Video service providers are still attempting to come to terms with how to manage and use big data. Identifying and focusing on key areas such as specific elements of marketing, targeted advertising and churn reduction can point the way ahead, writes Anna Tobin.
The amount of data being collected by content operators every day is phenomenal. As Guillaume de Posch, co-CEO of RTL Group, said in his keynote speech at the Let’s Go Connected event in Brussels in June: “State of the art technology and big data are key elements of all successful business models for the digital media world, from Google to Facebook, from Netflix to Amazon. Data is the ‘new oil’.”
The super powers that are Netflix, Google, Apple, Microsoft, Amazon and Facebook know how to mine these vast piles of knowledge and exploit them to their full potential. Nearly everyone else is still trying to figure out how to get the best from their data and some will prove more successful at it than others.
To squeeze every drop of useable information from your operating system you need to pick up data from every conceivable point in your distribution chain, says Mikael Dahlgren, CEO of Agama Technologies. “Video service providers are quickly becoming data-driven. More and more, operator processes are being supported by data and analytics; and, looking to the future, being data-driven will be a critical success factor for most, if not all, areas of operation,” he says. “We are currently working with a lot of operators in this area, helping them to improve their services and better understand their customers. Examples of this range from continuous improvements to their technical infrastructure, to on-boarding of new customers and churn prevention through proactive customer care.”
Learning how to maximise and make the most of the data they collect is key to the long-term survival of both larger and smaller players, but a reluctance to experiment, budget restrictions, skills shortages and regional and pan-regional regulations make what is already a risky business, much trickier.
The business model and original one-way technology of traditional free-to-air broadcasters means that they have to make the biggest leap when it comes to data collection. What little data they started out with on their viewership was based on general audience research figures aggregated by audience measurement companies such as BARB in the UK.
Going forward, free-to-air broadcasters do have three things in their favour, however, points out Bhavesh Vaghela, CEO of Paywizard: “Historically, free-to-air broadcasters haven’t had a direct relationship with their consumers and don’t have direct one-to-one information about them, but what they do have is reach, brand and some degree of loyalty,” he says. “To build on this, you find that a lot of those operators are now trying to find a monetisation angle, whether that be in the pay-per-view environment or through catch-up services. These are areas where they can start building a relationship with their viewers by having them register, so that they can start building their data up over a period of time.”
They might not have been doing anything with it, but dedicated pay TV operators have been collecting a range of data from their customers for years, points out Simon Trudelle, senior director of product marketing at TV technology outfit Nagra. “Pay TV service providers still enjoy privileged access to the big screen TV set and that’s a unique source of data,” he says. “While the personal data that can be collected from an set-top box is potentially less extensive than what silicon giants can capture on personal devices such as PCs, tablets and phones, it is still a very rich, media-based source that has value for TV advertisers and, increasingly, for other media and smart city ecosystem partners.”
Not all content operators, even long-in-the-tooth service providers that have been collecting data for years, make the most of this information, however. The sophistication of content providers varies greatly when it comes to using that data, says Ed Haslam chief marketing officer at Conviva. “Some operators are just letting this data pass through and fall into the ether; others are doing the full collection and they might be saying we don’t know exactly what to do with it today, but we know it’s valuable so we want to hold on to it and use it in the future; and, then there is a third class who are the most sophisticated, who are actually putting in place their own data science teams and their own analytics products that actually processes data to help them to try and understand subscriber trends, predict churn, predict conversion rates and try to create a better marketing programme.”
A marketer’s dream
All of this data is invaluable when it comes to marketing. Increasingly, data is being used to feed content recommendation engines. Taking the lead from e-commerce, these subtly plug offerings to consumers, just as other retailers have been doing online for some time. Viewers are being told that ‘people who watched what you have just watched, also enjoyed this series’, for example.
Operators are increasingly interested in the bigger picture, however, says Haslam at Conviva. “It’s not really about the [individual] consumer so much specifically, as it is about trends and consumption by groups of consumers. It’s all anonymised, but what’s coming back is minutes watched, types of device, geography and time of day. Then there is also all the quality data which covers: what was the quality level of the stream in terms of its bitrate, how long did the content take to start, for example,” he says. “Service providers are being offered the opportunity to process or understand an enormous amount of data as it relates to their service and their audiences who are viewing it. This allows them to say ‘show me certain groupings that are similar in terms of certain geographies or certain device types or certain content types or engagement levels’. From this, they are able to put together cohorts that allow them to do better marketing, with better understanding and predictions of where trends will be going. It’s predictive analytics.”
