Summary of Derral Eves's The YouTube Formula , livre ebook

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39 pages

English

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Please note: This is a companion version & not the original book.
Sample Book Insights:
#1 In 2002, the start‐up company PayPal had just been acquired by eBay for $1. 5 billion. This created a lot of buzz in Silicon Valley. Three PayPal employees, Jawed Karim, Chad Hurley, and Steven Chen, were some of these idea generators. They soon came up with the idea for the YouTube website, but it was nothing like the website we know today.
#2 The story of YouTube is a great example of how focusing on the problem can lead you to find solutions. The website was initially created as a dating website, but when it was realized that the users were posting videos of themselves and their friends doing funny or embarrassing things, the company switched gears and began supporting video uploads.
#3 The YouTube Formula is a set of steps you can follow to gain success on YouTube. It consists of analyzing what's working and what's not, and making changes accordingly. This is the premise on which the whole book is built.
#4 The YouTube ecosystem is made up of many different parts, and each one affects the whole in some way. The creator, the viewer, the advertiser, the brand, copyright holders, and MCNs all contribute to the YouTube experience.

Sujets

Communication persuasive

Marketing de contenu

Informations

Publié par	Everest Media LLC
Date de parution	27 avril 2022
Nombre de lectures	1
EAN13	9781669392736
Langue	English
Poids de l'ouvrage	1 Mo

Informations légales : prix de location à la page 0,0150€. Cette information est donnée uniquement à titre indicatif conformément à la législation en vigueur.

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Insights on Derral Eves's The Youtube Formula
Contents Insights from Chapter 1 Insights from Chapter 2 Insights from Chapter 3
Insights from Chapter 1

#1

In 2002, the start‐up company PayPal had just been acquired by eBay for $1. 5 billion. This created a lot of buzz in Silicon Valley. Three PayPal employees, Jawed Karim, Chad Hurley, and Steven Chen, were some of these idea generators. They soon came up with the idea for the YouTube website, but it was nothing like the website we know today.

#2

The story of YouTube is a great example of how focusing on the problem can lead you to find solutions. The website was initially created as a dating website, but when it was realized that the users were posting videos of themselves and their friends doing funny or embarrassing things, the company switched gears and began supporting video uploads.

#3

The YouTube Formula is a set of steps you can follow to gain success on YouTube. It consists of analyzing what's working and what's not, and making changes accordingly. This is the premise on which the whole book is built.

#4

The YouTube ecosystem is made up of many different parts, and each one affects the whole in some way. The creator, the viewer, the advertiser, the brand, copyright holders, and MCNs all contribute to the YouTube experience.

#5

The first consideration in the YouTube ecosystem is the viewer. If no one is coming around to watch, the rest of the ecosystem is dead in the water. In March 2007, a little company called Viacom, along with several others, sued Google and YouTube for $1 billion worth of copyright infringement issues.

#6

The Content ID system was implemented in 2007, and it was a game changer for YouTube. It allowed the platform to attach a unique digital fingerprint to new uploaded content, which could then be tracked and measured against already existing copyrighted content.

#7

In 2007, YouTube added two features that would have a huge impact on the site’s future. In-video advertisements and the Partner Program, which allowed creators to make money from ad revenue sharing. However, this also meant that creators could use tactics to get people to click on their videos, even if those tactics were deceptive.

#8

The great California gold rush of digital marketing was the advent of advertising revenue sharing. Companies were willing to share a portion of their revenue with content creators, who in turn were willing to compete against each other to get viewers.

#9

Because of the digital gold rush that YouTube brought about, it was not able to handle the masses of contributors. This is where the multichannel networks came in. They helped creators and businesses with audience growth, resources for production, and brand opportunities.

#10

The first component of the YouTube ecosystem is the viewer, who has changed over the years. YouTube wants to have satisfied viewers, as they know that happy viewers will stay around longer and produce content creators and advertisers who are pleased with the platform.

#11

You have to dig into the data to find out what's working and what isn’t, and adapt your strategies accordingly.

#12

The goal of YouTube's AI was to get people to watch more videos and click less, which it did by recommending videos that were relevant to what viewers had already shown interest in.

#13

The YouTube AI has changed over time to create a personalized feed based on customization. It now suggests, with uncanny accuracy, what a viewer might want to watch.

#14

YouTube had to change its algorithms in order to keep up with the rapidly changing world around it. In order to do so, it implemented deep learning machines that watched the behavior of its users and used that to make recommendations.

#15

The internet is a vast world of possibilities that can be explored and learned from by using deep learning. YouTube and its ecosystem are direct beneficiaries since viewers who watch more videos watch more ads and generate more revenue for the platform.

#16

In 2012, daily watch time on YouTube averaged out at about a hundred million hours. In 2019, that average sits at a mind-blowing one billion hours a day.

#17

When visitors arrive at youtube. com, they are being followed. It's like when you were a kid and went to your friend's house to play, and their pesky kid brother wouldn't leave you alone, but think of it this way: instead of being pesky, the brother quietly observes your behavior and accommodates your every whim.

#18

The second area the AI observes is user behavior via metadata. It determines things about a video based on the behavior of the person whose eyes are on the screen and whose fingers are doing the clicking.

#19

The AI uses the advanced technology of Google's suite of AI products to gather data. It operates a program called Cloud Vision that takes points from each image in the thumbnail and, using billions of data points already in the system, recognizes those images.

#20

The AI goes through every single frame of the video and creates shot lists and labels based on what it sees in the content of the video itself. It cuts through the noise of every single thing in every frame and determines what is most important according to that video and its metadata.

#21

The AI is also listening for actual sentence structure and breaking it down into a sentence diagram. This extracts the meaning of what is being said. It can differentiate language so it can group it categorically, but not just on the surface.

#22

The algorithm also looks at the video's title and description to supplement what it has already learned from the thumbnail, frame by frame. The AI knows that people can be deceptive with metadata, but they can't lie about what's actually in the content.

#23

YouTube has more than one algorithm. The AI uses multiple systems, and each has its own objective and goal. The surface features viewers see are Browse Features: Homepage and Subscription, Suggested, Trending, Notification, and Search.

#24

YouTube’s Homepage has changed over time. It used to be where users saw only video recommendations of channels they had subscribed to. Now the Homepage has a personalized recommendation feed based on that user’s history over time.

#25

Another place besides the Homepage creators should be focusing on is Suggested feed, including the Up Next video. This is a powerful place to be as viewers stick around when this feature is working well.

#26

The geo‐specific water cooler is a term I use to describe the way trends are created and distributed. It refers to the fact that even the Internet has geographical regions, and that websites with more authority than others will have topics that trend better because YouTube recognizes this and puts them in their own Trending section.

#27

The Search feature allows users to type in a keyword or phrase as a query and find videos related to that query. The algorithm narrows down the results based on the video's metadata and past data from people searching similar queries, and it also looks closely at trending videos.

#28

You have learned about YouTube's history and inner workings, and how the algorithm works. Now that you understand the system, you can move on to the rest of the book and learn how to implement systems and strategies that work with the algorithm instead of being subjugated by it.