I’ve been told that the majority of viewership on YouTube is driven through the suggested videos column on watch pages. It’s certainly true for the company that I work for, Frederator Networks, which receives 40% or more of its viewership from YouTube suggested videos. Dominating this section on your own videos and others’ has the ability to drive massive viewership and ensure your audience is not whisked away to someone else’s videos. In this post we’ll take a look at 7 ways you can dominate the suggested videos column on YouTube.
7 Ways to Appear in YouTube Suggested Videos
The YouTube suggested videos column is made up of three sets of videos:
- Suggested videos are the 4 videos featured from the creator (algorithmically selected)
- Related videos are videos that are similar to yours
- Recommended videos are based on the viewer
To determine which video the algorithm will place, YouTube uses metrics such as “watch time”, relevancy, viewership history, engagements, and more. There are many ways to influence these metrics, and thus dominate the suggested videos column. Here’s what we do at Frederator Networks to secure our own suggested videos column for our owned and operated channels Cartoon Hangover, Channel Frederator, The Leaderboard and Cinematica; and to drive millions of views from the suggested videos columns throughout all of YouTube.
We have 7 primary things that directly impact our suggested videos performance. We make “engaging” videos, encourage “engagement actions”, optimize our titles, optimize our metadata, interlink our videos, make great thumbnails and start YouTube Sessions.
#1 Make “Engaging” Video Content
At Frederator Networks when we say “engaging” we mean videos that keep the viewer watching for a long period of time, roughly 7+ minutes or more. An example of this is our ‘107 Facts’ video series, which is specifically designed to generate long watch times.
The average watch time for this series is over 9 minutes. This is great for our suggested videos performance because YouTube’s algorithms, especially the suggested videos algorithm, are highly optimized to promote videos that keep people on the YouTube platform for extended periods of time both on an individual video and viewing session level. There are a plethora of resources out there to help you shape the content that will be most engaging to your audience. Be sure to check any implemented learnings against YouTube analytics, which provides top of the line metrics in the form of audience retention graphs and average view durations across your entire channel so you can see what is and what is not working.
#2 Encourage “Engagement Actions”
A second way to dominate the suggested videos column is to focus on engagement actions. A report recently released by Philip Zeplin at Novel Concept, suggests that the algorithm (in this case the search results algorithm) may give weight to videos with lots of likes, dislikes, and comments. He does admit that “videos that are generally good enough to receive a high watch time and viewer retention, are also naturally videos that engage people.” So take the data he presents for what it is: a limited window into the black box of the YouTube search algorithm.
Data aside, from a theoretical and historical standpoint, it does stand to reason that YouTube’s algorithms look favorably upon videos with lots of likes, dislikes and comments as it has in the past. When a viewer has an emotional reaction to a video as expressed in a like, dislike or comment, it could likely lead to a longer watch session. In YouTube parlance it could look like this:
- You watch a video and your brain releases a ton of chemicals (endorphins, etc.).
- You click “like” and comment about how great it was.
- The punch of these chemicals recedes as the video ends and you want more of those chemicals.
- You click on another video.
- And that’s how you ended up in that part of YouTube again… 1 hour later.
I’d add to this that encouraging these actions could potentially create a heightened emotional experience in the viewer that wasn’t necessarily there before. If a call to action spurs a viewer to engage, it could have a similar effect as the psychological concept that body actions like smiling can influence our emotions. Therefore, by giving a call to action to engage with a video we are potentially creating a heightened emotional connection for the viewer where there was none before, which could lead to a longer session and more suggested video algorithm love for our videos.
There’s another, less theoretical, reason to encourage commenting. At Frederator Networks we encourage commenting heavily because YouTube has stated that it utilizes comments as a form of meta data around a video. We promote commenting by replying to a lot of comments, but also posting our own comment questions with each video. We typically post a question in the comment section when we release a video that pertains to the property being discussed. This serves two purposes. First, it generates more comments. Second, it helps condition the algorithm for keywords surrounding that property. For example, on SpongeBob we might ask the question: “Who’s Your Favorite SpongeBob Character?”. People then reply with the names of the characters from the show, thus telling YouTube this video has a lot to do with that show.
#3 Optimize YouTube Video Titles
A main source of creator entered metadata comes from the title of a video. We use our titles to do three things, which have an impact on the suggested videos algorithm:
Get people to click on our videos – The first step in generating watch time is to get someone to start our videos! Titles (and thumbnails) are the two most important components to getting that click in our view.
To tell the algorithm many of our videos are relevant to each other – We indicate this relation to the algorithm by always including the name of the show, the episode number and the name of the channel in the title. For example, for ‘107 SpongeBob SquarePants Facts You Should Know (ToonedUp #37) @ChannelFrederator’ For this video we manage to secure 18 of 19 of the suggested video spots for our 107 Facts videos.
