The Topspin tracker is used to facilitate a better user experience. We identify two main areas where the Topspin tracker generally is used and with their own specific use case.
The Topspin Tracker measures visits on pages (WEB) or sections (apps). This allows us to investigate how users navigate through a platform and what content is popular.
Player events are crucial to analyse how and when media content is consumed by users of the different platforms. The player will generate events when a user starts, pauses or completes a stream, but can also indicate if a stream is watched through an external device (e.g. Chromecast). It also sends an event at set intervals to indicate that a stream is still playing. The data coming from all these events allows us to make thorough analyses of the content we provide online.
From the player events several important insights can be gained, it can inform the business of what type of content works well on what days, or what time of day. Do people enjoy an in-depth documentary more on a Monday morning, or more on a Friday evening when they have a bit more time on their hands? Answering such questions can lead directly to curation of content. Player events are used to analyse what content certain users consume together. For example, users that watch show A and B make a case that recommending show B in the interface of show A is attractive. This forms the basis of our current recommendation algorithm. As such, obtaining accurate viewing statistics are essential, for the continuous performance and improving our recommendation algorithms.
A second vital component that relies heavily on data coming from the Topspin tracker are media recommendations. We strive to serve relevant media - be it audio, video or text - to our users. Hereby, recognizing that nobody is the same. The trick is getting the right content to each user, based on the users specific needs and our core values, thus providing the user with a wide spectrum of content. In order to receive feedback on the content we offer to users, we monitor how often certain content is being offered, but also chosen.
One clear metric for recommendations is the Click Through Rate (CTR), this is for us the ratio of choices divided by the offers for a specific algorithm or service on our platform. For example, the Topspin tag offers (pun intended) the possibility to measure offer and choice events, allowing for the in-depth analyses needed to mature these services.
The data can be further enriched with providing more detail, such as:
The Topspin tracker allows for measuring user search queries in order to easily access content. It does this by treating suggestions based on the query text as recommendation offers and the chosen item as a recommendation choices. By implementing the Topspin tracker on search queries it allows for analysis of the quality of the underlying algorithm.
We support a tailor made implementation for the analyses of lanes (linten) on NPO Start. The offering of content through these lanes is considered a recommendation for the Topspin tracker. The type of page, name of the lane the content is offered in, and the total amount of media ID’s in the lane are all parsed to the Topspin tracker. A successful implementation of such custom event tracking is only possible if all platforms implement the measurement according to the predefined standards set for this particular case.
Additionally to the previously described use cases of the Topspin tracker, it is used to do one-off or ad-hoc analyses. Such analysis are for example, monitoring the effect of a particular marketing campaign, or checking if traffic is being generated from social media platforms, etc.
Please note that in order to gain the most from the Topspin tracker a careful implementation is crucial. We try to make implementing it as easy as possible. If anything is unclear, please do not hesitate to contact us.