Excerpts from my latest article at Practical eCommerce: “Google’s Secure Search Squeezes SEO Planning and Reporting.”

Google’s secure SSL search protects users’ search results and the keywords they searched on. Unfortunately, it also poses a growing threat to data-driven search engine optimization. Firefox recently joined Google Chrome — and Google.com, for logged-in users — in defaulting to secure search. This has the side effect of increasing the number of “Not Available” or “Not Provided” search keywords in web analytics reports.

In the past, SSL search was too slow and cumbersome to use as a default. Web analytics programs could easily pick out most of the keywords that referred traffic to the site from Google.com. Today, with SSL search the default on Google.com for logged in users as well as the default on Chrome and Firefox browsers, a growing number of Google.com referral strings are coming into web analytics with no keyword information associated. Consequently, if a site optimizes a page for a certain keyword phrase, its ability to measure how many organic searches were referred from Google via that keyword phrase is diminished.

In 2011, Google reported that it handled 143.5 billion searches a month. Google represents 66.4 percent of the search engine market share, according to comScore’s February 2012 report. The Chrome and Firefox browsers together represent 39.8 percent of the browser market share, according to Net Market Share’s February 2012 reporting. Consequently, 26.4 percent — 66.4 x 39.8 — of all searches last month were conducted on Google in Chrome or Firefox. If this trend holds, 26.4 percent of all searches going forward will be stripped of their keyword data. And this doesn’t include the searches conducted by users logged in to Google properties and searching Google from any web browser.

Read the article in full at Practical eCommerce »

I discussed keyword research and keyword mapping in detail in the previous two articles in this series on content optimization. But keyword research is like any form of data collection and analysis: It won’t drive a single additional organic search visit or sale until it’s acted upon. With their keyword maps firmly in hand, content creators and search marketers can effectively and efficiently create or optimize content that turns those potentially valuable keywords into real search-engine-optimization traffic.

It’s obvious when content is written for search engines instead of customers. It tends to focus on high keyword density — having a higher ratio of keywords to other words — and tends to lack readability and interest. Instead of this, inform writers of the keyword theme for the page and let them write freely and creatively with the keywords and the brand messaging in mind. When they’re finished writing, go back over the fresh copy with an eye to replacing some phrases with keyword phrases. Be careful not to kill the spirit of the content in the process.

Where keywords are placed can have a big impact on how strong a keyword relevance signal they send to the search engines. This is referred to as “keyword prominence.” If a page is meant to rank for “online games for girls” but the keywords related to that phrase aren’t used on the page in prominent places, it will have a difficult time ranking. So before we start flinging words around the page, keep these content optimization guidelines in mind.

Read more of this article on Content Optimization»

The Complete Series: “Optimizing a Page for Search Engines”

• Part 1: Keyword Research
• Part 2: Keyword Mapping
• Part 3: Keywords to Content
• Bonus: Title Tag Optimization for Ecommerce Sites

Keyword research is essential to search engine optimization. It’s the window into the words that real searchers use to find products like the ones you sell. But at the end of the keyword research process — detailed in “Part 1: Keyword Research” — search marketers can be overwhelmed by the vast amount of data staring at them from their Excel spreadsheets. Keyword categorizing and mapping help move the optimization process from the research phase to the actual optimization phase.

Categorizing Keywords

During the keyword research process, patterns start to appear. Different types of keywords emerge that can be logically grouped into different categories that reflect the site’s business goals and core product offerings. For example, if my site sells subscriptions to online games for kids, my keyword research could be 12,000 phrases or more based on the research conducted in Google’s free Keyword Tool. But because each keyword is needs to be related to my core product offering, I can start to categorize them and delete the ones that aren’t directly relevant.

Let’s say that my site sells games. But it doesn’t sell just any games; it sells online games for kids. That’s three vital components to choosing keywords that are specifically targeted to my product offering: “types of games,” “online vs. offline,” and synonyms for the word “kids,” as listed in the spreadsheet, below.

