A major TV network, based in the Asia Pacific region, had successfully acquired several million users to its on-demand offering. However, some significant challenges were beginning to emerge:
- Monthly engagement of the user base was low for many registered users;
- The success of ‘blockbuster’ content was obscuring the need for the platform to better redirect users to other content;
- The majority of users had limited content breadth, backed by generally low awareness of the broad content catalogue
Smash Delta was engaged to lead a coordinated, cross-business-unit program to discover and define behavioural groups within the user base to aid a strategic response - driving content discovery and audience engagement.
In order to better drive audiences, an end-to-end strategic and machine learning capability was built and tested to learn about audience behaviours and respond to their distinct tastes.
The process involved the capture of distinct content interactions to drive behavioural and taste groupings of users. From there, audience taste was was fully explored and uncovered through collaborative analysis of user groups alongside a variety of client teams - including content, marketing and platform. Revealed tastes were tested in-market by quantifying a response to an enhanced marketing approach and audience offering.
With a platform of ‘lab’ and in-market evidence - new strategies were formulated to customise future audience content curation and marketing response. This technical approach was ‘mechanised’ and embedded within the client team - empowering them to continue to evolve the capability as the content and audiences did also.
The client was equipped with a new understanding of distinct audience groups, driven by consistent micro-behaviours and tastes, alongside the strategies and embedded technical capability to drive deeper engagement. In addition, an in-market validation of new audience groups and strategies, provided evidence of value for the new innovative approach.
The new technical approach created as a part of the project was effectively embedded within the client team - with training and skills transfer to support further capability growth. Finally a capability roadmap, to enable the further use and continual development of machine learning audience analytics and strategies, was co-created by the joint project team.