In my last Just Behave article, I shared a set of metrics that will help you create a powerful SEO business case for your natural search projects.

Through the process we’re now able to tell the CFO something like this: “Our addressable market spans 200,000 unique keyword markets and totals roughly 5,000,000 searches per month, of which we’re capturing 1% currently. The cost of acquiring that traffic through PPC totals $1,000,000 per month.”

That paints a compelling (perhaps rosy) picture. But what’s driving your current performance? Why do you believe you can do better? In this installment, I share three more metrics that can you help create strong baselines, set realistic expectations, and direct your campaign towards the most effective outcome.

Keyword reach

So you’re getting 50,000 searchers from natural search a month (1% CTR). But is that good or not? It depends. Are a handful of search phrases sending 99% of the traffic? Or is traffic distributed evenly across thousands of long-tail phrases? The Keyword reach metric helps you quantify the breadth of your presence to better manage it.

To understand keyword reach, start with the number of unique search phrases that drive natural search traffic to your site currently. What volume of traffic does each phrase drive? Your analytics package likely contains this basic data. But before we get excited, let’s apply a few filters.

First, differentiate brand phrases from non-brand phrases in your calculation. Why? Searches for your brand or company name are just table stakes. Don’t let yourself feel good about them. What you care about increasing is your share of the non-brand markets. Once you’ve separated these, determine the percentage of your traffic driven from brand vs. non-brand queries. Many retailers, for instance, find that as much as 95% of their natural search traffic comes from brand vs. just 5% from non-brand phrases. This confirms a big opportunity.

Now that you’ve distinguished between brand and non-brand traffic phrases, you can calculate your traffic per keyword yield rate on your non-brand phrases. If 5% of your search traffic (2,500 searchers) is from 1,000 non-brand phrases, your yield rate would be 2.5 searchers per keyword (2,500 searchers / 1,000 phrases). If your optimization is successful at increasing rankings in these 1,000 keyword markets, you’d expect to see the keyword yield increasing as well, perhaps doubling to 5.0 searchers per keyword.

For benchmarking purposes, you should also slice search phrase data by engine. This helps you avoid being misled by high level trends, and will show you if your optimization work is helping your Bing performance, at the expense of your Google performance, for example.

Last, make sure you can determine whether keyword reach is increasing or decreasing on a comparable basis, such as month-over-month (MoM) or year-over-year (YoY). This way you can measure the impact of your optimization work going forward in an objective manner.

Understanding keyword reach lets us augment our business case with some more powerful information: “Of our 200,000 addressable keyword markets, we are reaching only 1,000. These keyword markets drive 2.5 searchers/keyword. 95% of our search traffic comes from queries for [company name].”

Keyword placement

How highly do you rank in those 1,000 non-brand keyword markets that drive traffic? Can you do better?

We all know there are scraping tools to capture rankings. Rather than worry about ranking in markets no one searches for, and that you get no traffic for, what if you could determine where you rank for the thousands of phrases that did drive traffic? There are tools that tell you this by parsing the referral strings on engine traffic. Each major engine thankfully passes an argument in the URL which tells you what page of the SERPS (although not the actual position—yet) the searcher clicked on to land on your page. Naturally you want to filter these by engine.

Armed with this information, you can identify which phrases are ranking on Page1 (P1) of Google, Yahoo, or Bing. You can use this of course to talk up your SEO ninja skills in front of your CEO. More importantly, you can identify which phrases are ranked on P2 or P3 etc, in each engine. Perhaps you’re ranked on Google’s Page 1 in 70% of the non-brand markets. 20% of the time you’re on P2. You can begin to imagine an SEO campaign aimed at these markets, in order to get your ranking onto P1, thereby increasing CTR and traffic by many multiples.

The keyword placement metric helps you further enhance your business case: “Of our 200,000 addressable keyword markets, we are reaching only 1,000. We rank on page 1 of Google in 70% on these keyword markets, driving 2.5 searchers/keyword. 95% of our search traffic comes from queries for [company name].”

Landing page yield

Natural search is a marketing funnel: at the top are your supply of pages which get crawled. Some percentage of those get indexed. A percentage of the pages indexed get ranked. A percentage of those get clicked, etc. So an important way to baseline current performance is to map your search traffic against the pages that drive the traffic. Surprisingly, this is more difficult than it seems. In fact, it is highly likely that you do not know how many pages are on your dynamic site (don’t worry—I won’t tell).

The easiest way we find to approximate site size is to measure the number of unique pages crawled by a particular engine over a period of time. Engine crawl has slowed recently. Review your log files for unique URLs requested by Googlebot over a 60 day time frame. Or you can run a crawler over your site. Either way, you should be able to parse highly duplicated pages from the count. For our purposes, let’s assume there were 10,000 unique URLs requested by Googlebot over the past 60 days. In other words, Google thinks your site has 10,000 pages.

Naturally, you want to compare this to how many pages Google reports having indexed. If you have just 1,000 indexed, you should investigate why 90% of the available landing page “inventory” you take to market is being rejected, and then develop strategies to address the issue.

You need to understand how many of your URLs drove search traffic. Suppose 250 pages are driving your 2,500 non-brand monthly searchers. That means 250 of your 1,000 indexed pages are performing—a rate of 25% yielding 10 searchers per page. However, you have 10,000 total pages, of which 250 are performing—an actual yield rate of 2.5%. If these were your metrics, you should have many questions:

• Why are 90% of my pages not being indexed?
• Why are 75% of my indexed pages not being found at all?
• How can I identify my non-performing pages?
• How can my 25% yielding pages achieve more than 10 searchers per page?