See the diagrams and read more on how to categorize & map keywords »

In its purest form, optimizing content for search engines consists of modifying one page to send a strong keyword signal for one keyword or phrase. The amazing simplicity of this concept is often lost on marketers, many of whom think of content optimization like taking aspirin: If two is good then four must work even better. Sprinkling lots of keywords on the same page will not improve organic search rankings, nor will using the same keyword on lots of different pages. The key to content optimization for SEO is matching one keyword to one page in a methodical and disciplined manner. Scalable methods of optimization become necessary if the site is very large, but even the largest sites still “manually” optimize a selection of critical pages by matching one keyword to one page.

Choosing the Best Keywords

Before keywords can be matched to pages, the optimizer must know which keywords to choose. Make a seed list of the words that will be used on the page. Think of as many synonyms as possible and record them in a Word doc or Excel spreadsheet. Be warned, these are not the keywords with which you’ll be optimizing. The brainstorming process is only the start of the keyword research process. Optimizing with a seed list will result in content optimized for the way you think and search, not the way your customers do.

Read more »

Optimizing title tags is a bit like eating your vegetables. No one wants to do it, but everyone knows it’s good for you. Search engine optimization professionals universally agree that title tags are the most influential on-page element. SEOmoz recently confirmed the importance of title tags in a report that strongly correlated title tag optimization to higher rankings.

The guidelines for optimizing title tags are simple, but that doesn’t mean it’s easy. Begin the tag with the most valuable and relevant keyword phrase, use the exact keyword phrase, end with the brand, and keep the length to 70 characters or less.

Read more about the finer points of optimizing title tags »

By high-volume keyword research I mean identifying related keywords for thousands of known phrases, which while fantstically tedious is also quite useful for finding new keyword markets to optimize for.  For example, within five minutes of reading Baxter’s post on SEOgadget and downloading the plug-in, I was happily fetching keyword ideas for 46,000 phrases. Why 46,000? Well, I had a list of 200 cities, 150 topics and 4 different phrasings for each combination of city and topic. Adds up quickly does’t it? Thank god for MergeWords. But back to the AdWords API plug-in.

I quickly discovered that I had to run the queries in batches af about 5,000 phrases each or my poor PC would bog down horribly. Still, I was able to accomplish in 3 days what would have taken me 3 weeks. Three tedious, mind-numbing weeks of copy/paste/search/download/repeat. I was so excited that I immediately blogged, tweeted, +’d and shared Baxter’s post everywhere I could.

Then I discovered I had a new problem. My API queries had resulted in a combined 15 million keyword ideas. Many of these are duplicates — as many as 75-90%. And many are not relevant to the specific need I’m researching, despite their relevance in Google’s algorithmic eyes. SEOs are no strangers to scrubbing data, but how do you scrub 15 million keywords? How do you use Excel’s handy “remove duplicates” feature on 15 million keywords when Excel’s maximum rows per file is a little over one million? And that’s assuming you can get the individual keywords to march tidily into a single column for deduping in the first place. Which I couldn’t.

The AdWords API plug-in spits the keyword ideas out in a single cell with each related keyword separated by a comma. Naturally, since I’m a data hog, I wanted all 800 related keyword ideas the Google AdWords Keyword Tool was willing to give me. That’s 800 comma-separated phrases crammed into a single cell. It’s easy enough to separate those into unique cells so that you have one keyword per cell, but you still can’t dedupe 15 million cells in Excel without some external help.

Enter the DigDB plug-in for Excel. It slices, dices and juliennes data quickly and efficiently in lots of different ways. DigDB took my 15 million keyword phrases in their individual 15 million cells, extracted every unique phrase, and lined them up in a tidy column on a new worksheet in Excel. It did it quickly, without complaining and without freezing every speck of my PC’s memory. Just to be safe, I ran the extraction process 15 times on 1 million keywords each. Each extraction took about 7-10 minutes.

The download site offers tens of practical examples for using the plug-in, each with a sample spreadsheet so you can try it out to be sure that the description matches what you actually need to do. It costs $78 a year, but there’s a free 15-day trial so you can kick the tires. $78 seems like a lot to me, but on this one project alone using one feature of the tool I saved maybe 40 man hours. I’d say that’s worth the price if you plan on doing large volumes of keyword research.

