How to predict hits

Two elements can be relevant for predicting a hit song. These are: The “velocity of the tagging” and editorial judgement. It is the result of an interesting analysis run by a company based in London called Shazam. The first aspect is related to the level of engagement between artist and audience and how quick it is their judgement in terms of tag data per day. Therefore, this also shows that the amount of interest expressed could be less relevant in comparison with the timing of response.

The process starts in choosing a leading indicator for the songs to be considered potentially succesful, providing a report of tag data per day who have been received by the platform. After that, the evidence shows that there is a relationship between the impact of the songs in commercial and the rise of them in Shazam chart. Once reached the number one position, a direct consequence was provided by the climbing of Billboard’s Hot 100 classify: This result happened for several artists that gained positions during previous year,  as Lana Del Ray, Frank Ocean…and it’s the consequence of an accurate analysis about data and metrics measuring the commercial viability of the song itself. There will be other predictions for the next year and there is already a list of the possible hits. In addition, record labels are using this system for testing new tracks and the tags can also be driven by TV as in the example of “Too Cloose”. Infact the evidence shows that happened a significant increase from 10 tag a day to ten thousands in a single day after being featured in an ad for Microsoft IE9.  “Somebody I used to know” was included in the prediction according to the data provided by the company and some songs included in the report were not still commercially released.

It’s worth to say that this tool can de defined as a new business model. This could be very useful for labels that feel the importance to understand the target audience and to decide where to put maketing efforts.

Click to access Top-Tagged-Songs-and-Artists.pdf