Why Reviews are Garbage – Part 2 of N
I am back and I figured I would begin by focusing on an old series I had not updated in awhile: Why Reviews are Garbage – Part 1 of N. Since I initially began the process of outlining how this topic (Reviews being Garbage), I had a good friend visit me to do a writers workshop. During that visit, we took the time to “spiritually” debate some topics. Now, if you haven’t figured it out yet, I debate like an asshole. Since I had begun the preparation for this series before he had arrived, but we somehow got to the topic of reviews, and I began utilizing my research as part of our discussion. The reason I am beginning with this little story is to show that these arguments have been tested in a whimsical three hour debate. One of the first pieces we discussed was the concept of a corporation buying reviews. [Click “Read More” for 1800 words of critical analysis]
Read MoreWhy Reviews are Garbage – Part 1 of N
One of my favorite things about the internet, is how often people buy things based on the reviews. “Five thousand people have reviewed it and it is four stars! I am going to buy it.” Here is the thing, those reviews are bullshit. Even if some aren’t fake, they are not a good measure for a product. Reviews are a strategy to tell you that a thing is great! Except, is it? When was the last time you saw something with a thousand reviews and a 1 star rating? You won’t, cause the second the first set of ratings appear, they will be five to four stars. The reason is simple, anything that has 1 star will never be purchased. So manufacturers are compelled to buy their own product and rate it high to initiate a purchasing spree.
Now, it is important to note that there are many reasons that reviews are garbage. I plan to break down a lot of those over a multipart series. While reviews do help us choose a product, it isn’t necessary. In my mind, the reviews help you with satisfaction of a product. They let you be confident in a purchase; however, the ten major products on the webpage that all have similar reviews are all going to work just fine. That’s the trick, reviews don’t help you find a super amazing product, they help you be satisfied with the one product you ended up choosing.
Over the next couple of posts, I will go over why reviews are useless (except for customer satisfaction):
- Reviews are bought (maybe not directly, but just giving a person a product to review will drive certain behaviors)
- Updating reviews allow companies to respond to defective stock easier (if the product breaks, they replace it, you move review up based on how you are handled)
- Products are purchased in higher volumes if they are advertised by the manufacturer (Game of probability – more purchased, the better the reviews will go)
- People buy products based on their price point (aka, reviews are subjective – what is 4 stars for you is not the same as what is 4 stars for someone else)
- How many people buy multiple large items (no one buys 10 vacuums and then reviews them – they buy one, it works well, it gets 5 stars)
- New products will feel superior to old products (what we were using, are being replaced for a reason)
- ??? who knows, by the time I hit number six, I will probably have some ideas to hammer on
So, after I break down all the points above, I will hopefully have explained why reviews are useless. Even if I do that, I doubt it will matter. The reason is simple, humanity needs order to survive. That means, when faced with thousands of options, we need to be prepared to make an appropriate selection. In order to do that, we need to choose some criteria to narrow the options down. In the past, it was going into a store and touching the tangible object until we found defects or benefits that made one standout more than the rest. Instead, we now rely on other people’s tangible experiences with products to guide us to a selection. Which is silly, I am trusting someone I don’t know to make a recommendation to me. And it is insane that I accept that recommendation over my own mother. Yet, we all do it, we trust strangers on the internet to help us buy commodities instead of going and touching the real thing in person. So, if I can get one person to take back control, I will count this project a success.
Read MoreLet’s Gamble – Netflix
Let’s talk AI development based on something everyone has experienced – Skip Intro. You’ve seen it on Netflix when you are watching a show. That simple button jumps you two minutes into the future and gets you through the snappy intro with ease. Then there is the auto play functionality that knows you are at the end of a TV show and automatically begins the next episode in fifteen seconds. We have all been sucked into a binge on Netflix by that 15 second countdown. Yet, how do they create these features that streamline your TV viewing experience?
Now, many people would assume that Netflix has created an AI system that can watch TV shows and apply flags to the datafile. These flags would be used by the program to enable certain features: skip intros/autoplay the next episode. This assumption would be because of marketing departments. In every major corporation, there is a marketing department that is talking about their AI programs or machine learning programs and how they are moving forward. Except, creating an AI or machine learning programs is difficult and very expensive.
