One of the most quickly growing media companies in Bulgaria approached Ontotext looking for a smart sector-specific solution that would address the following goals:
Simple as they may sound, addressing both goals required a multi-faceted solution, which incorporated an ad rotation tracking system, integrated with knowledge extraction, sentiment analysis and recommendation services.
To respond to the client’s needs, Ontotext implemented a solution, which performs the following tasks:
All components of the solution were customized and tuned to work with content, written in Bulgarian.
The service wrapped a set of text analytics components, which perform information extraction over the diverse types of content of the client – news articles, forum posts, user comments, advertisements.
The annotation served two purposes:
The sentiment service analyzes the comments of the users and aims to provide insights about their attitude towards the mentioned concepts, topics and products – both in the referred content and their own comments.
The sentiment analysis provides important feedback for the ad recommendation service as well. For example, the media publisher didn’t want to show an advertisement for a product, which the client clearly dislikes.
A crucial part of the solution are user-focused recommendation services. They provide suggestions for relevant content across the client’s platforms, increasing the engagement with the content across the sites of the media company. In addition, they support serving the most relevant advertisements to their users.
The recommendation services are based on a user profile model, which takes into account:
As the client wanted to improve their control of the serving of advertisements and their relevance to the users, Ontotext built a custom ad serving platform. It provides the expected ability to register marketing campaigns, manage banner serving zones in the websites, integrated with it, and take care of meeting the rotation targets.
Apart from these standard features, a key differentiator of the system is the ability to target users more relevantly, by utilizing the user-focused recommendation services. By integrating the ad serving with these recommendations, which know about the users’ interests, preferences and sentiments about specific concepts, Ontotext was able to achieve more relevant user targeting.
As a result, the algorithm took into account not only the rotation targets for the advertisement but also calculated the proximity of a user profile to the ad’s content. Based on this semantic analysis, the system could select an advertisement from a number of candidates for a banner zone and match the media readers with the most relevant ads.
Ontotext’s solution for smarter recommendations and ad serving enabled the media publisher to minimize costs, increase efficiency and improve user experience.