The basic goal is for consumers of video services to be highly engaged. It is easy to say but hard to do. Yet it is at the core of being a D2C streamer.

D2C requires a deep understanding of the end customer’s satisfaction.  But rather than this understanding relating only to the content itself, at which Broadcasters have excelled for many decades, a D2C streaming service requires an understanding of satisfaction with the service – the quality of it, the ease of use, the style of use – which requires the right technology and a focused information-gathering approach. What should be done to achieve this all-important outcome?

Solving For Churn

Let’s start with a basic business challenge of any D2C video business – churn. Whether a pay-TV operator loses a subscriber, or an advertising supported operator loses ratings, churn impacts revenue.

In practice, there are two types of churn: voluntary, which is attributed to an intentional decision to stop using the service (studies show this represents about 75% of the total), and involuntary, which is attributed to unintentional events like credit cards expiring that can no longer be billed. This article focuses on voluntary churn.

In OTT, cancelling a service is easy compared to the traditional cable or telco TV package that is often tied to a 1-year or longer contract that generally includes broadband and TV. OTT services normally have a 1-month or similar cancellation period. In addition, research shows that approximately two-thirds of people will cancel their OTT subscription when they finish watching the series they signed up to watch.

D2C services in general also offer a lot of choice to the customer, which is increasing competition for eyeballs and wallet-share. The average US household now has seven regularly used OTT services, up from two just a few years ago (Netflix, HBOMax), then four (Netflix, HBOMax, Prime, Hulu) more recently.

Preventing churn is indeed a big challenge. Enter “engagement”.

Churn Prevention Through Engagement

To prevent churn D2C streamers need to engage their customers quickly and keep them engaged.

Engagement is often measured in terms of “time spent watching”. For example, four hours is better than two hours, and four times per week is better than two times per week.

But a deeper measurement is required, which must aim to understand customer behavior as they “shop for entertainment” in the OTT App. The measure should incorporate time spent, clicks, search activity, browse activity, favorites selected and more, which is what online retailers do. For retailers, what matters is not only what the customer purchased, but also what else they did while they were in the store, especially if they browsed and did not buy. If a retailer can know this, they know how to more effectively engage customers to earn a bigger share of customer spend. D2C streamers need to understand their customers in the same way, because maximizing engagement will maximize the lifetime value of the customer to their business.

One of the techniques used to engage customers is to enquire about their interests. Psychologically, not only do we have fairly consistent interests which we are generally drawn to, but when we are asked what we are interested in we receive affirmation of interest in us. Services are therefore evolving to ask general questions about our interests and preferences when we first set up a service. This “first-time user experience” was originally introduced following research that correlated high levels of churn with an impersonal first-time experience, or “cold start”. Customer field-testing run by TiVo with optimizing the first-time user experience on consumer devices showed a 30% reduction in 15-day churn. Personalization really makes a financial difference.

After this first-time experience, the work continues. D2C streamers must stay focused on how their customers are interacting with the OTT service. The User Interface (UI) and back-end systems (e.g., content library / CMS) should be instrumented to capture key engagement signals and use them. It is not enough for a D2C streamer to simply publish content and run basic search queries like “most watched shows” because the customer is doing a lot more than just watching programs. From a technology perspective, this is big data analysis using powerful algorithms and machine learning driven analysis. For best results, “eventing granularity” – i.e., the level of detail captured about individual events, such as a customer search – should be defined to an appropriately low level so it can reveal previously unseen behaviors. To manage this proliferation of data requires the use of graph database technologies to associate datasets in ever more meaningful ways. Compute and storage resource must therefore be sufficient and scalable to gather and analyze data even for the largest concurrent audiences.

As an industry comparison, the pure-play D2C streamers generally have an easier time of crunching the data compared to traditional pay-TV operators. The traditional operators often have large cloud DVR platforms that hold a lot of content, which requires managing a larger amount of customer interactions (e.g., record and delete actions). This increases the data sets held by back-end systems, which simply increases system resources required. Traditional operators often have on-prem fixed capacity platforms which have been expanded over the years. Running large data-sets with scalable ML algorithms to provide insights as quickly as possible requires elastic technical capacity.

QoE (Quality of Experience) And UX (User Experience)

These two terms dominate the subject of customer engagement. They are numerical measures of customer satisfaction, and the D2C streamer will have clear targets to achieve. QoE measures the technical quality of video delivery to the customer, in measures that directly reflect the customer’s experience. UX measures the customer’s experience of interacting with the whole OTT service.

QoE is a “hygiene factor” for customer engagement. This term, coined by clinical psychologist Frederick Herzberg, is widely used by customer experience practitioners. Applied to OTT consumers it means that if QoE is at the targeted level, customers will be neither highly satisfied nor dissatisfied. But if it is below the targeted level, customers will certainly be dissatisfied. In other words, we cannot impress the customer with QoE, but we can certainly upset them.

UX on the other hand, while it can cause dissatisfaction it can also be a source of real satisfaction, in other words a “delighter”. A slow UI could cause dissatisfaction, but a simple and clean interface that feels enjoyable to interact with could impress and deeply satisfy. For D2C streamers, Netflix has set the bar so far. As content libraries continue to grow, and people feel time is short, this area will become even more important.

It’s worth noting that delighters ultimately become hygiene factors as we get used to the new normal, so standards must continually be raised. The pursuit of customer engagement excellence is how this will happen.

Historically, engagement analysis has been mostly about the UI’s ease of use and the customer’s content choices, not the streaming QoE itself. This is because cable and telco pay-TV platforms, where engagement has been most researched due to their time in the market and the direct commercial ramifications of failure, generally do not have QoE issues. This is because they operate on stable, closed and managed networks with delivery to managed set-top-boxes. IP delivery to any device type over unmanaged networks – i.e., OTT – is still relatively new and still a small percentage of total consumption. But clearly things are changing fast. QoE is a known challenge for the leading D2C streamers and achieving target levels of QoE is mission critical. And when achieved, results can be impressive. Research shows that not only do customers not churn as easily, but they also consume more content due to the better experience. Quality pays off.

Looking to the future, customer engagement analysis will focus on measuring customer emotion and the proclivity to engage in the content. This will provide richer and more accurate information than abstracted measures of clicks, hovers and likes. The desire from technology leaders in this area is to read body language and facial expressions to understand the customer more deeply. While this would be ideal from a research perspective, and technically it is possible through the use of cameras in the consumer devices, the inherent privacy concerns may take some time to overcome.

The Engagement Objective

Customer engagement is a top-line objective of any OTT service. Combine excellent engagement results with great content and you have the basis to be a winner in the D2C streaming business.

D2C streamers are progressively applying the disciplines mentioned in this article to push the boundaries of data gathering to become customer experience masters. To honor customers’ privacy and maintain trust, the best practice is to keep the technical solutions used to understand engagement separate from personal information databases. This separation can continue to work well because the goal of customer engagement analysis is to simply understand what you engage with the most and then accentuate that. The process does not need to know your age or gender. As engagement disciplines seek to forge new levels of understanding, the privacy/trust line will be an important boundary to maintain.

Avoiding churn through satisfying customers is critical to D2C streamers. A joint focus on QoE and UX to understand customer engagement will help avoid churn and be the basis of streaming superstars of the future.