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Boost your users’ experience with data-driven decision making

The user experience is one of the elements that receives the most attention – and thus causes the most concern – for any business that is customer-focused or depends on product sales. Significant factors depend on it: factors such as the likelihood of repeat interest in a product or service; a user’s willingness to pay; user opinions that are shared with others; and the overall user experience requirements. One of the most innovative ways to improve the user experience is by making decisions powered by data. Video streaming services are no exception: How you use the massive amount of data your video service generates each day could be the defining factor when it comes to deploying a successful user experience.

Focus the user experience on the simple and intuitive discovery of the content that is most interesting per user

A good user experience for a video service mainly requires an easy-to-use, attractive-looking service for the end user. The customer’s primary need is to discover and consume content as efficiently as possible. He or she should be able to do so as quickly and easily as possible.But to achieve this, you have to identify: what it is that customers want to consume at any given moment (which movies, series, or channels would be the most interesting); where they want to consume it (on their smartphones, smart TVs, or computers); and, when (in the morning, afternoon, or at night). All of this is much easier to achieve if you can exploit your data.

Some issues arise in the heat of the moment, when users are trying to consume video service content; others can be defined according to standard use cases applicable to a majority of users. Even so, many trends can be identified from a video service’s customer data: trends or patterns that occur in concrete circumstances or with a specific type of customer. Basing user experience decisions on the information that this data provides could significantly improve the overall experience and preempt the most common problems.

User navigation and interaction using your video service’s multi-device applications

A key element of any video service user experience are the multi-device applications that allow users to consume content. If we base the design of these applications on data, the apps could wind up being a fundamental tool for the delivery of a compelling user experience. The question is how to design them accordingly. It is indisputable that applications facilitate the customer process, but it is critical to determine the factors that distinguish a truly successful, one-of-a-kind video application from the others. What delivers the leading-edge accessibility and functionality that sets a video service apart from the others?

Clearly video apps in general share certain features (carousels, trending or most popular content tags, etc.). These features represent the essential, minimum requirements and are relatively obvious for video services. Still, there are hidden trends in user behavior and in the user experience that are fundamental to the success of an app. Making smart use of data is the key to identifying these trends and putting them to use to improve functionality, helping to differentiate your service from the competition.

Choosing the right brand ambassador(s) for your video service

Brand ambassadors, and even more especially “influencers” can play an important role in the first customer touch point with any product, in the user’s perception of the brand, and in the experience he or she might expect. The full benefit is achieved when the ensuing customer experience lives up to expectations and makes the impact the company so desires. It is important to find the appropriate person to fully and accurately transmit the product’s potential to possible customers.

Even if this practice is currently not very prevalent within the streaming industry, it will certainly not be long before we see more innovative marketing strategies – such as how to use influencers to recommend our video service or even review and comment on our content – crop up in our industry as they have successfully in other mass consumer services.

Using data and big data technologies will help you decide which influencer can best showcase the benefits of your video service and the value of your user experience to different customer types. Trends specific to the interaction between brand ambassadors and potential or existing customers will be revealed, trends that are positive for the user and/or customer experience. There are people who are better positioned or naturally able to communicate to a specific target audience to get the most out of a product.

Personalization is undoubtedly the area of greatest opportunity for the improvement of the video service experience

Personalization is one of the key areas where businesses can use data to make informed decisions, thus improving the user experience of its video service. Making your users feel unique and special, personalizing your services to offer them the series, movies, and/or linear channels that are of most interest to them, adapting the user interface to their specific interests – interfaces for all types of customers, ranging from kids to sports fans to addicts of particular genres – improving the overall customer experience. This can be done with big data technology and the collection of viewer data.

Personalization is a key element, and data helps us learn about our target audience(s) so that we can be as accurate as possible in our personalization. We can then adjust our content, messages, and even prices, depending on the profile of the viewer on the other side of the screen. All of this is closely related to analysis: there are hidden patterns that big data can extract, and help you put to use, adapting, if necessary, key processes such as addressable advertising, ultra-segmentation of the audience, the user interface, prices, etc. Data analysis can thus contribute to the design, functional logic, and development of multi-device applications, helping to meet the demands of video service users and their unique behavioral models.

All of this allows us to deliver automated flexibility – dependent on the needs and desires of each user and at any given time – in our service processes, and therefore in our interactions with the users, as per previously analyzed data. All this obviously improves viewer engagement, and in turn, our video service ROI.

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