Asking and answering these questions leads to smarter strategies and more accountable performance.

Your business case now looks like this: “Our addressable market spans 200,000 unique keyword markets and totals roughly 5,000,000 searches per month, of which we’re capturing 1% currently. The cost of acquiring that traffic through PPC totals $1,000,000 per month. Of our 200,000 addressable keyword markets, we are reaching only 1,000. We rank on Page 1 of Google’s in 70% on these keyword markets, driving 2.5 searchers/keyword. 95% of our search traffic comes from queries for [company name]. 97.5% of our pages drive no search traffic.”

Remember, you can only manage what you measure. With these metrics, you can create performance baselines and develop data-driven SEO strategies aimed at achieving specific performance outcomes. Trust in the force, Luke.

As a search agency we see many different styles of PPC campaign design, from in-house teams, other agencies, and occasionally running across those from the search engines themselves. Broadly speaking, campaigns can fit into one of two categories:

1. Those heavy on keywords or phrases made up of low number of fairly generic terms (for the purpose of this article, referred to as “shorter keywords”)
2. Those using a high number of terms ranging from generic to improbable (or “longer keywords”)

Our approach has always been to go for broke with the number of terms we use in our campaigns. So, we’re better aligned with option two and I know we are not alone.

As spelled out in Convert More New Users Using Advanced Segments, I’m a huge fan of the new advanced segments feature in Google Analytics. This article offers another example of how advanced segments can help us chop up our data into more digestible morsels. My aim here is to show the workings of this type of segmenting and combine it with a custom report to analyze keyword data more efficiently. I finish with a note on applying similar filters and the many possibilities that follow. The goal? To demonstrate that there is now an easy way to measure the reward for the effort of building those keyword lists.

A common misconception

I know some of you are thinking “why not just use “long tail” and “head” instead of saying “shorter” and “longer.” I can hear a lot of experienced search marketers and analysts replying “because they aren’t the same thing!” But then there are some slightly quieter murmurs coming from an unnamed corner of the SEM population. This sounds more like “erm, well, yeah, they are. Aren’t they?”

To clear things up, the “long tail” refers to the hundreds or thousands of keywords sending users to your site which, individually have few visits but collectively form a substantial chunk of your total traffic. The length or number of words in the keyword in this definition is irrelevant.

To make the second group feel better about this situation, I would like to point out that the long-tail often is full of keywords containing 3 or more words. To compound this, we also don’t really have a collective term for these long, ungainly but highly profitable terms. If we did it might prevent this misconception.

Defining “longer keywords” & “shorter keywords”

In the example below, the obvious starting point for defining a “longer keyword” is four words or more because from this point onward, the sum total of all the bars in the chart is less than the total of the previous (three words) bar alone. By that mark, keywords with three words or less become my “shorter keywords.” As a general rule, your “longer keywords” will be between 3+ and 5+ terms. Either go with that or your own analysis.

Create the segments

I doff my cap to the Google Analytics Twitter team for publishing this screenshot of a regular expression (regex) filter and to my colleague James Carswell who took the Google regex and made it even shinier.

Now that you have your definitions, add the below regular expressions as in the images. Think about whether there are any other terms or traffic types you might want to exclude at this point.

The longer keywords segment

I have used this segment to specify that we want to see keywords which contain at least three spaces and therefore have four words or more (\s|\+).*(\s|\+).*(\s|\+) (we altered the original Google regex to take into account the fact that occasionally words are separated by “+” signs instead of spaces in Google Analytics).

The shorter keywords segment

Use this segment or copy from the below image to create a segment which only shows keywords containing three words or less.

Build a custom report

This example is taken from an ecommerce website so I have included revenue data. You can equally use goal conversion data or bounce rate and average time on site. I have included source and medium here so that the data is available should you want to take it to the next level.

After applying both the custom report and advanced segment to a keyword report you can start to play.

A small tip here: the maximum number of keywords you can view in one report in Google Analytics is 500. However, when viewing a keyword report you can change the limit by appending “&limit=n” to the url in your browser. Where “n” is the number of keywords you would like to see data for—I believe the maximum value is 20,000. You won’t see any change in the interface but when you download the report as a .csv file you should have all the data you wish.

Go out and play with your segments

There are so many ways we can apply variations of this segment to suit different job roles and business needs. Also, the results really will be different for everybody. Here are some different ways of looking at interpreting the data for this segment.

Value of short vs. long keywords. Try comparing the data for the two above segments. What do you see? Is it worth bidding on those big generic terms anymore?

SEO value. Try charting the rise of visits of your “longer keywords.” Is the situation improving? As above compare the segment with the shorter keyword segment. Are they both going in the same direction?

Campaign cross-pollination. You may be able to segment by paid search, and in turn use the data to inform and help guide your SEO work. Similarly, are there some nice long terms you haven’t got in your paid campaign which are working for SEO?

AdWords optimization. What is the relative CPC of the longer vs. shorter terms? Do you need to come up with different bid strategies for each?

Google ad position. Combine these two segments with a custom report showing overall data for the different ad slots. Do longer terms perform better?