A whole new company culture is required, however, to see off the old legacy mindset and start exploiting potential data sources. Trudelle at Nagra backs this up with research conducted in the second quarter of 2017 by MTM London for the Nagra-sponsored Pay TV Innovation Forum. He says: “It shows that ‘investments in big data and analytics’ is one of the five most important steps – scoring 30% – pay TV service providers need to take to ensure that they are fit-for-the-future and well-positioned to innovate successfully.”
Pay TV operators need to collect their data at every possible opportunity and, more importantly, use it. Collecting consumer data from viewing habits, including VOD, streaming on the go, linear TV viewing panels and even social-media, allows pay TV platforms to gain insight into what customers are watching, how they are watching it and on what platform, says Jamie West, group director of advanced advertising at Sky UK. “With the increase of available platforms, including Sky Go and Sky Q’s multi-room set-top-boxes, we can now understand even more about how Sky customers are viewing content,” he says.
While start-up services don’t have the brand credibility or maybe the reach of long-standing players, they may have a better relationship with their customers, because they launched with a rapid-uptake pay model and have been collecting specific data from day one. They are also quick to learn from the big, successful companies.
And, if smaller players feel that they can’t do all the data collection and analysis themselves, they could look to partner with other players. Trudelle at Nagra cites the example of one of Nagra’s customers that is hoping to profit from such an opportunity. “StarHub, a Nagra customer based in a small and constrained geographical market, Singapore, announced earlier this year the launch of Hubtricity, a tech centre that offers access to various sources of user and network data it collects, enabling third-party firms to leverage the potential of the data collected to deliver new services, including enriching existing data and using this augmented input to run campaigns on various online properties,” he explains. “This example shows that smaller players need to think smart, focus on the specifics of their local operations and collect usage and network data whenever possible. Through partnerships with tech vendors, it is then possible for them to offer value added services that take advantage of the large Silicon giant platforms, while focusing on delivering value to their subscribers and regional partners.”
When viewers were limited to a handful of channels, operators were focused on giving advertisers what they wanted. Now data allows them to aim to please both advertisers and viewers, amid the huge amount of channel choice now on offer.
“TV advertising remains the most reliable, effective and brand-safe platform for advertisers, it provides robust data and customer data – not just email addresses. It allows us to build extensive advanced advertising solutions, helping brands at every stage of the marketing journey,” explains West at Sky.
“With our market leading Sky AdSmart technology, we can target campaigns for brands of all sizes reaching their target audience without the brand-safety and viewability issues associated with some online advertising. This means that we’re introducing real flexibility to TV advertising, opening it up to businesses of all sizes. Democratising TV, so the most effective ad medium isn’t just the domain of big budgets brands. From local taxi firms to ultra-niche premium brands, we’re allowing brands to anonymously match their own data to Sky’s to build bespoke and targeted campaigns – there is something for all budgets and objectives. With TV advertising, it is not a three-second thumb swipe. We’re saying to agencies and clients, ‘You can trust us. We only charge you if your ad is seen. And, by the way, it’s really brand safe.’”
Not only can data that is collected about viewers be used by content providers to allow advertisers to specifically target those viewers who are most likely to buy their products and services, it can also be used to create programming that viewers want to see which, in turn, feeds the adverting business. Keep this cycle going and profits are guaranteed.
“If we look at the likes of Netflix, consumer data is actually used extensively in every aspect of their business operations, including for content creation,” says Trudelle at Nagra. “It is clear that access to data is also becoming a new currency for content producers and distributors and it is a strong factor motivating content owners to ramp up their direct-to-consumer operations so they get access to consumer data.”
Although consumer demand has always had some impact on content production, this has traditionally been based on a hunch and very general viewing figures, now big data and analytics makes it possible to truly understand consumer behaviours, interests and appetites and feed this back to advertisers.
“We can use our data to improve our commissioning decisions for Sky original productions, as well as harness the rich data to provide brands with a deeper understanding of their audience, smarter cross-platform executions and, ultimately, more engaging and effective advertising campaigns,” says West at Sky. “Combining this data with Sky’s technology allows us to surface new programs for customers and make recommendations on shows they might like. With our new platform, Sky Q, we built personalisation for customers at its core, meaning we can offer the whole household viewing tailored to them, depending on the time of day, what room they are viewing in and what device they are using.”