To try to secure high ranks for a particular Keyword for our video – This is actually most important for securing placements in the suggested videos column for other people’s videos. To this day, 107 SpongeBob regularly receives 60,000+ monthly views (~20% of its total monthly views) from suggested videos on other people’s watch pages and this video was released in August of 2015. I should add that the majority of these videos are about SpongeBob, which demonstrates the importance of “relevancy” to the suggested videos algorithm.
# 4 Optimize YouTube Video Meta Data
Descriptions, Tags and Closed Captions are all important aspects of our meta data. There are far smarter people than me in this form of SEO right here on ReelSEO (editor note: thanks Matt!), so I’ll leave the best practices to them. That said, many if not all of the principles around SEO apply to the suggested videos algorithm as well. At Frederator Networks our guidelines for these forms of metadata are:
- Your video descriptions should be a minimum of 3 sentences and placed at the top of the description section before everything else such as links.
- Always include a generic 3 – 5 sentence description of the show and channel at the bottom of the description (use the defaults tool on YouTube!)
- Descriptions & Tags should focus on one primary keyword
- Limit tags to 10 – 12 focusing on the primary keyword*
- Always include the same 4 – 6 “generic tags” about the show and channel**
NOTE: *For ‘107 More SpongedBob Facts‘ we used these specific keywords: SpongeBob, SpongeBob SquarePants, facts about SpongeBob, 107 facts about SpongeBob, top SpongeBob facts, 107 facts about SpongeBob SquarePants, best spongebob facts, nickelodeon, patrick star, sandy cheeks, squidward tentacles. (**For ToonedUp & Channel Frederator we always include: “Channel Frederator” “ToonedUp” “107 Facts” “Frederator” “Tooned Up” “Cartoon”).
#5 Interlink Videos via Annotations, Playlists
A fifth way we utilize the tools available to us to dominate the suggested videos algorithm is through interlinking of our videos in annotations, InVideo programming, playlists, links in descriptions and commenting on older videos with links to our newer videos. I’ll be honest and tell you we have 0 data or evidence, other than anecdotal, that indicates the suggested videos algorithm is directly influenced by any of these actions. For example, we do not know if we put two videos in a playlist together whether or not that is a signal the suggested videos algorithm picks up on, or how strong that signal is if it does.
However, we do have a lot of data that indicates these actions lead to longer session and view durations. We know the suggested videos algorithm is highly optimized for view and session duration and therefore we can say that these actions at least have an indirect impact on the suggested videos algorithm and are very much worth the minimal time and effort it takes to do them.
#6 Upload Compelling Custom Thumbnails
In our view, custom thumbnails are generally the single most important element in getting someone to actually click on our videos (besides our brand!). The more people who click on our videos, the more watch time we’re able to rack up.
Now, there’s a pitfall here, which is that if we make a misleading thumbnail (or title), people will click away from our video quickly, harming our average view duration and harming our suggested video algorithm performance. This has been confirmed many times over by YouTube, but is laid out quite well in this Computerphile interview with YouTube executive Cristos Goodrow. There are lots of resources available about how to make great thumbnails. This article I wrote about thumbnails is a great start.
#7 Start YouTube Sessions
The final key factor across all of YouTube’s algorithms, and arguably the one with the least amount of data available about it, is whether or not a video starts a viewing session on YouTube, and how often does a channel start those viewing sessions.
YouTube features videos and channels that frequently start sessions because they have data that shows session time and views increase exponentially the more frequently a viewer comes back to YouTube. For example, if someone comes to YouTube once a week, they may watch 20 minutes of videos. If they come twice a week that increases to 50 minutes of videos. 4 visits a week generates 150 minutes watched and so on.** This means that the more videos we post, which cause people to come to YouTube, the more likely it is our videos will be featured in suggested videos.
An extra step we take is building touchpoints with our audience outside of YouTube. These are our social profiles, media connections for embeds, email lists, websites, connections to other YouTubers and so on. These profiles, connections and lists, even if they’re small, help act as a catalysts for starting sessions and thus growing our audience through suggested videos viewership. In addition to this, we communicate our schedule. If our audience knows when they should come back to our channels to see a new video, they will come and find our videos when they are set to go live. (**Keep in mind these are not actual figures just an example).
Potential Road Bumps
There can be a few road bumps along the way to dominating the suggested videos column. First and foremost is the “Up Next” feature. This unit is in the first position of the suggested videos column and autoplays (if enabled) when a video ends. This unit is algorithmically programmed, and is not necessarily another video from the same channel.
The second road bump to dominating suggested videos is the “Recommended” slots in the suggested video column. This placement is highly dependent upon the unique viewer. Keeping our audience watching our videos through annotations, calls to action, etc. is the way we secure these spots for our own videos.
The final road bump is whether or not our videos act as an “Exit Page.” An exit page is essentially the last page a viewer hits before leaving a site. In the YouTube ecosystem, if one of our video pages causes sessions to terminate, that video, and potentially other videos from our channel, will not be served as frequently or at all.
CONCLUSION:
Dominating the suggested videos column is not easy. It starts with great content and is accelerated by brilliant programming and an engaged audience. What is outlined in this document is just a part (an extremely important part!) of our overall programming and audience development strategy.