Sussing out the true value of the head vs. the long tail. If you really must define things by long tail and head status then try adding a number of visits quantifier to each segment. A great use for this is to see the shorter terms which are effectively in the long tail in terms of volume. They can often give you great ideas for a whole new array of terms.

Compare the engines. Look at the relative performance of Google, Yahoo! and Bing, segmented by longer and shorter keywords. Which one is doing a better job of bringing in the traffic on longer keywords? How does that affect your strategy on these terms?

Above all, experiment! You might not know something is useful until you try it.

A common way of managing a brand in paid search results is to bid all brand terms to the first position. While this strategy may seem correct from a brand management standpoint, it misses out on many of the nuances of search engine marketing(SEM). For one, many brand campaigns contain over a 1,000 brand variations, of which over 500 may get clicked on in a given month. When a query is typed, these keywords compete among themselves for the impression.

Consider a brand called 123loans. A searcher may enter the brand query “123loanz.” Your campaign contains the following keywords:

Given the CTR of 123loans, its very likely that 123loanz is mapped by the search engine. The end result is an impression sucking effect from the lower bid keyword to the higher one and the net result is a higher cost per click (CPC).

My point is that brand keywords should also be optimized based on return on investment (ROI) considerations.

We looked at some of our clients for whom we managed a large number of brand keywords and the CPC and discovered the position distributions were quite telling. First, the number of variations of broad matches in each campaign was far more than exact or phrase matches. Next, more than 50% of broad matches were below average position of 1.5. In contrast, for exact matched keywords almost all were bid to the first position in search results for optimal performance.

Next, we looked at CPC distribution, using a special visualization tool called a volcano chart. The “mountains” represent the distribution of CPC by keyword, with each mountain representing a match type. Each red square represents a keyword and these have been plotted by CPC. For broad matches, the peak of the mountain is close to $0.2, indicating that the mean CPC is about 20 cents. But look at the variations. It peaks at $1 or more. One might argue that the positions for broad matches are all the way from position 1 to 7, so a variation in CPC is to be expected. However, if we look at the exact matched keywords, most of them are being bid to position 1. Although the mean is 10 cents, the range is from 1 cent to 40 cents.

From a statistical standpoint, these keywords will exhibit heterogeneous behavior, meaning they will not behave the same way, deliver the same performance or have identical ROI potential. If that’s the case, why should they all be treated the same way from a bidding standpoint?

The key takeaway from this is that you should look at the performance of your brand keywords just like non-branded ones, and even if you want them all to be at position 1, you should do so by bidding smartly. In the absence of sophisticated bidding technology, a good rule of thumb would be to leave the exact matches at position 1 but to also treat broad matched brand terms just like a regular non-branded keywords. Bidding all brand keywords to position 1 is at best inefficient and at worst foolhardy.

Two rockstars have emerged in the web analytics field to date. We all know who they are: Eric Peterson has demystified analytics for us, while Avinash Kaushik has helped us take it one day, or dare I say, “an hour a day,” at a time. And one of them says web analytics is easy while the other one says web analytics is very hard. So who is right?

Why web analytics is easy

Yes, it’s true. Web analytics is easy, according to Avinash Kaushik. It’s actually incredibly easy. Assuming that the desired outcomes of web analytics are changes that will positively impact your site and your bottom line (what other purpose can you think of?), you’ll find that even complete beginners can drive surprising value.

Web analytics is this easy because your web site has more issues than you’ll see in a month of Dr. Phil episodes. Starting with some of Kaushik’s favorite metrics like bounce rate by landing page, it’s a virtual walk in the park to identify a host of obvious issues with your site, your marketing, your calls to action and more.

Bounce rate / percent of single page view sessions (times where users enter your site and leave almost immediately) is the online version of your significant other saying “hell no” when you walk up with that new striped shirt you thought was so snazzy. Don’t take it personally when people reject your content, especially when you thought it was great. It isn’t. Just get over it and change it for the better. Test it using website optimizer. Your site is there to make you money, not generate pride.

Web analytics is also easy because you can learn as you go. Almost all valuable insights you will come across in your web analytics quest are a result of you saying, “Huh, that’s interesting.” Then you dig a little deeper, find some answers, and come up with a new way of doing things. It’s rare to be unsurprised by your findings when you’re digging through Google Analytics or Omniture SiteCatalyst or any other tool, because what you’re really looking for are things that you don’t expect.

Whether you’re a seasoned veteran or a complete newbie, you’re going to have to dig in and figure out what’s causing that drop in page views per session or conversion rate or video completion rate or whatever else you’re measuring, and it’s almost always going to be a learning experience. The conclusions and efficiencies that come from the seasoned veteran may be superior, but the newbie can definitely hold the fort, much more than we often give them credit for.

Here are some typical problem areas where you can take advantage of “easy” analytics to gain insights and improve your site:

• Landing pages with the highest bounce rates
• Landing pages with the lowest conversion rates
• Referrers with high bounce rates
• Referrers with low conversion rates
• Paid search: keywords with high CTR and low conversion (money fires)
• Natural search: top keywords for major landing pages (are we satisfying those searchers?)

So keep in mind when I say web analytics is easy, my standard is how sophisticated you need to be to drive performance-altering change on your web site. And you don’t need to be that sophisticated to pinpoint a basketful of site issues that need addressing.

But web analytics is hard!

Very hard, according to Eric Peterson. So, web analytics does have a dark side. It can be hard, but also not for the reasons you might expect.