When I say very expensive, I mean like ungodly expensive. If you look at Google’s AI department, there are like thirty engineers working fulltime in Palo Alto. Not only that, if you are on the AI program, you have to be over compensated so you don’t jump ship and take IP with you to another company. That means, the company has (more than likely) hundreds of engineers working on creating a singular program that will do important tasks. While these departments exist, they aren’t being applied to the technology you see.
A great example was a lawsuit that was levied against Microsoft. Former employees for Bing Search were suing because they had to stare at horrible pictures and flag them. Why didn’t Microsoft just create an AI system that flagged inappropriate pictures automatically and keep humans out of the picture? Simple, an engineer is going to cost hundreds of thousands of dollars, a human that goes through pictures and flags them will cost thirty thousand dollars. In order to flag a picture, you just need to have eyes and basic comprehension of what is inappropriate. It was a business decision and it was cheaper to hire someone to flag something than to build an AI system.
So, how do major technology companies create little features we love? Simple, they probably pay employees some money to grind through a basic task instead of developing software to do it. The skip intro is a great example. I can think of a few ways it can be done:
- Someone at Netflix watches every show, flags the beginning of the intro in the file, then flags when the intro ends. That tells the program where to skip to.
- When people watch the show, they fast forward the video to the end of the intro manually. This tells you the beginning of the intro and the end of the intro, but you are going to have to make assumptions based on the user input that tells you they actually fast forwarded an intro.
- You are using crowd sourced data and assumptions to deduce the intro time length for that series.
- The first people have to provide that input, means the feature doesn’t become available till later. Also different people will do it at different times.
- Person/Software solution. This is you take either 1 or 2 above and then apply a software solution. All video files are data, as such, at a certain point in time there is a unique set of data for that specific video. So a person goes to the first episode with a intro, flags the beginning of the intro (provides you reproducible piece of data for all intros) and then the end of the intro (another unique piece of data). Since the introduction is always the same (cut from the same file), you can always find the introductions beginning and end.
- Once you have flagged these unique pieces of data, you just have software go through and add the flags to all the files.
- If the intro changes, you bring the human piece back in and they flag the new intro the same way. Then the software goes through and adds the flags at the appropriate points in the file.
- Software solution. Instead of having a person flag the intro file for the program. You have the software program look through all the files for a season and isolate out the repeated pieces of data. That means, your intro would be the same piece of data in each episode. Once you see there is a pattern of data, you isolate that and add the flags at the beginning of the sequence and the end of the sequence so a user can skip the intro. This would work for the credits also as they would appear as a sequence.
- Problem with this is there could be hidden videos at the end of the episode – you would lose this added value to the episode if you automated the skipping of the video.
- It would cost a good amount to get to this point instead of crowd sourcing or hiring a cheap resource to look through the videos and apply the flags.
Option three allows you to save a ton of money on software development and avoid pitfalls of automation (when something doesn’t follow the same form as originally assumed when the software was coded). As such, you wouldn’t have to do additional development as things change or shift. This would require an ongoing cost of a human being, but depending on the amount of work needed to code the automated solution, it could end up being the cheaper option for the next ten years.
Then again, I could be completely wrong and Skynet is running all the major corporations in the world or we are in a simulation.
Read MoreTo Succeed, You Must
One of the most frustrating things for me is to be talking with a partner in a project (creative or non-creative) and be told that we should do something one way because that’s what everyone else is doing or because the market dictates that we have to solve a specific need. Specifically, I have been working on a podcast (severe back burner) for two years (Record Store 2016 Baby!!!!!) and everyone tells me the same thing when it comes to monetizing the thing: “How are you going to get advertisers,” then they ask, “Who is going to listen to it”? One, I don’t do it for money so I don’t care about monetization(I will try to get paid for the effort I put in, but I do it because I enjoy doing it). Two, I don’t care who is going to listen to it because it is a project where I get to work with my friends and talk in a structure form; the final outcome, I have their voices preserved for all history and our crazy ideas. I have a personal snapshot of our minds at a specific age – a portal back into the past.
