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Maximizing ROI via Viewer Personalization

TV personalizationAre we in control of our decisions? Although we all presume that we make rational decisions, essentially we are much less in control of this process than we know. 

According to Wood and Neal, about 80% of our everyday decisions are made with minimal cognitive processing, or without conscious thought altogether.

In the digital space, where we are continuously fed information, the problem is exacerbated. Personalized suggestions and recommendations assist in reducing the perception of information overload,  ideally by simply presenting information that you were already looking for. Therefore, the number of items that require sifting through to arrive at a choice is dramatically reduced, leading to a sense of greater control.  When implemented correctly, personalization can have a direct and positive impact on profitability. If the requisite work is undertaken, consumers can be enticed into purchasing decisions with a far greater ROI.

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Key to achieving successful personalization is sense of trust on the part of the consumer. If the messages vis-a-vis the products and/or services are perceived as having integrity and are ‘enjoyable’ this will translate into a far higher retention rate, satisfaction rate, and engagement rate.

At VO’s recent TV Leaders Summit, Liraz Margalit, PhD, Web Psychologist at Clicktale, challenged TV businesses to look at their assumptions about how viewers make decisions, such as which show to watch - and when, and which plans to purchase. She explained that trying to personalize the experience for TV viewers has not been entirely successful, since we continue to look at the data instead of understanding the people behind the data.

What are the sources of data that we using to make the TV experience personalized? We collect data about visitors’ behavior, such as clicks and views, ratings, social events (like and shares), devices, time of day and more. Based on those sources of data, two types of approaches have evolved.

Item-Item Approach

This model finds similarities between item characteristics, so the next movie that is suggested to a specific user will have similar traits to the movies already watched.

User-User Approach

This model bases itself on user’s preferences, so that if certain people order the same movies, then the system will recommend additional movies that the other users also watched.

However, the problem with these approaches is that they are based on the following assumptions:

  • Past behavior predicts future behavior
  • The customer’s mindset is the same in many different situations 

Personalization whats wrong 1

These models lack context and don’t take variations in the user’s mindset into account.

What is required is a new model, based on psychological principles. This model takes different personality types into account. For example, two main categories of users are:

  • Browsers: make decisions from the heart with mainly emotional input
  • Goal-oriented: make their decisions in their head; they know what they want and don’t want any interruptions on the way to getting what they want.

These are not static designations, the same person will make different decisions at different times using one category or the other.

Dr. Margalit and her team have defined a new way of looking at consumer behavior, named Psychology-Based Personalization. This method defines two systems that are used in decision making. One is automatic, usually influenced by emotional considerations. The other is rational and deliberate.

Different parts of the brain conduct decision-making, depending upon the situation. The quick, automatic responses, such as sensing danger, lead us to taking actions without having to think too much about it – such as the ‘flight or fight’ response. In contrast, reasoning and logical decision making occurs in the frontal-cortex, which requires higher-level processing, and this takes time. It also consumes much of the brain’s resources so that a person cannot be involved in anything else when making a serious judgement. When the instinctive system fails, the logical system moves to take over.

How do these factors affect TV viewing habits?

In a recent study, Dr. Margalit looked at a screen with recommended movies, designed to expose viewers to additional content. Users can land on this screen in two different ways from the home screen. The direct way is from the navigation bar; the indirect path occurs after watching a video; a recommendation appears, directing the viewer to the screen with additional content.

The time that the viewers spent on this content screen was noticeably different. Viewers who arrived directly spent very little time on the content screen compared to the viewers who arrived indirectly. This first group was labelled ‘goal-oriented’ as they next clicked  Search or navigational elements. The indirect group, labelled ‘browsers’ spent much more time on the screen, with no specific pattern, clicking a number of elements such as images and catchy headers – in this case the product was leading the interaction. This leisurely experience is pleasing to the ‘browser’ type.

TV businesses must consider how to provide the best experience for both types of viewers. The goal-oriented viewer wants to achieve his/her purpose quickly and efficiently. Alternate suggestions and visuals impede their journey and negatively impact their experience. The browser, on the other hand, is looking for a more laid-back experience and is open to viewing related content. Therefore, it’s critical to provide the correct experience for each type of viewer.

Heart not mind 1

Additional consideration must also be given as to how the information is presented.  Consuming information is dependent upon two main factors – motivation and ability. Even if one is highly motivated to read an in-depth article, but if it’s the end of a long, frustrating day, motivation won’t be enough to tackle the article as too many cognitive resources are required. Consuming information from a video will be easier at this point.

Learn more about VO's leading TV Business Analytics

To obtain the most value from their business strategies, TV businesses need to differentiate between the different types of content that is offered to viewers. If it’s entertainment then it must speak to their emotions with catchy headers and colorful images. Overloading these types of offers with much text and other details brings the rational system into the picture. This, in turn starts a thorough decision-making and comparison process which can delay choosing which content to view or purchase.

Technology must adapt to the way the brain works, and not vice versa.

Einav Levi

Einav Levi is a Senior Product Manager, Personalization Domain. Prior to joining Viaccess-Orca she gained product management experience from several companies including ebay and several startups. She is an expert in big data analysis and product solutions and interacted with global Fortune 500 customers. Previously she led development teams focusing on big data algorithms and rich end user experiences. She holds MBA from Ben-Gurion University and Bs.C. in Computer Science from Tel-Aviv University.