Modern online advertising and content recommendation practices rely heavily, if not exclusively, on tracking user activity across the web and apps. Organizations follow the belief that past user behavior will represent future user interests and needs. We see three major issues with this current practice. 1) ad campaigns are ineffective and spammy with click-through rates and conversion rates that continue to decline, 2) current analytics and targeting rely on poor classifications and particular user actions (e.g. views or clicks) while the content users read or contribute is ignored, 3) current services violate user privacy.
Content analytics is the drive-train for high quality and effective advertising and content recommendation technologies.Chris Margiolas
Transforming spammy into resourceful
We firmly believe that ad targeting and content recommendation should rely more on understanding the content users interact with across the web and mobile applications. Users are more positive towards ads that are relevant to the content they interact with, as they find them more resourceful for their current needs. As an example, a user that reads about cooking would be interested in cookbooks and cooking appliances, not a car lease she searched for a month ago.
Leveraging content instead of behavior
Understanding diverse content across web and mobile applications is a challenging task. We need to understand content of different forms including articles, social media posts, short conversational style messages and comments. Also, the content we need to analyze has diverse origins which affects the way ideas are expressed and communicated. A successful analytics technology understands the differences and adapts on the fly.
Furthermore, the lifespan of content that users interact with can vary anywhere from a few seconds (ex. news feed or message app) to a few years (a high-quality article). The content analytics technologies that drive advertising and content recommendation need to perform in real-time to guarantee proper understanding of the most recent content, while introducing minimal latencies.
Upholding privacy standards
The content analytics technologies need to guarantee user and content privacy by instantly filtering out any sensitive or private information about the user and the content. A successful service has a fine-grained understanding of content and does not require information about the user and her activities in order to deliver a resourceful ad or content recommendations.
At adNomus, we deliver AI technologies for real-time content analytics. By focusing on understanding and targeting content, we help organizations to serve relevant ads and content recommendations that increase user engagement by multiple times.