Day#226: Netflix Site Review

Day#226: Netflix Site Review

I recently got Netflix and it has been an awesome experience here is a break down of my opinions and experiences thus far, I have decided to review the site in relation to the Gestalt Principles. You can check out a post I did specifically on Gestalt Principles here  as well my review of a course I did on Gestalt here.

Reciprocity

The platform utilizes reciprocity, to an extent you have to put in your details for a one month free trial, however you can opt out of the trial and not have to pay for the initial first month. The initial first month is enough to get anyone hooked on the service and have it form apart of their routine.

Viewing selections

The site immediately after creating your account allows you to choose material that you enjoy, instead of simply choosing a genre, the viewer is met with an an assortment of movie poster images of all sorts of genres and once you choose, it affects the suggested content you receive. Buttons are grouped together using Gestalt theory principles on proximity, basically this refers to having buttons grouped together which then help you make all your choices and changes etc from one centralized location.

Law of similarity

This is also utilized where you have similar content grouped together under categories, this then helps if you would like to see what Netflix is identifying as top picks for you or look at trending content. I must mention though that Netflix has a match rating that they display in contrasting colours on each show, this “Match Rating” is supposed give you the viewer a hint from Netflix if you will like or dislike the show. What is interesting is you tend to not identify it as trustworthy at first, because basically everything on my suggested list has a 97% rating. However after a bit of digging and finding movies that I would really not watch, I noticed the ratings do change and I found ratings as low as 47% for a Match for me specifically. It seems that Netflix only shows you what you would like, however for the benefit of having the Match percentage valued, it may be better to make some changes perhaps, given how I viewed it may be helpful, but it may also be a rare occurrence. Quantitative Usability testing will help with understanding this..

Figure/Ground

This was one of the earlier Gestalt principles and this is clearly defined by the commonly known face and vase image, where you can see faces in the image, and if you re look at it you can see vases. The concept is utilized in the Netflix platform where there is a huge video landing page in the background which advertises featured content. Then in the front you see the viewing suggestions that Netflix has pre-selected for you based on your interests.

General activity

Something that I also wanted to mention was how when you watch a show you can skip the title sequence, and you can skip the end credits and go straight to the next episode. Yes that is probably increasing the chance of binge watching but I love the idea, it creates an easy interface and I feel well taken care of by the platform.


Finally to end of I obviously have to mention how cheap Netflix is, at a fraction of the cost of DSTV, we actually got it because we wanted to do the interactive Black Mirror episode (check out my review of the episode here) and then the platform really grew on us, and we will be staying with Netflix and paying the monthly cost. By them having products like this, that can only be used on their platform, it is really giving them an edge. After chatting to other people it seems like DSTV still has loyal customers, because of their sports channels. However I am interested to see how that changes in the future.. and if it does. I really also look forward to seeing Netflix improve their understanding of what viewers like more, for example I tend to have a very different type of taste on a Saturday morning when I am working and watching something in the background, verses when I want to sit down and watch a movie on a Friday night. Anyway bye for now and happy researching until next time Uxers

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