Churn in check
OTT services such as Netflix and Amazon Prime have revolutionised the way consumers buy their content. Consumers are now less loyal to specific service providers. They may, for example, sign up to a service for the latest season of Game of Thrones, but then end their subscription once they’ve viewed every episode, only to sign up again once more enticing content arrives on the service.
They no longer want to tie themselves into long-term contracts and in most cases they don’t have to. It’s now much easier to change provider, and many viewers see this selective purchase model as saving them money.
“We do a lot of consumer research and what we see is that when people sign up to OTT services, such as Netflix, they are already in the mindset that they are going to spend less money elsewhere as a result,” says Vaghela at Paywizard. “They might cancel their Sky Movies subscription for example, and what we have seen is that around 25% of customers do actually reduce their spend elsewhere.”
On a more positive note, Vaghela has found that this trend can be reversed. “Conversely though, if you treat a customer well enough they will end up spending more,” he says. “So, while you are providing these micro services and giving the customer more flexibility, if you play your cards right and you build a relationship well enough they will end up spending more money with you.”
Niche channels that really understand their customers could fare even better than massive mainstream providers from their data. If a horse-racing channel can provide a steady stream of races that its subscribers want to watch, for example, they could be onto a winning formula.
Content is king, says Haslam at Conviva, but it is not always exclusive and that’s when consumer loyalty starts to wane: “As that content starts to get syndicated, as it starts to be made available for cross-multiple service providers, to differentiate your service you are going to have to have better recommendation engines and better marketing programmes so that people can discover and find what they want to watch, when they want to watch it.”
It’s not just viewing data that operators need to look at, points out Vaghela at Paywizard. “You need to understand your online data too, to understand the journey that your customer is going through. Have you made it as easy as possible for the customer to sign up? What does your sign up process actually look like and how much information are you asking for from the customer?” he says. “Once you’ve signed them up, how good are your recommendations to them and how good is your customer support? Even Netflix has its own contact centre and we did some focus group research, both in the US and the UK, and they were incredibly praised because it is possible to just pick up the phone and contact Netflix and they will help.”
Service providers could also cooperate to keep up with the big internet giants. “They can co-operate and integrate their primary data sets – both the data generated by broadcast, online VOD and the set-top box viewing data collected by TV operators. With that they can replicate the same targeting and measurement capabilities of the big digital players and help sustain TV viewing and advertising revenue,” says Laurence Miall d’Aout, VP, advanced advertising, Liberty Global.
The lessons taken could be surprising. For example, traditionally, operators have been minded to make it difficult for customers to leave their services, because every monthly subscription counts. But Vaghela at Paywizard says the data shows that if you make it very easy for a customer to leave, they are actually more likely to come back. “There is a mindset that says I don’t want my customer to leave, but if you use data correctly, it will tell you that this customer is a serial churner,” he says. “Data gives you the opportunity to think about your customers in those segments, whether you are a large company or a small company and actually small companies can be way more nimble and look at the data and truly understand their customer base. They can be much more tailored and personalised to their customers when compared to a larger organisation.”
Operators may use their data to try to persuade those that are thinking about leaving to stay and increase their spend instead. To grow the business footprint further, data can also be used to expand into new markets and even to get rid of distribution channels that are not economically viable, says Haslam at Conviva. “Global data sets can help geographic expansion. It can help you to understand which new markets to enter and which distribution partners to approach,” he says.
“Then there is that almost hidden cost that a lot of people don’t think about except the people who are actually in the service themselves, the publishers. That is how many platforms should I support? Do I need to support Apple TV, Samsung, iOS devices and android devices? There are some service providers that support 30 or 40 different platforms and that’s incredibly expensive. I think that data in the future can be used to more effectively pick the platforms you want to support and even do this potentially by region. For example you may discover that Android might be much more popular in this particular area and this allows you to split your platform support more effectively.”
Data works. Consumer data needs to be used to improve viewers’ experience, whether that is through buying, producing or commissioning the content they want to watch, showing them the ads that are relevant to them or surfacing shows on their EPG that will entice them to continue watching and, more importantly, subscribing. It’s all about creating a TV viewing experience that someone is keen to pay for, whether that someone is the advertisers, the viewers or a mix of both. For service providers, it’s time to get number crunching.