Lightbox is a New Zealand streaming TV service committed to delivering the best viewing experience possible to the local market. Lightbox offers subscribers unlimited access to brand new, globally trending shows, cult classics, New Zealand favourites, and a huge range of kids shows.
The Video on Demand landscape is fast paced and highly competitive. For Lightbox to compete against global content providers it is essential that data is at the core of all their strategic business decisions, to ensure they continue to offer exciting and relevant content.
Through the work we have done with Qrious we are moving towards becoming a truly data-driven business, enabling us to ensure we are providing our subscribers with the best possible viewing experience and stay competitive with global content providers”. Hema Patel, GM Lightbox
Lightbox is a New Zealand-based company with big competition, so ensuring strategic content purchase decisions and remaining customer centric is crucial to their success.
Following an internal review, Lightbox engaged with data specialist Qrious to garner deeper insights into customer viewing behaviour. They wanted to understand what they needed to master to remain competitive for customer viewing time, and furthermore, how to sustain competitiveness.
The specialised data expertise of Qrious allowed not only a fresh perspective on existing data but the ability to consolidate and overlay data from a number of different sources.
Lightbox and Qrious identified the first challenge as one that is faced by many organisations – to consolidate
all data sources across the business into a central data warehouse. Secondly, it was imperative to develop a segmentation that would incorporate the audience’s taste groups based on the type of shows that Lightbox offers and also understand how customers are engaging with the content.
AWS Redshift was implemented as the data storage facility. This provided the opportunity to bring three separate data storage systems into one centralised location.
To understand why some customers became inactive and ceased viewing, Qrious specialists took a less traditional view on churn propensity modelling and mapped what “good” viewer behavior looked like. This then became the benchmark for all subscriber activity. Any behavior variation from this ideal standard was highlighted to be addressed.
Two models were developed the first being a Recency Frequency Monetary (RFM) model to understand how customers are using Lightbox, how they are engaging and how often.
The second being a taste segmentation model which was developed to understand subscriber content preferences. Four taste segments were then developed and provided in a report to categorise the subscribers based on the content they are watching.
The two models can work in combination to give an overall powerful understanding of what customers are watching, when and how.
Housing the data in a centralised store grants access to teams across the organisation, simplifies the reporting process and saves time and resources. Management and finance teams can easily pull data they need in real-time. Analysts are able to carry out investigative work on areas such as customer information, engagement levels and churn analysis.
Self-service monthly updates
Lightbox are now able to run a regular report that investigates engagement levels and how subscribers are watching the content. These self-service reports are used to guide marketing activity. Based on different people’s viewing behaviour they will receive varying and relevant marketing communications.
Customer segmentation profiling is used in conjunction with the RFM model to understand what content different people are watching, informing recommendations to viewers and content