Web analytics is not hard because you need a statistics degree. It’s not hard because you need to make some sort of model that looks like you’re trying to land something on the moon (or blow it up). It’s not hard because you have to be some Excel whiz or know how to run a multivariate test. It’s hard because people believe that analysts are automatically good when they embody these characteristics, which is completely untrue.

The best analysts are good communicators, not NASA engineers. In fact, engineers are usually the most frustrated and unsuccessful analysts out there (in the long run). While they’re trying to explain that the hypotenuse of a thermodynamic econometric assimilator is equal to the perennial habits of in-market visitor segment recency, the clear communicator is explaining that a shift in budget from paid search to an email campaign is expected to generate $2.6 million in incremental revenue. While the NASA analyst is trying to explain this:

… the articulate analyst is in the CFO’s office talking about the tech support and IT prioritizing savings driven by their investment in Tealeaf, in real dollar terms.

This isn’t to say that formulas like this (it looks like Pac Man, math edition) aren’t downright brilliant. They are. They’re just not universally useful in a business environment. They’re very potent research tools that should be used to make complicated data more malleable for the analyst, but they should never see the light of day in the rest of the organization. While the NASA analyst may think this formula will make him look smart and impressive, the executives just see another propellerhead that will waste time with technobabble. No matter how valuable this technobrilliance is, it’s always going to sound like Urkel to the CEO.

Web analytics is very hard, in essence, because we deal with very complex data sets, statistical analysis, trying to tie online and offline data together, seasonality, and more. It takes a very smart person to do this well, without making mistakes. But the most important—and hardest—thing to do is tie it all back to the two very simple metrics that drive all business value: revenue and profitability. This is the language of business, which is different from the language of the analyst. And while the NASA analyst may think these two basic elements of business oversimplified and unsophisticated, the entire history of business demonstrates that these are the only two things that matter.

Something else we can relate to

The same can be said of SEO, for example. Is SEO hard? No, of course not. You can spend an hour on this site and learn enough to make a huge difference. Is SEO easy? No, of course not. Even if you spend 100 hours on this site, you’ll still be making huge mistakes and missing out on nuances that can cost you valuable real estate in the search results. That’s why there are specialists. But don’t let specialists tell you that it’s so hard that you shouldn’t learn the basics and employ simple recommendations that can make a huge difference.

Our industry is rife with smart people who are on border patrol. We tend to get so caught up in how smart and sophisticated our ideas are, we push lay people out and purposefully alienate them with our big words and complicated explanations, telling ourselves that if a CEO doesn’t understand a simple chi-square test, he’s a dumbass. The truth is, we’re the dumbasses when we can’t reduce the outcomes of that test to simple, explainable tactics that will produce either a revenue increase or a cost reduction.

So if you’re the expert, make it simple for people. Make them comfortable. Don’t make it hard. If you’re the beginner, keep it simple, find clear opportunities, ask smart people for advice, and enjoy the ease of web analytics!

In my previous article, I shared a set of natural search metrics that help frame your natural search business opportunity and win the resources needed to improve your SEO performance. In this article, I’ll show how to use the first three metrics to begin building a kick-ass business case that your executives will find hard to resist. Before we proceed, just one word of advice from Obi-Wan, young Master Luke: Only use these metrics to sell (either internally or externally) if you have ability to deliver on what you’re selling.

Define the market opportunity

First, what’s the total size of market you’re chasing in natural search? Yeah, I see your blank stare. This number has to be your mission; it must be top of mind in order to successfully convince executives to invest in SEO. Think of this first metric as a basic marketing feasibility study. The SEO costs and tactics are irrelevant at this stage. Tell me how many people are searching for what you sell every month. What keywords do they use—besides your brand name. This exercise is different from traditional “keyword research.” We’re looking for an estimate of market demand.

To estimate keyword market demand, first look at the phrases currently driving traffic. Export (from your site analytics) all the non-brand phrases that drove natural search traffic over the last completed month. Augment this list with all your PPC phrases that outperform your average site conversion. You can further augment the list by running a spider over your site to extract onpage phrases that may be worth exploring, but this is a more advanced step and is probably counter-productive at this stage. (Trust me: your business case will be compelling enough by the time we’re done. Resist the temptation to inflate it into unrealistic fantasy data that will only hurt your credibility later.)

Historically the tools needed to conduct our feasibility study have simply been unavailable, or we were forced to make keyword research tools do a job they weren’t meant for. Thankfully, Google made its AdWords Keyword Tool, with demand data, accessible for advertisers over a year ago. Hopefully Yahoo and Bing will follow. For now, simply feed your keyword list into the AdWords tool over the comparable time frame. You can query using broad or exact match, but I’d suggest exact match to calculate more precisely how much of that market you penetrated.

A few caveats here: First, Google’s numbers are imperfect, but better than the alternatives. We find that Google will fail to report useful data for many long-tail keywords that have small demand. This is an issue since long-tail keywords are the essence of what big natural search programs are made of (another tool limitation, for the time-being). Second, we suspect the demand numbers Google reports are overstated by a factor of between 20% – 40%. So you can discount accordingly to keep a clean, consistent Google-only calculation through your business case.

At the end of this process, you want a spreadsheet with the number of keyword phrases and the demand of those markets, with a total market size that you are competing in, across natural and paid search. You have defined your market opportunity when you can confidently tell your executives something like this: “Our addressable market spans 200,000 different keyword markets, and totals roughly 5,000,000 searches per month.”

