Have you ever seen an episode of Good Morning America or Breakfast Television aired in the afternoon or evening? Why are soap operas so popular in the afternoon? Why are there two different versions of The Office (the original UK version and the US adaptation) and House of Cards (the original UK version and the US adaptation)?
Why Temporal Locality?
Temporal locality is fundamentally a function of common sense. Television companies in particular apply this learning on a daily basis. They understand that people’s minds are at different places throughout the day and this knowledge is reflected in the differences between daytime and nighttime programming. The idea is that what we want to watch in the morning is radically different from what we want to watch at night. Our concerns for the weather in the morning, or curiosity about our traffic routes before we leave the house, differ greatly from our desire to simply be entertained, via comedies, reality tv, and dramas, during primetime each evening.
Our performance, behavior, and emotions fluctuate throughout the day. Many studies have been conducted to determine how people of all demographics, respond and react to different tasks and stimuli throughout the day. Even variables such as intelligence apparently tend to fluctuate. Thus, it’s very possible to use time of day research to choose the type of content delivered at specific times of the day in an opportunity to maximize your content’s message.
For example, according to academic studies, time of day is correlated to variables such as optimism and how people deal with problems. This particular study mentions that people tend to feel overwhelmed in the late afternoon; perhaps this is why, according to iMedia Connection, BuzzFeed’s pageviews peak at 4PM. Readers need something funny to pick them up. Other research has been conducted for time-of-day studies; for example, this Shareaholic study shows that the best time to publish to reach high pageviews is 9AM, and the best time to publish for social shares is 11AM.
Bloggers know it. TV producers have understood it for decades (hence the practise of dayparting). Newspapers have started adapting to temporal locality, with news dailies being distributed during the morning, and entertainment dailies near the end of the day. However, content providers and their mobile apps have not taken advantage of this knowledge yet. The mobile phone is a perfect data collection end point to reach an audience with specific content at a specific time. Furthermore, people are very much aware of their phones at all times of the day – simply walk down the street and ask people for the time and watch how many of these people pull out their phones.
Why Spatial Locality?
Another very interesting piece of data that mobile presents, when users allow, is the knowledge of where they are. Leveraging spatial locality data presents the opportunity to take into consideration the location of the user (or viewer) and figure out how that context changes the way they will interpret or need the app for any company creating content. Foursquare did it well with geo recommendations and Passbook notifications is taking a stab at it is as well. Both these apps provide not-so-subtle recommendations when you enter a targeted area.
Google Now is a fascinating real-world application of spatial locality. The service works quietly in the background, aggregating information about users and sending them relevant updates. For example, if a user’s flight gets delayed, Now will let them know.
Similarly, Google Now goes a step farther; it is anticipatory software. It will update you with things that are just about to happen, right when you need it. You will know which route is most effective when you get inside your car. You will know when the next train is as you step on the platform. This entire customization and enhanced experience happens because of the context that mobile devices are able to provide.
Other devices can’t tell you nearly that much: a TV can’t tell you anything besides time spent. Radio can’t give you any feedback. However, the mobile device’s ability to deliver an accurate read on the spatial and temporal locality variables opens up a world of possibilities. You can cross-reference the information with various other pieces of data in order to better serve your customer.
Despite only being two variables, spatial and temporal locality completely change the way you can determine your user’s needs and priorities at the moment. You can read your users much more accurately, and give them what they want right as – or even before – they realize they need it. Google Now is pushing this along and is seeing success. How can your mobile apps take advantage of these two variables to ultimately provide your customer with a better and more intelligent experience?
