Regardless of whether you think your content matters or not, one thing is for sure — effective content is an integral piece to the SEO puzzle.
As link-building campaigns go, there isn’t anything more valuable than strong content.
In a consumer-driven marketplace, providing bigger and better material to a consumer base hungry for the most up-to-date information remains one of, if not the most, effective ways to gobble up those sweet, sweet links.
If you don't want to just take my word at face-value, try the opinions of industry experts:
Peter Himler of Forbes
Bill Gates of Come On, It’s Freaking Bill Gates
Tad Chef of CognitiveSEO
Nick Eubanks of IFTF
Don't Like Opinions?
Take a look at some of the data:
The average Google first page result contained 1890 words in 2016.
96% of B2B buyers want content with more input from industry thought leaders.
55% of B2B content marketers can't define an effective content marketing campaign.
72% of marketers worldwide credit relevant content creation as the most effective SEO tactic.
Backed by all of these industry experts and stats, it seems like slam dunk. Still, people get it wrong for a bunch of different reasons.
One of the main reasons is ... that they're relying too heavily on industry experts and statistics.
I know. I know. This was a shocking turn of events, but that shouldn’t deflate the gravity of the sentiment or distract you from the point of this article.
The simple fact remains that there is a serious difference between the perceived effectiveness of these two distinct approaches on the minds of consumers. For now, let's call the two approaches the egobait method and the raw data method.
In order to give you a better idea of the effectiveness of both, we will use two separate examples of promotional content pieces that I'm From the Future produced for our clients, and compare their respective pros, cons, and ultimate results.
To shed some light on the egobait method, we will dive into a piece we produced for an e-commerce home improvement retailer. Acting as our counterweight on the the raw data side will be a piece produced for an e-commerce fashion retailer.
We will try to determine if there is a statistical advantage to producing one type of content over the other, and take a look at the tangential benefits and drawbacks of each in the long run.
The Egobait Method
For e-commerce sites, it's a well-established principle that adding customer testimonials can have tremendous impact on increasing the conversion rate for a site.
It makes sense, then, that adding well-recognized industry experts to your content would increase the traffic and overall effectiveness of your piece.
By having definitive industry leaders provide their insights and knowledge to your content, your content will be valued more heavily.
Customers in your industry should pay attention to your content over all of your competitors since you have enough sway to garner quotes from influential people.
As we were creating our home improvement retailer’s content, we decided to implement a variation of the Skyscraper Technique, in that we went out and found some content pieces that were doing well for our primary keywords, and we blew them out of the water.
We noticed that DIY projects were some of the most searched for content in our vertical, so providing a bigger and better DIY piece was the natural response.
After we established our topic, the next step was to secure industry experts to contribute to our piece and confirm that they would promote the article after it was published.
Through our outreach efforts, and a strict return link requirement structure, we secured 14 expert quotes, such as:
And
The Results
Our article did extremely well, given the market and the state of the blog that we were posting on.
By this I mean, our client’s vertical does not contain many heavily trafficked keywords and our client’s writing presence was close to non-existent prior to our intervention.
In fact, from March 16 to April 2, 2016 (which is the same time period that we analyzed the performance of our test article), our client’s blog traffic looked like this:
And again, graphically:
Through our piece, we were able to see the following improvements in the blog statistics:
1,217.2% Increase in Total Pageviews
1,271.0% Increase in Unique Pageviews
331.8% Increase in Average Time on Page
Now, one might wonder, why the this worked so well, which brings up the more important question:
Did it really work that well?
For a relative nobody in this specific of a vertical to make this jump from one piece of content is great.
But it makes you wonder why it worked and whether it is sustainable.
Well, the first answer is simple.
This piece worked well because of social proof and promotion.
The beauty of performing this version of the skyscraper technique is that you start off your content piece with some guaranteed backlinks from trusted sources, and you confirmed them yourself.
You are also adding in the promotion channels of a handful, if not all, of your industry experts.
They will promote the piece because it features them, and they will send it to their already strong base of followers. Suddenly, a brand new piece on a relatively unheard of site is able to reach thousands of additional consumers.
But is this traffic sustainable?
Yes.
I should qualify that. Yes, to a degree.
Remember my fancy screenshot above?
It showed that, over the course of an 18 day promotional cycle, the blog received 233 pageviews, which amounts to roughly 13 per day (if you round up).
The blog also managed to keep readers on the page for an average of 88 seconds.
Well, in the 11 days that followed this content promotion, the blog had received 198 pageviews, which equates to about 18 per day, and the visitors were staying for an average time of 129 seconds.
Simplified down, the blog has seen a 138% jump in pageviews and 147% increase in average time on page. Not too shabby.
The Raw Data Method
This, in my opinion, is the more entertaining method for creating content.
I have always found that providing real numbers and raw data is a way more compelling and engaging way to prove a point.
As a reader, I believe that it is more entertaining to be able to see the raw data, delve into the numbers, understand what they mean, and then come to a conclusion.
That was why I was so excited to produce the data research piece for our fashion retail client.
In order to produce the piece that we put together, we obtained real sales data for a specific set of products over the course of the calendar year and compared that data with non-sales statistics for the industry.
The best part was that NO ONE ELSE produced any similar content prior to us in this field. This was the first time ever that someone was able to obtain this type of information and attempted to make sense of the data based off of non-sales stats.
What were the results?
Well, before I get to the results, I think I should add some context.
Our client, like our last example, did not invest a lot of time or expertise into their blog. While they do have a blog and do update it fairly regularly, there is not a logical or detailed process for the posts.
They tend to cover a wide range of topics, most of which are not keyword-driven or targeted to any specific cohesive goal.
