider of outdoor furniture.

Mike Villalobos, Head of Performance US at Seedtag, said: “With the application of Seedtag’s deep learning models, we’ve evolved contextual advertising to human-level comprehension. Our ability to identify macro trends with a myriad of signals around a reader’s consumption in real-time provides our partners with highly targeted solutions without infringing on the privacy of the person behind the screen. With persona-based audiences becoming stale and inconsistent, Seedtag has refined the balance of scale and accuracy with real-time situational signals of a reader’s environment and web-context derived from the content of interest. The result of our advanced comprehension operating system, Liz, is real-time targeting segmentation and creating contextual profiles to drive actions needed to propel business needs forward.”

Integrating these contextual targeting capabilities will allow the industry to rise to the challenges brands and agencies are facing in driving decision and action. Seedtag is now able to offer brands a full-funnel contextual solution that develops contextual profiles in real-time and in a non-intrusive way, driving improved performance without sacrificing efficiency.

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