If Netflix’s decisions on marketing its hundreds of original shows seem highly calculated... that’s probably because they were. Netflix has outlined how it uses AI to market shows and predict their success in ways that conventional box office numbers and Nielsen ratings likely couldn’t match. Effectively, it comes down to finding connections and determining the likely audience sizes.
The method relies on transfer learning, where the the parameters learned from a “source task” improve the performance of a “target task.” In this case, the source tasks are simple: what titles are comparable to a Netflix original, and what kind of viewership can the service expect?
For thematic comparisons, Netflix creates a “similarity map” where AI uses a show’s metadata, tags and summaries (“embeddings” in Netflix’s world) help determine links to other titles. Marketers would know which shows and movies to help describe a coming-of-age comedy, for example.
With audience sizes, the service has an AI model that compares the audience sizes of similar work in a given country. If a drama is likely to fare well in Spain, Netflix might not only ramp up marketing in the region but prepare dubs and subtitles earlier.
The systems are self-supervised, letting them access a much wider range of titles than they would if they were limited to Netflix’s own info.
Netflix’s approach might not be thrilling if you prefer the human approach — there’s nothing quite like an indie production getting a huge audience after an executive takes a chance on it. The AI makes it easier for Netflix to market a flood of originals, however, and eliminates some of the subjectivity that could hurt the success of some shows.