Today’s As Seen on GKT: [clothing optional hotels palm springs]

My favorite aspects of this phrase:

1. Clothing optional, not nudist. As if these searchers are either uncertain that they want to commit to full nudity, or recognize that perhaps there are some situations in which nudity is not preferable. Or perhaps one member of the party prefers to be nude and the other prefers to remain clothed. OR perhaps the searcher wishes to remain clothed but likes to be among nude people. So many interesting reasons why someone might prefer the optional option.
2. Palm Springs is a frequently searched destination for those who prefer optional clothing. It’s sunny and warm year ’round, so that makes sense. But Palm Springs is in the desert, known for its intense rays. I’m hoping their lack of packed clothing leaves lots of room for sunscreen. In case you’re wondering, other popularly searched options include Key West and the Caribbean.

Let’s say I have downloaded 3 .csv files (file-A.csv, file-B.csv and file-C.csv) and I want to quickly merge them.

Simply open the command line by typing the word “run” into your Windows Start Menu, or execute the cmd.exe file at C:WindowsSystem32cmd.exe. A black window will open like a portal into 1985.

Next, direct the command line to the directory that contains the individual .csv files you want to merge. The command line begins in the C:WindowsSystem32 directory. I keep an empty folder at C:merge for this purpose so I don’t accidentally merge other files. So all I need to do is type “CD merge” to ask the command line to kindly switch to my C:merge directory.

Next, the copying. Type “copy *.csv merged.csv” to copy all .csv files in that directory into a single file called “merged.csv.” You can call the file anything you want: Actually, I usually call it “1.csv” instead of “merged.csv” because it’s fast.

Windows Command Line

And you’re done. Open C:mergemerged.csv, dedupe it and you’re ready to filter out the wheat from the chaff. Enjoy!

A hot tip from my cool friend Don Schantz:

Another handy tip to go with this is that if your files are in another folder with a long path name, you can drag the folder name from your Explorer address bar directly into the command prompt window after typing cd , and it will fill it in with the necessary quotes. Yes, drag and drop into a DOS command line.

Google AdWords quietly updated its Keyword Tool on Sept. 7, resulting a dizzying drop of up to 95% in search counts for some phrases. For those who rely heavily on the keyword tool to predict potential SEO performance increases or to identify phrases to optimize for, this update will come as a heavy blow. Details are sketchy from Google, and the SEO community has been silent on the issue except for Dave Naylor and a few folks in the forums. So what happened?

“If you use both the previous and updated versions of the Keyword Tool to search for keywords, you may notice differences between the tools for statistics on Global Monthly Searches and Local Monthly Searches. This is because the previous version of the Keyword Tool provides search statistics based on Google.com search traffic and traffic from search partners, while the updated version of the Keyword Tool provides search statistics based on Google.com traffic only.  We’ve updated these statistics based on user feedback, and hope you find them helpful for keyword selection.” >> from AdWordsPro on the AdWords Help Forum

The Search Network: Your ads may appear alongside or above search results, as part of a results page as a user navigates through a site’s directory, or on other relevant search pages. Our global Search Network includes Google Maps, Google Product Search and Google Groups along with entities such as Virgin Media and Amazon.com. >> from AdWords Help

OK, so previously the data was based on an aggregation of Google.com searches and traffic from search partners like Amazon and Virgin Media. But since the Sept. 7, the data is based solely on Google.com searches. Am I the only one who would have found that incredibly helpful to know before now that a data source as large as Amazon’s was skewing the data in the Google keyword tool?

Yes, we all knew/theorized/suspected that the AdWords keyword tool data was skewed. And given the source (Google) and the purpose of the tool (get advertisers to pay for ads on keywords) we took it with a grain of salt. But seriously, 95% inflation is a very, very big grain of salt.

If you don’t already, this is a wake up call to diversify your SEO data sources and understand that most public SEO data is relative rather than exact. First, diversification. Try using more than one data source for keyword data. There are a lot of tools out there, but these are the old stand-bys: WordTracker, Keyword Discovery, SEO Book’s tool. Keep in mind the source of each tool’s data — they either use the APIs from the engines themselves or toolbar & ISP data, which renders each pretty much as reliable as the Google keyword tool anyway.

