Amid overwhelming choice, the ability to provide a personalised experience can help broadcasters and content owners to differentiate their services. Indeed, as streaming services proliferate, companies should now focus on the customer experience, supported by data that allows them to engage contextually with each customer as a “segment of one”.
A study conducted by PwC in 2020 found that nearly one-third (31%) of respondents to a survey carried out in the United States said easy, personalised content recommendations would be a reason for staying with a streaming service. This trend is only set to continue, especially now that streaming service providers no longer have a captive audience as COVID-19 lockdowns are eased around the world.
“Customers are increasingly calling the shots,” PwC observed. “In fact, we expect customer-centricity to be the theme that drives growth for years to come.”
Amruta Shankar, director of data and analytics at Synamedia, also noted that as the volume of available content increases, “personalisation is especially important because consumers will go elsewhere if they spend too long trying to find something to watch.”
Shankar added: “Getting the content discovery journey right is a key customer retention strategy and, as every marketer knows, it is far less expensive to keep existing customers happy than to onboard new ones.”
Good customer data is key, as well as the technology to extract the right information from it. In a December 2021 blog, Google Cloud noted that media companies now have access to an ever-expanding pool of data from the digitally connected consumer.
“And over the past two years, as content consumption and audience behaviours have shifted in response to the world around us, direct-to-consumer has only accelerated,” the company wrote.
While this presents challenges with the volume, velocity and fragmentation of data, “it’s also an opportunity to better understand how to acquire, engage and retain audiences — and inject agility into their business amidst a competitive landscape,” Google Cloud added.
Bleuenn Le Goffic, VP strategy and business development at Accedo, agreed that personalisation “has the potential to increase engagement and reduce churn”.
Le Goffic added: “It gives consumers quick and easy access to the types of content that has the most appeal to them, especially if it is packaged in a user experience best suited to their preferences. For ad-supported services, personalisation does not only deliver more return on investment for advertisers, but also means that consumers will be more open to the ads they end up seeing.”
Unlocking the value of good data
So how should broadcasters and content owners be thinking about their data, and its value, to capitalise on this opportunity? What tools do they need, and what role will techniques such as artificial intelligence (AI) and machine learning (ML) play?
Gloria Lee, executive account director in Media & Entertainment at Google Cloud, noted in the December blog that AI and ML will be critical to unlocking data’s full potential. “The most valuable data is generated data, typically from machine learning or AI, where you’re seeing new insights in data that give you new opportunities,” she said.
Bart Lozia, CEO of Better Software Group, believes that a strong focus should be placed on using viewership as a metric and precisely setting the objectives, “starting with setting which sources of data you want to cover, developing normalisation strategies, defining the recipient, GDPR compliance — and choosing appropriate tools,” such as Google Analytics, Hotjar, Custom JSON document and MQ with Snowflake or Mongo DB — “even considering a custom solution which would bring additional benefits.”
Geoff Stedman, chief marketing officer at SDVI, also observed that an important element of being able to offer personalised experiences to consumers will be the creation, collection, and accuracy of content metadata.
“The more information that can be accumulated about each piece of content, and the ability to make that information available for search, recommendation engines, and even localisation applications, the more accuracy there will be in matching a consumer’s preferences and delivering personalised content to them,” Stedman said.
He added: “Today, AI/ML tools can be used to enrich content metadata, speeding up the process of adding descriptive information needed for personalisation. Media companies that embrace a strong metadata model will enhance their ability to deliver a superior end-user experience.”
Oliver Botti, SVP of sales and innovation within the Global Media Business Unit at Fincons Group, noted that AI and ML, in combination with interactive TV standards (HbbTV for Europe and ATSC3 for the United States), “are bringing TV personalisation and audience engagement to the next level, moving towards an ‘intelligent content’ era, where data is collected to enrich the user experience and to enable new data-driven business models.”
Maintaining customer engagement
Synamedia’s Shankar said a holistic, universal view is required of all the digital clues viewers leave when they watch video content across a myriad of services and devices.
“With insight about content consumption, device usage, content discovery and operational performance, operators can turn the art of second guessing a viewers’ behaviour or intentions into a science that yields genuine business-boosting results,” she said.
Shankar added: “This needs to be underpinned by a cloud-based modular SaaS approach that gives streaming providers the scalability, flexibility and agility they need to employ personalisation and drive engagement and loyalty, to ultimately impact the bottom line.”
Accedo’s Le Goffic said the key to personalisation lies in truly understanding the behaviour and preferences of different kinds of users. “For this you need good data, but also the ability to analyse insights effectively and ensure that they are actionable.”
“While most OTT video providers harvest huge amounts of data, very few leverage it to the full extent. You need to ensure that your data strategy is aligned with the wider business objectives and this can be challenging as it generally involves multiple stakeholders. For those who get it right, however, the benefits are many,” Le Goffic said.
Lozia from Better Software Group agreed that teams need to be put together carefully and with consideration, “beginning small and gradually developing a reliable and strong base of skillsets and expertise with vital business intelligence-specific roles like head engineer and data science analysts with good knowledge of company processes”.
Le Goffic added that video providers also need to be able to experiment with content and user experience changes, using data to determine what is and is not resonating with a certain audience.
She cited a survey recently commissioned by Accedo, where the vast majority (85%) of industry executives said that they are either likely or very likely to experiment with the user experience in a bid to harvest intelligence on usability and engagement.
“However, only 26.7% said they are always collecting metrics that provide a measure of how features and changes to the product affect usage. Only 23.7% of respondents say that they always let the outcome of experiments and user metrics they run actually impact their product roadmap and feature prioritisation,” she said.
Le Goffic concluded that if data is collected, analysed, and acted upon successfully, video providers will be equipped with vital tools for keeping viewers happy and engaged.