To what extent have consumers embraced voice search as a tool for content discovery and what more needs to be done to encourage its use?
Over the past year, we have seen voice really starting to take off with consumers. In our own research(1), we’ve seen access to voice-based search rise to over 24 percent, with over 70 percent of people saying they find it easy to find the content they are looking for. We’ve also seen that the users of truly “conversational” products, like the TiVo Bolt Vox, which have more advanced ‘Natural Language Understanding’ (NLU), and can handle multi-faceted queries – such as “show me all the Bill Murray comedies from the 80’s with a four-star rating” – have a 21 percent higher weekly usage than other more basic services. Key to encouraging usage is how the services are being advertised to consumers through our operator partners. Where operators have embraced voice in their advertising – as Sky has done with Sky Q – we see strong and maintained growth, as consumers realise the added simplicity it brings to their lives on a daily basis. Voice interaction is entering the mainstream as tech giants like Google, Amazon and Apple heavily promote voice-based features and drive consumer adoption. Done right, voice not only helps users get to their content faster, but also enables operators to expose users to a much greater breadth of content. The ideal offering for operators is one that combines a deeply media-focused vertical content solution with the broader voice ecosystems of Google, Alexa, Siri, etc.
How far are TV operators embracing unmanaged IP devices and apps to distribute their service offerings to subscribers? What are the advantages and what remaining concerns do they have?
We see many operators looking to take advantage of devices that consumers have purchased to consume entertainment, as it can help to lower their capital expenditure costs and deliver a service that consumers are coming to expect – namely their subscription services being available where they choose to watch them. The ‘TV Everywhere’ revolution was the pre-cursor to this, where operators provided service to subscribers via an app on their mobile phone or through the web, but we’re now seeing this evolve to the point where we have operators – like BT in the UK – combining their own content along with the UK public broadcasters, Netflix, Amazon Prime and Sky’s Now TV, into one experience. Only a few years ago, those services would have been seen as too competitive to the operator to contemplate providing them to their customer. This type of content integration is a key cornerstone of the TiVo Experience 4 product, allowing consumer access to content from many sources in one interface. In a market that is increasingly fragmented, there is a window for providers to serve as the starting point for consumers’ entertainment experience, and guide them through the maze of content options.
What impact is adoption of Android TV as an operator platform having on the market and what are the advantages and disadvantages to service providers of using this technology?
Android TV used to be a major concern for the pay TV community, as questions around the experience, security and control featured high on the agenda. Google has listened to operators, and with the latest Android TV Operator Tier has ensured that these concerns are addressed. This is great, as it allows operators to choose to use a class-leading customer interface like TiVo Experience 4 and still take advantage of everything that is offered by close integration with the Google Play store.
How can machine learning enhance content discovery and how transformative is the use of this technology likely to be?
Machine learning is bringing rapid change to the realm of content discovery in a number of ways. Most importantly it is helping to make sense of the vast unstructured data sources that are available on the internet, finding information that is relevant, and helping enhance the structured data that is supplied by companies like TiVo. These content sources and formats are constantly evolving, so you can’t simply just write a set of rules to process them. The system itself must take advantage of the latest Artificial Intelligence (AI) to adapt itself and continue to surface the most relevant information in real-time, at the right moment, without slowing down. With the industry fragmenting so quickly, and consumers being faced with more compelling content and ways to discover that content, machine learning will offer the speed and accuracy that is needed to keep up with consumers’ needs and desires.
What are the most compelling applications for the use of machine learning technology currently being investigated?
One of the most interesting areas is how technology can be used to enhance the work of human experts. From helping find the most appropriate content aficionados to curate an ever more specific set of content options – for example, your catalogue of Spanish horror films that need a true fan to review. Machine learning can also help to bring scale at speed to the world of metadata, by comparing inputs from both machines and human editors for consistency and accuracy. It can also help to surface meaningful results and recommendations that enable contextually relevant discovery by assessing current events and connecting and presenting timely entertainment content to the customer.
(1) TiVo Q4 2017 Online Video and Pay-TV Trends Report
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12-14 June 2018
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