Rankings

The Role of On-Page SEO Content: Relevance, Not Rankings?

People love to talk about the ways that search engines determine their rankings. I always advise our clients to stay away from trying to find "the edge of the algorithm" or any practices that are manipulative because of the risk these tactics carry, but the search engines continue to have many limitations on what they can do, and how they interpret what they see.

Therefore it is prudent for publishers to understand the landscape, and do the right things to make the job of the search engines easier. The SEOmoz ranking factors survey includes a great pie chart showing an estimation of the weighting of the various ranking factors:

However, this picture was reshaped back on February 23 with Google's Panda update. With this update Google added the notions of user engagement and content quality firmly into the mix. This led me to more recently propose a different view of SEO ranking signals:

As you can see in this model, I guessed that the broad category of social engagement and content quality now represents a large 20 percent piece of the Google rankings pie. As I defined it, this piece includes a variety of user engagement signals, such as the way people interact with your site, some form of evaluating the content itself, how your metrics compare to competition on a per search query basis, and more.

I should also note that less is currently understood about the way that Bing is using similar signals, so this discussion is oriented around Google, but Bing is likely doing similar things.

Let's Go One Step Further

When I speak with people about on page SEO, I often refer to it as being required to gain "entrance into the competition":

 

What I mean by this is that you can't compete for ranking on a specific keyphrase unless your web page provides signals that suggest to the search engine that the page is a good match for the user query. For example, if your page is about Tupperware (for example, look at this page), there is little chance that you can get that page to rank for the term "used cars." It just isn't relevant.

Of course, a few years back there was the notion of Google (or link) bombing, where SEOs ran some experiments to make irrelevant pages rank for various search queries solely through implementing lots of links to a web page using a target keyphrase. Search engines have mostly solved this problem.

So far this is all pretty straightforward, but the notion I'm putting out there today is that from an SEO perspective that on page content is not a ranking factor. It is solely about helping establish what search queries your page might be relevant to.

Here's what an adjusted ranking factors chart might look like if you take this into consideration:

This may be a subtle mental shift but I think it is am important one. If you work with clients, or within an organization, with people who have a limited understanding of SEO, you can often find yourself in discussions where they are unwilling to make adjustments to on page content, because they don't see why they should make those changes. They may not realize that the result of that is that those pages end up having no possibility of ranking for a particular term.

There is also the flip side of overemphasis. I have encountered countless people who think that SEO begins and ends with on page SEO.

"I've optimized the site itself, so I'm done, right," they ask.

Well, no, you aren't. It simply buys you a ticket to the competition (it makes you "relevant" to the query).

This is an essential step to success. You don't get to play without it, but there is far more work to be done before you can declare victory. This is the link building, and engagement optimization which make up a full 96 percent of the rankings picture in my adapted chart.

One side note: the only way on-page optimization can enter into the rankings chart is if you engage in keyword stuffing of any kind. This is still something that you can encounter on the web, and I believe that any sort of abusive practices can become a negative ranking factor, but for purposes of my chart, I have chosen to start with the assumption that this type of practice isn't a consideration.

Summary

I use this mental model when I think about SEO work, and it helps me get to a really clear picture on how I spend my time. It also helps me get others focused on where time is spent, and how the major components of the SEO world fit together.

You can't participate without addressing on-page SEO (after all you won't be relevant), but you can't win without addressing the promotion and user engagement pieces of the puzzle either.

As always, bear in mind that your publishing strategy should begin and end with understanding what unique value you can bring to visitors to your site and how best to provide that value to them. This is the first and most critical element of SEO.

Being mindful of the limitations of search engines and making their job easier is another necessary step in the process. To that end, provide clear keyword based signals as to what your pages are about. Make sure you are in the competition as your first step, and then set out to win it with an effective marketing strategy for your site.

        Actionable Media Attribution and Analytics for Search Marketers?

Attribution of digital marketing efforts -- across elements such as paid search, organic search, display and social media -- gets no shortage of discussion among search marketers today. This is for good reason. Technology has enabled marketers to understand how their distinct marketing efforts impact each other.

Meanwhile, consumers are transitioning much of the purchase funnel online, which makes attribution analysis even more important. But questions persist: Is the effort required for proper attribution worth the payoff, and what do I do with the data when I get it? 

Specifically, there are distinct ways that marketers should be using funnel analysis and attribution to impact their ROI:

1. Centralized tracking which de-duplicates performance across digital marketing channels to avoid "double-paying" for conversions across multiple vendors.
   
2. High level funnel analysis to support media mix decisions and understand assisting interactions between different types of media.
   
3. A feedback mechanism into bid optimization, which values media in a consistent manner with a marketer's attribution model.

The following is a quick scenario about one of our customers (a national hotel chain running search and display) and how they took advantage of all three benefits above. It provides a useful and illustrative real-world example of how attribution can positively impact our ROI. 

This customer had been using last click attribution for several years. As a result, all of the originating and assisting media was greatly under-credited in the day-to-day attribution accounting. 

De-duplication of actions had already been eliminated as an early challenge. The first step in the attribution analysis was to examine the funnel position of the marketing channels. 

We discovered that non-brand keywords and brand-display tended to appear early in the funnel process, while brand search and re targeted display tended to "close the deal." 

Once we understood the relationship between each of these marketing channels and funnel position and analyzed the data further, we ended up recommending a "spread" model for this customerâ`s attribution, one where revenue and action credit was divided fractionally across various clicks and impressions. 

The spread model still favored the last exposure, but the analysis accounted for media where the marketer had more headroom for efficient spending that would end up feeding the funnel, but hadn't been perceived to be efficient enough (on a last click model) to justify additional spending. 

After the attribution model was changed, our paid search portfolio optimization algorithm started shifting spend up the funnel to keywords that had been bid down previously. This kicked off a virtuous cycle where top of funnel search ended up assisting brand search and display retargeting, both of which were extremely cost effective at closing the deal. 

The optimization algorithms automatically started feeding the top of the funnel. Overall efficiency improved across all of their marketing channels, which in turn meant budgets could be raised while sticking to the same CPA goals that the marketer had been targeting before. 

More budget shifted up the funnel created more efficiency, until we reached a point of stasis around the desired CPA goal across all media channels. 

The new model allowed the marketer to spend 42 percent more on paid search and earn 34 percent more revenue attributed to paid search, while still growing their overall funnel volume significantly and maintaining a flat ROAS across all media. 

Attribution modeling and analytics can be vital to the success of a marketing campaign, but only if the attribution analytic's are actionable and fed back directly into the optimization of your campaigns. 

For this marketer and others who have adopted attribution and automated these learnings to feed their media optimization, the return is most certainly worth the effort.