This is a guest post by Nick Kellet, co-founder of Listly.
You influence Google search results!
Did you know you matter in the eyes of Google? Google has given power to the people. In so doing they created the world’s biggest crowdsourcing platform.
So what is Google?
We know it’s a “Search Engine”. Google began by building on the library model of citations and patenting the notion of Page Rank, defined by backlinks to your content. The first law of gaming kicked in.
“If a system can be gamed, it will be”
A tribe of SEO experts were born to game organic results. Google has been in a cat and mouse game with these self professed gurus ever since.
Google 1.0 : Power to the Gurus
Who makes backlinks? Pretty much it’s bloggers, brands and publishers. SEO specialists create links to build Page Rank for their own sites and for clients. Links could easily be gamed by trading, instead of being earned.
With Penguin and Panda Google demonstrates the system can’t be gamed. That debate is still raging and there will always be people who think they can beat the system. Long live Vegas.
Black hat SEO is out. White hat SEO is in. It’s that simple. Nobody knows how it works. Google’s search algorithm is cloaked in magic and mystery. Google has also made search personal, which makes gaming the system much harder.
Google 2.0 : Power to the People
I have a theory how Google is working today. By way of full disclosure, my theory comes from my work on Listly. This has given me a great deal of data to evolve a hypothesis that Google has become a massive crowdsourcing platform.
Google 1.0 was about tracking backlinks. Today that’s still valid, but just part of a now bigger pie.
You should know Google 2.0 builds social sharing into the mix. Sharing is another proxy for interestingness. You don’t just want to make great content, you need to create content that is highly shareable.
Sharing is hard to deliver, but tools like Triberr or GaggleAmp or Buffer tend to make cross-sharing, resharing and timing of sharing easier to scale (both inside and outside the enterprise).
With the rise of importance in sharing we need to think about our full “Sharing Supply Chain”.
There are more sharers than there are content creators, so gaming the system is harder. Headlines have become even more important.
The SEO on a post does not change over time, but the potential to keep your post share-worthy for longer should make you reevaluate the lifecycle of each post.
What’s more interesting is what Google is doing with the input it gets from it’s billions of users worldwide. This is why I believe Google is the world’s biggest crowdsourcing platform.
- We don’t know how this works.
- We don’t know how much data they accumulate.
- We don’t know which signals they choose to listen to.
We do know Google is listening. Google does its best job to render what’s interesting using all the signals it can muster, but beyond those signals Google is factoring in user behaviour on each search term. Google is being driven by 3 datasources:
- Traditional page rank: backlinks and keyword analysis
- Social sharing : a subtler form of content ranking.
- Search user content engagement
So if an item is on Pg 3 of Google’s search at position 4 is outperforming the preceding items , this item will quickly move up the leader board and advance to page 2. So the process of bubble sorting continues.
Interestingness has become more and more dynamic and harder to game. With so many people influencing the results it’s much less feasible, if not impossible to have any meaningful influence on the search results. Quality will be your ultimate barometer.
Google 1.0 was a crowdsourced model where it outsourced the validation of interestingness to blogs. This worked well and was an enhancement on earlier models.
With the shift to Google 2.0 they have massively scaled up the number of people providing input and more importantly those people don’t even know they are teaching Google to improving its output. That’s the magic. We are oblivious. With billions of inputs every day there is no way to truly game the system.
Logging not Blogging
Don’t be fooled to thinking Google made Chrome because the world needed a better browser. Google made Chrome to better log all the things we do. They can track bounce rates of pages, our engagement times and our in page activity.
- Did we play content on the page?
- Did we jump tabs or continue watching or listening?
There’s a scary number of possibilities, but they all make for a better future search experience.
Why do I believe this to be true?
Supporting Data
I used to think my view was pure speculation. I just spoke with Edelman’s Jonny Bentwood, he’s the brains behind TweetLevel, one of the leading influence measurement platforms. We were talking about the next release of TweetLevel, launching on Nov 15 2012. Here’s an image of their Topology of Influence. I’m impressed by the new release. I think they have a unique and highly valuable approach to tracking influence. In this example, you can plot other people on the same chart and get a sense of the role they play.
Topology of Influence
Jonny said something I had to write down. I also used it to begin this post.
“You Influence Google Search”
I wrote a blog post “Is Social Media an Inclusive or Exclusive Club?“ after listening to one of his Influence Webinars. He really gets influence. I understood the significance of his comment. I know Jonny knows his stuff.
I’m not the only person believing this to be so. So why aren’t more people talking about this more? One theory is that it doesn’t serve the SEO gurus. That’s one theory. I’d be interested to hear your views.
Since joining Listly as co-founder we’ve seen some lists really perform. Some lists have created so much SEO traffic we simply had to explore. The outcome of this analysis changed our thinking on the lifecycle of content.
Countering The Normal Content Life Cycle
Most people expect your content’s lifecycle to look like this.
There’s a spike at launch as you promote your content. There may then be the odd additional mini spike after that, but that’s the norm. We all expect our content to flatline, so we feed the content beast with more content. We follow one spike with another. We eagerly tread the content hamster wheel. We certainly don’t expect that content to generate views at an increasing rate over time, post launch. That’s not today’s content norm.
However, we now believe, if you create great content that is loved by your readers – ie web search visitors, you can counter the spike and burn mentality. That’s my new theory. Take a look at these two charts. They show clicks per week over the last 10 months. Neither of these lists began with any kind of spike, but now they are a regular source of inbound traffic. It’s been a slow build. We’re wondering how to optimize this. What are the thresholds? The impact of old SEO strategies may still impact your content during the early stage of your content’s life, but over time power shifts to the audience’s view of value.
Hindi Evergreen Songs - Current SEO run rate: 25k views/month
Visio Alternatives for Mac - Current SEO run rate: 4.5k views/month
My key Takeaways
- These lists have received a lot of views, but that process was not instant.
- They gained visibility via improved SEO and this was not a function of any dubious activity.
- Search results are a slow cooker. They can brew for months. Quality can take time to rise to the surface.
- The lists have changed slowly over time, they have been extended and refined by the crowd
- They have been shared by users.
- They have been discovered by SEO. This discovery process has grown dramatically over this period
- They have low bounce rate on this content
Your Thoughts
Have you seen any other examples to support of contradict these findings?
Did you know you were shaping the Google experience for future users on a daily basis?
