New machine learning technology could help the movie industry create a 15 per cent rise in ticket sales in 2018, according to data analytics and marketing firm Movio.

The company’s Audience Insights tool, which is set to launch next week, will help cinemas to engage with their customers by predicting the most likely audience for each film.

Movio’s tool draws on past audience behavioural data such as ticket purchase frequency, time of day preference and film genre. It supports cinema marketers connect moviegoers with the films most suited to them and then work out how to best incentivise attendance.

Steve Mathwig, from US Cinema chain Marcus Theatres, said: “Audience Insights is a powerful tool that gives us a data driven view of our membership. The propensity modelling that it uses takes the guesswork out of who is most likely to see a particular film. It has become a major part of our campaign development strategy.”

Movio’s Propensity Algorithm allows marketers to determine the likelihood a moviegoer will see a particular movie, on average predicting the 10-15 per cent from that audience who will most likely attend.

Marketers can then focus efforts on creating personalised, relevant communications, matching messaging and incentives.

Movio customers have already seen success from its trials, with one cinema confirming 14 per cent of people who were identified as the ‘likely moviegoers’ made up half of its opening weekend admissions to the Marvel hit, Black Panther.

Will Palmer, chief executive and co-founder of Movio, said: “We have worked with cinema marketers for the past seven years to develop this product. It is a revolutionary step towards not only increasing audience numbers but also building customer loyalty.

“On demand streaming services offer viewers relevant content based on their viewing habits, and cinema marketers are under pressure to do the same. So imagine knowing which movie everyone in your database is likely to watch next and how likely they are to see it – that makes marketing incredibly simple.”

Image: Dmytro Larin