Estimate click through rate (CTR)

The next question asked will be, “But how much of that are we getting right now?” To answer this, determine what percentage of those markets your current keyword traffic represents. This is an easy and powerful calculation. You know what non-brand traffic you received from Google during the same time period (from your site analytics). Simply divide the market opportunity by actual traffic received for each keyword to determine your CTR for each keyword. You should calculate CTR on an individual keyword-level basis. For bottom-line purposes, calculate a weighted average of the individual keyword CTRs.

You have defined your CTR when you can now tell your executives something like this: “Our addressable market spans 200,000 unique keyword markets and totals roughly 5,000,000 searches per month, of which we’re currently capturing 1%.”

(Pause the movie a second. Did you catch what just happened? With just two metrics you now have the power to compare the efficacy and potential of natural search against other forms of online advertising using familiar performance metrics—without resorting to ineffective faith-based arguments or resource-begging. It gets better. Unpause…)

For added power, insert a column in your spreadsheet showing where your site ranks for each phrase (SERP page is fine for now). As you might expect, you’ll find that phrases for which you’re ranked on Page 1 of Google (here I’ll be using shorthand like P1, P2, etc.) will have a higher CTR than phrases for which you are ranked deeper. Now compare CTR on P1-ranked phrases against P2-ranked phrases, etc. Our retail clients find Google P1 consistently achieves CTR of around 10%, while P2 achieves around half the CTR (<5%). If you see similar values, the business proposition is crystal clear: There are performance gains to be had by investing in phrases ranked deeper than P1. We all know this instinctively, but now the data can do the talking for you. Note: There are tools that report on SERP rankings automatically. Or you can parse referral strings yourself on all engine traffic to capture what page of the SERPS the searcher clicked on to land on your page.

If you let it, the data can say something even more powerful. Once you quantify the performance difference between your P1 and P2 (and deeper) phrases, you can assign and model a budget value to achieving the desired lift across the desired markets—along with some probability assumptions. Don’t be surprised if that budget is much more than you’re budgeting for all your SEO efforts right now. You’ll recall my premise: your SEO is underperforming now for this very reason.

Map out traffic acquisition cost

Now for the trifecta: Knowing your addressable market size and current penetration, your executives want to know two things: How much are you spending on that performance now, and how much does “more” cost. You’re in the game. The costs of advertising via paid search continue to increase. The cost of advertising through natural search is dirt cheap. Your executives want to increase profit by acquiring more traffic (and sales) at less cost. Natural search is an obvious way to increase traffic, decrease costs and increase profit, right?

You can easily answer the “cost of more” question by exporting the average CPC value reported by Google’s AdWords Keyword Tool above. Simply add two columns to your spreadsheet, one to reflect a growth assumption on your current natural search traffic (50%, 100%, whatever), the other to estimate what it would cost to acquire that traffic using AdWords. Total it up. You’ve just created a reality-based framework for valuing natural search that executives will appreciate – even though it may total more than what you’re currently budgeting to spend on SEO.

Your message to the CFO now looks like this: “Our addressable market spans 200,000 unique keyword markets and totals roughly 5,000,000 searches per month, of which we’re capturing 1% currently. The cost of acquiring that traffic through PPC totals $1,000,000 per month.”

More can be said on this point in future installments. But notice that you’re no longer taking Quixotic approaches towards SEO. Instead you’re making a business proposition based on markets with known performance and that have real costs associated. Your data is doing the talking for you, and your CFO’s heart is warming up to you. Powerful, the force in you is, yes…

Next time I’ll discuss the remaining metrics that help measure incremental gains in performance.

Here’s an important question that many search marketers never think to ask:

Q. How many different types of website visitors do you have?
A. Two.

The answer is easier than you thought, right? We should qualify that statement: For the purpose of this test we can divide your users into two camps:

• Those who know your site (or business)
• The “newbies”

Newbies are users who have no prior knowledge of your site or indeed your business proposition. These people are immensely important to you—they are the ones you’ve spent so much time and money getting to your site. They are future loyal customers, the drivers of growth and prosperity and healthy looking ROI charts. But not if you lose them at first touch.

This is where those often quoted statistics about how many seconds you have to engage a user when they land on your site come into play. Whether the official figure be 2, 3, 5 or 0.5 seconds, we’re all united in the belief that it’s not long. We also all know that we need to do everything we can to keep these people on the site long enough to channel them towards behavior that both satisfies them and helps achieve our goals, turning them into customers.

Whether your site’s purpose is ecommerce, data capture, whitepaper download or something altogether different, it’s almost certain that there is some kind of action you want users to complete. Channelling as many of your prospects as possible to this action should be pretty high on your “list of stuff to do on the site.” First step, make sure you have some way of tracking these actions and that you know what your conversion rate is.

Segment & conquer

There are problems inherent in defining a “new” or “returning” visitor in all web analytics solutions. For that reason we use segmentation to refine the definition somewhat. Here we want to see site usage data for those users arriving at our site completely that have never visited previously. All they know is that they have just clicked on a link (be it paid or free), most likely from a search engine result page, and voila, here they are! With that in mind, the segment we create must exclude all users who we can reasonably assume have some experience of your website or prior knowledge of your business. For our website we can define this as anyone who fits (or doesn’t fit) these criteria:

For your site there may be more criteria. Take some time to get this right and make sure you really have excluded all unwanted traffic. For example: subdomains, or any strongly linked sister sites, email campaigns, etc.