Which brings us to relativity. Get used to the reality that you will never know the exact number of searches that occur for any given keyword or phrase. Public keyword data and search frequency data are imprecise. The only data you can be certain of in SEO is the data that comes from your own log files on your own site. All other data is approximate. If you base projections on approximations, be certain that you take into account the squidginess of the data sources.

In this update, the biggest differences between pre and post appear to be on the larger, more competitive head terms, both in this sample and in the analysis I’ve been doing over my own keyword sets. Here’s an example. Let’s pretend we’re researching keywords for a site that offers hotel reservations. I might target sampling of keywords like these.

Click to view larger. Data source: Google AdWords Keyword Tool, Exact Match, US English.

Had I taken the Google AdWords Keyword Tool at face value, I would expect there to be a US English keyword market of 450,000 searches for the phrase [san francisco hotels]. I might choose project to win 10% of those searches and figure a conversion rate of 5% based on my analytics. Each conversion might bring me say $10, so I might project a value of (((450,000 * 10%) *5%) *$10) = $22,500 in a month.

Unfortunately, the updated number based on true Google.com searches, according to the tool in September, is 95% lower at 33,100. So now we’re looking at (((33,100 * 10%) *5%) *$10) = $1,655 in a month. Not bad for a single keyword in a single month, but much lower than the previous projection and it comes with hefty competition.

For a detailed description on safer ways to project, see SEOmoz’s post: Predicting Yearly Site Traffic.

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Think what an optimization campaign around [location] + [charity gifts] or [christmas donations] could do for a local charity. Say a seasonal program attracts 100 volunteers — what if SEO could attract 20% more? I’ve reached out to help my favorite charity optimize for next year since this year is essentially a wash for holiday optimization. Next year, look for http://www.mompop.org at the top of the SERPs for [madison charity gifts]!

I finally stumbled on MOM (Middleton Outreach Ministry), a local charity serving the western part of Madison, WI. Like many charities, MOM is a local operation staffed by hard-working volunteers and a few employees that wear too many hats to focus on online marketing. Even the national or global charities tend to lack strong SEO savvy. What would they optimize for? Keyword research would light the way, of course.

I did some quickie keyword research to find the optimal annualized keyword phrase for holiday and Christmas donation gifts. The keyword market isn’t huge, and the data for Madison-based phrases is even tinier since we’re not a major metro area. In the end I had to settle for non-location-specific keyword phrases, logically prepended with location. Here’s what I came up with:

The tricky thing with keyword research is intent. When folks search for [charitable gifts] they may be looking for general charities to donate to as opposed to the intent I had in my search, giving holiday gifts through a charity. The non-holiday keywords are incredibly valuable, of course, but will probably be utilized at the top of the site’s hierarchy. [Christmas donations], [holiday giving], [holiday charities] and [charity christmas gifts] are more on target for the seasonal holiday charity campaign’s landing page.

So let’s look at an example. MOM’s Madison Christmas donations page appears to target the program’s name: Sharing Christmas Program. That’s handy for folks who saw another form of marketing and already know the program exists, but it’s not going to get them a lot of natural search-referred traffic or donations.

While the page mentions some of the optimal individual words, none of the valuable phrases are incorporated together. Here’s what I would do for the Title Tag: Christmas Donations: Madison Charity Christmas Gifts & Holiday Charitable Gift Giving

That one string targets my primary phrase of [christmas donations] and touches six secondary keyword phrases either by exact match or with another word interrupting the exact phrase:

• [charity gifts]
• [donation gifts]
• [charitable gift giving]
• [holiday giving]
• [charity christmas gifts]
• [charity christmas gift]

In addition, the heading, body copy and meta description should be optimized for the primary and secondary keywords. The best I can do for them for this year’s holiday giving season is give a link, but next year we’ll be ready with optimization a-blazing!

Learn more about Madison charity MOM, volunteer or donate, or visit their blog or Facebook page.

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Thanks for sharing.