As it turns out, this isn’t a sound strategy to proceed with, as you can see by their analytics data. From March 1 through March 9, the blog received the following pageviews:
From an outside perspective, 355 unique pageviews might not seem terrible over the course of eight days for a relatively new blog, but for the blog of a major e-commerce fashion retailer, this falls far short of where it should be at this point.
In order to support this claim, consider our first piece for this client.
It was a statistical look into the effects that NBA basketball player performance has on the retail revenue they see, and this piece lived on its own landing page separate from the blog and the retail site, and over the same period of time, the piece saw the following results:
Why did this piece perform so much better than the blog articles that this fashion retailer was publishing?
Well, the first reason is keyword research.
We identified primary keywords in the space to focus on.
For instance:
And
While this piece was not an SEO play, the page itself began ranking for 32 keywords in this niche over a very short period of time.
Through a concerted effort to use familial terms, with the help of one of my favorite tools Alchemy API, to our targeted keywords, we were able to create the context around our target keywords that Google is looking for.
Those people over at Google are smart, and they know how this industry attacks keywords.
More importantly, they know how people search, and therefore, producing context around your primary keywords is the most efficient method to gaining traffic.
The second reason this piece was successful so quickly is that we promoted the article like a ringleader at the circus.
The 80/20 rule for content promotion was in full display during this period, as we made a concerted effort to let every big hitter in this insanely popular vertical know about our article.
While this is great for getting links and traffic to the page, it has it’s own drawbacks, that I will get into a bit later.
The main point of this article is to compare these two methods though, so let’s get into the stats as to the effectiveness of our data-driven piece, and see how it stacked up to the blog for our fashion retailer.
Over the same time period, our article outperformed the blog by:
616.6% increase in total pageviews
921.4% increase in unique pageviews
261.1% increase in time spent on page
1.7k social shares compared to 28 for the blog itself (too big of an increase to show the % increase)
The Real Test
The best way to represent the comparison between these two approaches and gauge their effectiveness could be simply by a straight compare and contrast of the numbers:
Home Improvement Retailer
1,217.2% Increase in total pageviews
1,271.0% Increase in unique pageviews
331.8% Increase in average time on page
Fashion Retailer
616.6% increase in total pageviews
921.4% increase in unique pageviews
261.1% increase in time spent on page
1.7k social shares compared to 28 for the blog itself (too big of an increase to show the % increase)
By this measure, it would appear that the egobait method wins out.
However, that may not actually be the case.
Maybe we should delve a little deeper into the benefits and drawbacks of both methods.
We discussed the pros of egobaiting earlier, but there are some pretty severe drawbacks as well.
The primary one being that you are just rehashing information that is currently out there, so any dream of being associated with original content and newsworthy statistics goes out the door.
This might not affect your piece overall.
You can orchestrate traffic to your article if you handle the approach properly. But the fact remains that you are not establishing a name brand for your blog and will only start to move the needle if you maintain your presence over several posts of this style.
While that might not be the biggest drawback, it is something to keep in mind as you invest your time and energy into this type of a campaign.
On the other hand...
The Raw Data Approach Has its Benefits and Drawbacks
On one side, you are able to create something from scratch, which allows your designers and developers the freedom and creativity to come up with new themes without having to be reliant on the client’s standards.
Additionally, you are able to create a brand new concept based on the research that you and your team performed, setting industry standards for what the consumers should be looking for, using real life stats, and sharing those stats with industry leaders.
Nothing is more exciting than seeing industry experts pick up your research to support one of their points.
However, that can lead to the dark side of this approach, which is putting your conceptual ideas out there where anyone can steal it.
When we were promoting our piece, we reached out to ESPN, as a long shot to try and get our piece picked up or linked to, and we received no response.
Here is our email to an ESPN reporter:
“Hey ****, While doing research for an upcoming resource page on how NBA player performance impacts shoe sale revenue, I came across True Hoop. I just wanted to say I was hooked on the content from the moment I visited your site. Are you a data lover like me? I just finished the resource guide, and I think it could be of interest to you as it contains data-driven results, interactive graphs, plus statistics you can't find ANYWHERE else. (Do you know which NBA player sold the most shoes during the 2014-2015 season? Hint: It may not be who you think…) If you have just a few minutes to spare, you won't be disappointed if you give it a quick read: ****. I'd love to hear your opinion on the piece, especially because it seems like a topic you're well-versed in. :) I was wondering if you'd have any interest in republishing the piece or using it as a resource in an upcoming post (or even adding it to a previous post). I really think your audience would love it! Let me know if you have any questions - I'm happy to answer! Thanks,”
We sent this email out on March 2, and we followed up on March 8, with no response.
However, by March 23rd, ESPN came out with their own version of it.
Now I should be clear - I am in no way saying ESPN stole our concept. The article is focused on a player we did not discuss, and the topic was addressed in a varied and unique way.
However, the conceptual similarities between our piece and this article are somewhat telling.
Here lies one of the biggest negatives to this approach.
Due to the fact that we were creating a brand new piece and we were new research on a less-established domain, the chances were high that some of the heavy hitters in the industry would use our research for themselves.
In addition to this negative, there is always the concern that not having established readership will create a tough situation to spurn up interesting discussions.
People may also not be blown away by the information presented, as numbers and stats don't resonate with everyone.
The Results
The primary purpose of this article was to explore whether the egobait method still works.
We went about looking into this by comparing our egobait process against a raw data approach. Through this process, we discovered that both methods work.
The general idea is that if you work your ass off and put together compelling content, you will be able to see some movement on your piece.
But this is a world of winners and losers, so we're not calling it a tie.
If you want to break it down statistically, at least in the cases presented, the egobait method still moves the needle more and has some staying power when looking at its overall impact on a client’s brand.
There's some irony here. We went about making this point by using the raw data method.
If you're still reading by now, I hope that wasn't lost on you.