Over the past year, we have completely overhauled our approach to identifying user interests. By leveraging deep neural networks and advanced language models, including SeLLMa from Seznam, as well as the latest natural language processing techniques, we have achieved significantly more accurate content classification. Let’s summarise what this means for you.
Previously, we used techniques to convert text from visited websites into a basic form, known as lemmatisation, so that it could be easily analysed. Based on the occurrence of typical keywords, we then categorised the texts according to relevant interests. However, this method was unable to capture the overall context of the content fully.
We now generate hundreds of sample articles for each interest category, using advanced methods to compare the content with predefined patterns (a process known as vectorisation). This approach enables us to assign users to interest categories with significantly greater accuracy. Additionally, we have begun training our language model according to the IAB taxonomy, enabling us to transition seamlessly to a pan-European standard for identifying interests in the future.
In light of this new feature, we recommend regularly checking the results of campaigns targeting user interests. To reach a wider audience, consider increasing your cost-per-click (CPC) bid or adding related targeting.
We believe that the new interest targeting feature will help you to achieve even better results and reach a more relevant audience. If you would like more information or support, please contact your Sklik consultant or use our contact form. We are always happy to advise you on how to make the most of more precise targeting.
Over the next few weeks, we also plan to introduce new targeting options for RTB, enabling you to use it for programmatic advertising. We will inform you of the exact launch date.
For the identity and user profile division, Jiří Udatný
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