Back to monitization for a moment, all podcasts use the same model for income: advertising (everything in the universe uses this except subscription services); yet, industries do the same thing (if Business A makes money doing Thing Z in way ZYX, then Business B will do their Thing X in way ZYX since it is safe and already proven to be successful). This copycat mentality plagues all walks of life. In order to get a book deal, you need an agent, to get an agent you need to prepare a query letter and provide certain materials based on the agent’s requirements (all utilize query letters) – this is an industry standard.
Now, the book example isn’t a problem cause it allows the writers of the world to easily move from agent to agent without killing themselves over writing a query (except each query gets rewritten, at least, that’s what I do – gotta personalize that shit). The root of my problem is the sale of a product. When the smart phone introduced feature X, most phones had feature X shortly afterwords. Android looks painfully similar to iOS and vice versa. Windows phone was unique in how it handled navigation and use (I have one, it is easy to use and is from six years ago and still doing the things I need it to do), yet, the Windows Phone OS is now dead. Did it fail because the phone didn’t make calls? Was it cause they were late to the party? Or was it because it was too different? No one will know. In the end, we end up with X options in the world and all look the exact same with minor tweaks.
What I do know is that you have to be careful of using market research to design a product. Unfortunately, the market only knows what exists in the market today. So if you go to a bunch of people and ask them what they want to see in product X, they will respond with 1,2,3,4,5,6,7 but what you miss is that they can only count to 10. While your creatives/engineers are thinking all the way to two hundred thirty six. You should poll the market, but you should pitch them ideas they haven’t comprehended so that you solve a need they didn’t know they had.
This concept works for all creative pursuits. The moment you start bending to the market and trying to satisfy their existing needs, you are behind the curve. Everyone else in the world is able to read the same market as you, which means, you are competing against thousands of other products that are about to come out. That’s the danger with building products off of the market’s desires. So, my argument is simple, stop listening to the market and try to solve a need you have personally. Throw your passion into it and keep revising it until you hit something people want. Just don’t go to the market and say: “What can I build for you?” The moment you do that, you are doing the same thing as N people. So differentiate your product by truly creating something unique that you are passionate about.
Read MoreIt’s All Natural – Arsenic
If you have stuck around this long, you obviously know my feelings towards business and marketing terms. So, if you are surprised here – that’s on you. There are laws in place to protect a consumer from being taken advantage by false advertising. But there are various ways to avoid breeching those laws… like creating a product called: “REAL CHEESE!”. Now if you are super sneaky, you can call the new product (created from pure chemicals and formulated in a lab) “NATURAL REAL CHEESE!”. As a product, and having it trademarked, you can do whatever you want with the term. Derived from soy beans and decomposing plant farts, doesn’t matter, the product is still “NATURAL REAL CHEESE!” and it can be sold as vegan! Imagine that, a cheese product that is vegan. Then there is the vegetarian option: “NATURAL REAL CHEESE!!” that is made from human farts, soy beans, and goat urine – yummmmmy!
My point is quite simple, though I meandered from my original topic, and that is anything can be called natural. In the above case, I can use law to generate an appealing product by naming it one thing even if it is creating from human shit. By creating a legal name for the product, I force you to only look at the surface level and see: real cheese. Not only that, I throw in natural to make you think that it was derived from a natural process like fermentation. This isn’t the case, the process is manufacturing, but the ingredients are natural.
However, the clear issue is the concept of natural. Everything is natural. But I can promise you would have certain feelings to the difference between a strawberry from the side of a mountain versus one grown in a test tube – yet both are natural (since atoms/elements/quarks are all natural).
Read MoreHow Hate Dies – Maybe
I don’t know if capitalism will destroy hate, but I can hope that a weird dynamic that has sprung up within our version of capitalism that will force hate to die out – revenue. In previous posts I’ve railed against the new structure of using advertisements to build revenue for most technology companies. I hate these advertisements because I don’t think I should be subjected to a 15 second advertisement when I want to watch a 2 minute video… however, I am beginning to see an interesting twist. This culture has given the power for choosing web content to the companies that need to advertise – not the consumer (think, who pays the bills, that’s who chooses). But more on that, let’s focus on some assumptions I’ve made in the past. [click “Read More” to dive into the twisted world of revenue]
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