As an exercise, this is a good intro to the immensely powerful “advanced segmentation” feature you’ll find in the top right of your dashboard in Google Analytics these days. If you’re running a different package, fear not: most web analytics solutions will allow you to segment traffic in some way.

Identify the right pages

Start by gaining an understanding of which site content is being accessed most frequently by our prospects. Apply the segment you just created to the “top landing pages” report. You might be surprised by what you see in the top landing pages report. We have seen many times that one page is optimized better for natural traffic while another is preferred for paid search traffic. Remember we’re talking about first impressions here so we’ll base this analysis on landing pages.

Once we know which page(s) they are, we can set about understanding two things:

• How these visitors are reaching the site
• What they are doing (or not doing) once they are on there

Answering these questions will help you to decide if this is good quality traffic that should intuitively be converting at a good rate. For example, are the sources either good quality and/or keywords highly relevant? If the answer is yes then this page is worth optimizing for conversions. If no, you can refine your segment to exclude these elements and re-evaluate.

Next, get an idea of how often users landing on those pages are converting. A good tip here is to add a landing page qualifier to your segment and duplicate the segment, one-per-page analyzed. To get a full picture, use a mixture of conversion rate, bounce rate, time on site and average page views to form this opinion. One of these metrics alone may not give a true picture. You may decide to weight it in favor of one or other metric depending on what is of value to your business. In most cases, goal conversion rate should be the focus here.

Analyze & theorize

To recap, you have segmented your traffic into newbies and old-hands; you’re focusing on the behavior of these newbies. Now you even know which pages they land on. Hopefully, you’ve worked out at what rate they are converting into customers and decided whether you think this is reasonable or not.

Now the hard part: being objective with your own website is truly a difficult thing. Putting yourself into the shoes of one of your new prospects doesn’t make this any easier. So have a stretch, make a cup of tea, crack your knuckles and, when you’re ready, load new prospect landing page number one. So, what is your first impression? Within 5 seconds can you identify and satisfy the answers to the kind of questions your new prospect is asking? For example:

• Do I know what this company does?
• Do I know what their price/quality proposition is?
• Have I identified that they have the right product/service/information for me?
• Most crucially: do I know what to do next? (Channelling towards the goal)

Be honest! You might have spent days crafting that synopsis of your professional life to give your site an air of authority. But does it answer the above questions? Your SEO-optimized homepage text might be great for search engines but does it really provide a succinct synopsis of what your business does? Likewise, another issue we’ve seen frequently is the confusion of different possible actions. Imagine a user is satisfied with the answer to the first three questions above. All they need now is a quick, easy way to proceed to the next step in the process. Does your website provide this for them? If you are dealing with internal sensibilities relating to the website design, this process will help you build a case for change.

Drive change

You should now be left with a few informed assumptions/hypotheses about your website. It’s good to hypothesize so long as you don’t confuse an assumption with an empirically proven truth.

Test these assumptions, prove or disprove your theories. Depending on what these are, you will test different things. Here are some common examples:

• Think your signup process may be too long? Cut the form short and observe conversion rate, ideally test side by side.
• Think your homepage may be too wordy? Create a B version and A/B test.
• Think the call to action isn’t clear enough? Add a clear call to action to the landing page

There are some great tools to help here. We’re big fans of the free Google Website Optimizer. There are plenty others out there. Use a program like this to test different versions of key elements in either an A/B or multivariate test.

Whatever testing you conduct, remember to be objective with the results. It’s also crucial to have the right measurements in place. Once you’ve made an improvement, it doesn’t have to stop there. Move on to another segment or another portion of your site, measure, hypothesize and test again.

A question often posed by marketers is, “What is the relative importance of different factors Google uses to determine quality score (QS)?”. Some of the factors mentioned on the AdWords blog are:

• Click through rate of the keyword and the matched ad
• Account history
• Landing page quality
• Keyword/Ad Group relevance

The question for an advertiser then becomes, “What factor should be the primary focus when trying to improve my quality score?.” The answer is overwhelmingly the click through rate (CTR).

For the analysis, we looked at several Google accounts and plotted quality score vs. CTR. A typical plot for a large account with 500,000+ keywords looked like this:

Several interesting patterns show up:

• Quality scores from 1 to 8 are very well explained by CTR. Notice how the linear regression (line fit) aligns so well with the observed pattern. The R squared of 72% of the trend is explained by CTR alone.
• There is a sudden jump at a quality score of 8.
• While CTR does not explain the jump between 9 and 10, there is a huge jump in CTR between 8 and the higher quality scores.

But there is more to it. Some quality scores appear more frequently than the others. We found in our analysis of millions of keywords that quality scores of 8 and 9 are very rare. Here is a typical example for a Google account. It appears that the quality scores of 8 and 9 are “transition” regions. While a linear trend explains the QS-CTR connection until the score of 7, keywords with QS of 9 and 10 require a very high quality score compare to the rest.

We found this pattern across the board, in all verticals.

The takeaway is that when looking to improve quality score, first seek to improve your CTRs. This will have the biggest impact, by far. Do not worry if you see very few keywords at a quality score of 8 or 9. These scores are rare and do not appear to have a direct connection with CTR related factors. There is not much you can do to get these scores. In fact, it likely has something to do with the way Google’s Quality Score algorithm works. Once you have the CTR piece of puzzle solved, work on the other factors (such as landing page quality, ad copy relevance and campaign structure) to improve your quality score. And don’t waste your time fretting about getting the highest score.

