You’ve read our Chief Executive, Will Palmer’s, vision for dynamic content, but how do our data- and technology-heads plan to make it a reality? In this blog post, we take the topic of innovation and dynamic content to the two people behind many of Movio’s technology and data decisions: our VP of Research, Dr Bryan Smith, and Head of Technology, Nicolas Maquet. Read on to discover the big picture, from those behind-the-scenes.

What is Movio doing that is unique in the technology and data space?

Dr Bryan Smith: What makes Movio unique is its complete niche focus on the cinema industry. Most competitive technologies are general purpose solutions which cover broader industries, so the level of detail their data drills into doesn’t come close to Movio. Also most other industries have a similar ‘stock list’ every month, whereas movies are changing every day, so the inventory turnover is constant.

Additionally, Movio gathers information on actual moviegoer behavior – not just who they are. We go beyond demographics and, in the future, will be looking at the ‘why’ as well. Audience Insights was our first big move in that direction, as it gathers information about not only who moviegoers are, but what they’ve done in the past. Our algorithms learn about movies and concessions, and infers the relationships between the different items and habits of people buying multiple things. It then finds patterns and makes predictions.

Nicolas Maquet: One of our unique challenges, is that we need to be able to make recommendations for new films, for which there is no available moviegoer data. Similar to Airbnb trying to recommend a new listing that doesn’t have any visitor data or reviews, we are predicting audiences for movies that haven’t come out yet. The way we solve this problem is through content modeling; we provide tools within our product to create models of upcoming movies based on comp-titles and assisted by our Audience Similarity Algorithm™. This allows for an easy but really powerful workflow for creating targeted audiences.

How do you keep the technology up to date?

NM: As we’re 100% web-based, we are able to transparently upgrade our systems without disrupting our service to customers. In addition, our engineering team is really passionate about technology so there is a very strong internal drive to continuously improve existing systems. We believe that constantly improving our tech, upskilling our engineers and upgrading our systems are all key to Movio’s success.

How will this technology advance?

DBS: A year from now our offerings will look similar, but will be based on more advanced algorithms in order to make better predictions. We are currently conducting research into expanding our propensity modeling beyond film content to include areas like concession purchases and cinema concepts. Five years from now, the focus will be the amount and types of data collected by exhibitors and expanding the number of ways our customers and partners can connect with moviegoers.

Finally, we will be forming more relationships with film studios, which could help with casting and early production decisions. We are actually already making some headway in this space.

NM: At Movio, we’ve only recently started to upgrade our core technologies to true big data platforms (see our previous blog post on Apache Spark). We’re very excited about this transformation because of the massive uptick in performance that this upgrade is creating – workloads that used to take weeks can now be completed in a couple of hours, and workloads that were previously unfeasible are now within our reach.

How does the insights-gathering technology behind Audience Insights and Movie Insights work?

DBS: A collaborative filter determines which pieces of content people will be most interested in, based on their viewing and transactional histories. In our Movio Cinema console, we use the historical behavior of all of an exhibitor's members to inform the collaborative filter, while Movio Media takes advantage of all of the moviegoer data across all of our set of media exhibitors.

We use the various interactions and similarities between people and content to determine a propensity score, which is our estimation of how much a particular person will be interested in a particular movie. You can understand it better by reading our Audience Insights launch blog post.

How do you see technology and data science advancing with dynamic content?

NM: There are a number of possibilities for where dynamic content could be taken. One would be customizing kiosk interactions. For example: you're at the POS terminal with an automated kiosk, and a list of movies appears. You see the session times, and are prompted to choose a movie. The order in which the movies are presented could be determined by your propensity, which might have a big effect on your behavior. That's one interaction point.

Another interaction point could be on an exhibitor’s website. If you browse the website and you're logged into it as a member, the information could be displayed differently to you, based on your propensity to do certain things.

It just goes on and on. Right now, we're focusing on email because it's one of our core selling propositions. But there’s no telling what we can do in the future to deeply personalize those customer journeys.

Finally, from a technology perspective, what do you want Movio to be known for?

DBS: I’d like Movio to be known as the data authority in the film industry and a provider of reliable, novel, and actionable insights into moviegoer behaviour.

NM: The quality of our engineers – their motivation, ability and willingness to continuously innovate.

Keep your eyes peeled for more on the upcoming release of our dynamic content innovation. In the meantime, check out everything Movio Cinema here.