44 ROUND TABLE Audience Analytics
GABRIEL BERGER: If a consumer is viewing on a mobile device then you could recommend a selection of short-form content and stay away from recommending data-intensive 4K content. And if you can see that a consumer is watching while abroad you could recommend relevant content related to the country they are visiting in order to boost user engagement. Location data can also be used to sell targeted ad space to local advertisers that would not be able to afford nationwide TV advertising – for example, a local car dealership wanting to target people within a 20-mile radius. FEED: WHAT ARE SOME OF THE BESTWAYS A CONTENT COMPANY CAN LEVERAGE VIEWER LOCATIONDATA? BHAVESH VAGHELA: Ad-funded TV operators could use location to drive regionally targeted advertising, identifying where a viewer is watching – especially if they are using a mobile device. It can also be used to target people at a specific live event such as a sports match or a concert – where they could push via mobile devices additional content such as interviews with participants or even relevant advertising to boost consumer engagement. Additionally, it could be used by a streaming service provider to let a customer know how they can still watch the service when they enter a new country. ANNA ZAIKINA: Location data can help to create and serve more relevant content, similar to other data points. Understanding the cultural and behavioural undertones of the location a viewer is in should dictate what content is likely to resonate with them the most.
WHAT HAPPENS IN THE FUTURE WHEN CONSUMERS ARE JUGGLING UP TO TEN DIFFERENT OTT SUBSCRIPTIONS?
FEED: HOWCANMACHINE LEARNING BE USED TO COLLECT ANDUSE DATA ABOUT VIEWERS?
GABRIEL BERGER: AI and machine learning algorithms, combined with best practise techniques, let providers analyse data and gain unique insights into viewer behaviour and preferences. This deeper understanding makes it possible to personalise each viewer’s experience with intelligent search and recommendations that attract and deepen subscriber engagement. These insights can also be used to predict churn and open up new revenue streams, for example from targeted advertising. BHAVESH VAGHELA: AI and algorithms are revolutionising the way data is used by media operators of all types. They enable high volumes of data to be analysed to understand and predict behaviour in real time, empowering TV and OTT operators to take action in real time. Ultimately, it’s about determining what a customer is going to do next and what a customer can be persuaded to do that enables them to keep a service for longer, which is becoming increasingly difficult. Algorithms can be created to predict customer behaviour – such as how likely they are to purchase or churn, and determine what the next best action should be – and then feed back learning
to update the SCV and analytical models, generating ongoing insight. Leveraging AI allows TV operators to determine a unique profile for every customer and provide a snapshot of their intent. They can then utilise AI and machine learning to analyse the data, to determine and recommend in real time the ‘next best action’ that will strengthen the customer relationship and benefit the business. This could be to make a timely offer – such as a package upgrade – an informative communication, or to do nothing. The key is to use the technology to segment and target your database, taking the right actions to attract and keep high-value customers. ANNA ZAIKINA: Algorithms are often used to collect and process data in a much faster and often more reliable way than a human being. Examples of AI benefits include standardising multiple data sets and combining them into one, as well as finding anomalies and patterns within them. Additionally, these technologies can assist in serving the right content to the right viewer by instantly obtaining and processing a multitude of user data and content scenarios, in order to choose one that is likely to get the best response.
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