Did you know that there are a handful of simple reports you can check in Google Analytics to see if your search engine optimization guru (or Agency) is catching critical pieces of the SEO puzzle? Take quick a look to sniff out what might be missing in your SEO effort.

Uncovering technical SEO issues

Of course, the wise SEL audience needs no reminder of the importance of the technical side of SEO. If the engines can’t easily see your content and associate discrete content with discrete URLs, mama ain’t happy. Fortunately for us, there are reports in Google Analytics that can also be used to help you uncover these technical problems, and we’ll talk about a few of those today.

How to identify canonical issues. There is a report in Google Analytics called “Hostnames.” It’s found under the Visitors > Network Properties section. If you’re having trouble finding it, here’s a picture of where to find the Hostnames report.

What we’re looking for here is a very short list of names that represent the domains we always intended people to see. Here’s a screenshot from my blog; please bear with the shameless use of my own sites—my clients aren’t too keen on me showing off their information.

We like what we see here. Almost. I decided to get cute with the name in some links and capitalize it, so we see two domains here where we really should see just one. Big deal? Maybe not, but I’ll leave it to the pro SEOs to comment. Should I fix it? Probably.

Now, let’s look over at another site—this one’s up on cinder blocks and there’s a little trash in the yard:

This screenshot reveals a big problem: a canonical issue with a www site and a non-www site. I need to 301 redirect traffic requesting http://evanlapointe.com to http://www.evanlapointe.com (or the other way around—just pick one). The IP addresses we see in there aren’t an issue—they’re usually just Google’s IP addresses from when people view cached copies of the pages. If you see a lot in your own results, just take a look at them to make sure. That last result? Not good, either. I’m going to have to give my hosting service a call.

Another thing you might see here are staging servers (like dev.site.com) or mirrors (like server2.site.com). Double check to see if you can access those from the internet directly. If you can, use robots.txt or the appropriate meta tags to disallow the indexing of those pages while you figure out a way to put them behind some sort of protection—not only do the search engines like to take a gander at all of your content, your competitors might find out about your new features before you do if they’re able to check out your development site.

Dig up some duplicate content. Another technical SEO enemy is a single piece of content with more than one home. This can be a particularly big issue for sites publishing articles, displaying products using parameter-driven pages, or if your site is just a quilt of many developers’ efforts. While Google Analytics doesn’t make finding these issues as simple as identifying some other problems, here’s a quick routine I go through with our clients.

Under the Content section of Google Analytics, I’ll pick a dozen or so pages under the Content by Title report. This report gives me the same information as the Top Content report, but it aggregates against the title tag instead of URLs. Again, likely candidates are articles, products, category pages or anything a CMS generates dynamically.

When you click on a title in this report, you’ll see the URIs (URIs are the domain-less URLs seen in Google Analytics) this title tag represents. See more than one page? Not good. See more than 3 pages? Not only do you have potential duplicate content, you may be missing one of the most fundamental SEO tactics: picking unique and descriptive title tags for every page on your site. If this is you, do not pass Go, do not collect $200. You’re already on the right site. Read. A lot.

But if you only see 2 or 3 URIs here, it’s likely that the same page (content) has several homes (URLs). Often enough, SEOs will create “friendly” URLs (like http://www.site.com/sunglasses/polarized.html), and forget to 301 redirect the old URLs (ugly ones like http://www.site.com/products/category018/product.jsp?prodID=2265) to the new ones. Then the engines come across a link to the old URL somewhere on the internet and there you have it: duplicate content. Make sure to redirect the duplicate URLs to the canonical (”authority”) URL, and make sure you have unique title tags for each unique page of content.

Beware: SEO can skew analytics reports

The best SEOs realize that analytics reports may not always be accurate, but many do not: all of this redirecting can potentially cause some major integrity issues in Google Analytics, or any analytics tool for that matter. In some cases, redirects may strip off critical URL parameters (for tracking paid search or other marketing campaigns) or prevent the analytics tool from determining where a visitor came from (often reclassifying referral traffic as direct traffic), and this is obviously a huge problem for the SEO who is trying to prove the traffic lift that results from their efforts. If you are seeing decreases in traffic after redirects are put in place, run a few tests to make sure that these redirects are working properly.

I’ll take some time to cover more ways Google Analytics and other analytics tools can help with technical and linguistic SEO strategies in future posts, but like my best teachers, I’ll end with a good strike of the ruler across your knuckles. Don’t forget to tag your paid search campaigns so your analytics tool can tell the difference between paid and natural search. Google provides instructions on how to do this, as do the other tools you may be using, and not doing this means that you’re just going to be looking at search soup, making it much harder to prove the value of either program.

In the meantime, if you have questions about doing the above in other tools like Omniture SiteCatalyst or working through these exercises, feel free to comment below or reach out to me on twitter.

What a thrill it is to kick-off Search Engine Land’s new “Analyze This” column! I applaud SEL for creating space for this industry conversation. Those of you who’ve heard me speak at industry conferences (SMX, AdTech, ACCM, SES, Shop.org) know I believe there is a strong disconnect between the opportunity natural search practitioners see (or instinctively understand) and how organizations resource and value natural search. The primary cause is that natural search practitioners have lacked a proper metrics-based business framework with which to have more powerful business conversations. Lacking this framework, the natural search opportunity fails to convince executives (internal or external) to allocate needed resources. As a consequence, natural search performance suffers, and sadly, your contribution goes under-recognized in the eyes of the organization.

I hope to help. The development of more robust search metrics has been a passion for me over the past 8 years in the field and in working with premier online brands at Netconcepts. I love measuring things. Looking for patterns. Questioning. Concluding. Experimenting. Learning. Then doing it all over (and developing products that automate those processes). I very much view natural search as a form of direct marketing. One my professional aspirations is to help elevate natural search from that of “black art” to a genuine business discipline capable of producing sustainable results more predictably (OK, I have ambitious tendencies). And as my company and colleagues would attest, I am a firm believer in the old management truism “you can only successfully manage what you have successfully measured.”

So what I want to offer you in my regular contribution to this column is simply this: How to systematically improve your natural search performance. More specifically, how metrics can help you win the resources needed to grow your channel; how to calculate them; which metrics matter; how to shape them into powerful business conversations; how to evaluate the smorgasbord of SEO tactics available to you, and their effectiveness at driving performance for you. When your CEO knocks on your door demanding you double your search performance in 6 months, I want you to know how to assess the feasibility and requirements of achieving that objective—or at the very least, how to tell your CEO what is more attainable and why.

Let’s get started.

The natural search opportunity

Allow me to humor you with some industry facts:

• Search, as an industry, is growing from a $12B industry in 2007 to a $25B industry in 2011—100% growth in just 4 years (SEMPO)
• CPC costs are on the rise—Google’s average CPC rose 15% last year
• Consumers click on natural listings 85% of the time according to research (from Forrester)
• Meanwhile marketers spend 85% of their search budgets on paid search (according to Marketing Sherpa)
• 56% of Google queries have 0 paid ads placed (each of those queries present 10 “non-paid” or natural search results (or for the forward thinking, “ads”) on the results page) (according to comScore)

Clearly, natural search presents marketers with a much bigger pool of potential consumers—each of which can be acquired much more profitably than by any other means.

But as practitioners, how do we normally communicate this opportunity? Most search geeks (I mean that lovingly and inclusively) default to tactic talk and irrelevant metrics: begging for an hour of IT or copywriting or mechanizing to modify HTML elements on templates, H1 tags, page titles, or add links, or rewrite a URL or two. Then you get shot down because when pressed for “what’s it worth,” you start fumbling for something impressive to say (”um… thousands! Maybe millions” are gems I’ve heard over the years). And when that fails you resort to “leap-of-faith” arguments that CFO’s just don’t buy – or at least not for very much money. The standard SEO metrics you do share have no connection with business—you know what I mean. Things like PageRank flow, inbound links, keyword density, engine distribution, ego term rankings.

And that’s the nub of our issue. Winning the Darwinian resource struggle requires not that we lose our passion or faith in search, but that we realize it; and I am saying that we realize it by first talking business metrics before we talk implementation tactics.

Show me the money

Ultimately if we want resources allocated towards SEO work, we must be able to communicate the value of that work in return on investment (ROI) or return on ad spend (ROAS) language. That seems simple enough. Yet the reality of measuring natural search is complicated by the long-tail and distributed nature of natural search.

How do you define what is actually incremental traffic or sales? One month you get three visits for a long tail phrase. Next month you get just one. Did market demand decrease? Or did your rankings decrease? Or did both stay constant while other SERP page competition stole your traffic? And practically speaking, how can you possibly care about such small volumes? You don’t worry about the height or width of each blade of grass in your lawn (I hope). Yet successful search channels are comprised of just that: hundreds of thousands (or millions) of non-brand phrases each acquiring handfuls of searchers every month for various pages of your website.

In addition to the scale issue, many factors impact natural search performance, and many stakeholders are likely influencing what the engines are seeing and responding to. Can you correlate gains or losses to specific site changes? Or is your performance driven by an invisible hand of unnoticeable activities—perhaps the combined effort of user interface enhancements and keyword-rich copywriting tempered by new AJAX navigation schemes, all of which may have been deployed at various times over the past quarter or year. It’s complicated!

So our challenge is this: not only must we speak in ROI/ROAS business language, but we must also understand what’s driving performance currently, what the level of effort put forth has been, and communicate how we expect actions to contribute towards that positive ROI/ROAS we see.

That said, here is a framework of progressive metrics we have developed that take many of these factors into account in order to drive a stronger natural search business conversation:

• Market opportunity
• Clickthrough rate
• Traffic acquisition cost
• Keyword coverage
• Non-brand reach
• Landing page placement
• Landing page yield
• Incremental traffic / revenue
• Return on investment / return on ad spend

In my next few installments, I will walk through each metric, how we derive them, their relationship to each other, and how to use them in a practical manner.

Our newest Search Engine Land column, Analyze This, launches today. Analyze This focuses on analytics and measurement, two crucial aspects of search marketing that are often overlooked or underused. Columnists write about measurement techniques, compare analytics software programs, discuss strategies for using data to improve results and more. The Analyze This column appears weekly at Search Engine Land.

In today’s debut post, Brian Klais explores some of the reasons the work you’re doing may be underappreciated, and what you can do to shift negative perceptions into a more avorable light. Read on in Why Your SEO Is Underperforming – And You Are Underpaid.