Google has modified the tool over time, and one of the great additions was the ability to see the monthly demand via a small little bar chart. This can be very useful for factoring in seasonality or growing demand for certain phrases. Wrapping your head around the actual numerical data is a bit more challenging. The Local number is just for the most recent month while the Global number is a monthly average. This is further complicated in that the Global number includes the world essentially while the Local number may factor in your campaign settings and locality (based on your AdWords campaign configuration).

To help tighten up data and provide a little more insight into the Local numbers, I just released an Excel spreadsheet that can take your Google Keyword Tool’s export and annualize the Local demand numbers. In some cases, this may dramatically change the order of importance of keywords to target.

Best of all, this tool is free to use so give it a play. The link below will take you to the download page for the tool as well as more detail about how it works and an example.

Google Keyword Tool Annualizer

Yet, a great many sites continue to miss this vital key to relevance, and they wonder why they fail at ranking for their most apropos keywords. Keywords for which they’d otherwise have a very good chance at ranking upon!

W3C calls the TITLE the “most important element of a quality web page”

Yesterday I reviewed another major retailer website which had their brandname embedded in their page titles — and nothing else. Thousands of product pages all had identical TITLEs! This company could’ve had top three rankings on a great many competitive keyword phrases had they only customized their TITLE tags very slightly.

The W3C calls the <TITLE> tag “the most important element of a quality Web page.” Google has apparently paid attention to that, and all of the search engines have placed especial weighting upon the words found within page titles when evaluating the topics for which a webpage is associated.

It makes sense, when you think about it. A title should be a super-concentrated blurb that tells a user what a page is all about. In search engines, the title is often also displayed as the link text for each of the pages listed in the search engine results page listings. Informative titles appearing in SERP listings will get clicked upon more as users are reassured that the page they’re clicking upon is what they’re actually seeking. A page with an informative title will get clicked upon far more likely than a vague or unrelated page title.

I heard Googler Amanda Camp once mention that she’d recommended to a friend of hers to customized a page title, focusing it upon the main topic keywords for the webpage, and it immediately began ranking in the very first position for the keyword phrase.

And, I’ve seen it many times myself — engineer a good, simple, appropriate, keyword-rich title tag, and your page can  zoom its way above all the other nonoptimal page listings for the very same term.

As he mentioned, I’d previously listed this idea in my somewhat tongue-in-cheek post on “Extreme Local Search Optimization Tactics” some time back.

While my Tactics were intended to be a bit over-the-top, the tactic is indeed likely to work to varying degrees in different search engines and internet yellow pages directories, as Mike outlines. I should note that I only endorse the engineering of business names for purposes of branding and for purposes of targeting business-category/product/service terms for which the company involved is actually providing.

I’m not big on throwing away a brandname completely, even if it contains no good keywords — I’m more in favor of adding keywords to the existing business name in a meaningful way. For example, a business named “Xymax Corp” might rename themselves to include their product name: “Xymax Corp Rubber Seals”. This would be good for the business, good for the consumer, and therefor good for the search engine, too.

As Mike aptly outlines, there are a number of other considerations beyond just optimizing for search, such as creating a beneficial image to the company, and building towards longterm customer retention. If you used too fly-by-night a sounding business name, you could expect fewer clickthroughs per search rates than if you used more conservative, reassuring names. So, it would be easy to damage your performance to some degree by mucking this up — you could increase the amount of times your business listing comes up in searches, but simultaneously decrease your click-through-rates.

Mike further states that one should approach business renaming with great care, and I wholeheartedly agree. If you’re not a professional in local search optimization, you might just shoot yourself in the foot. But, with thoughtful deliberation on the multiple factors involved, doing a rename to add in some valuable keyword(s) could improve your referral rates from search engines.

Read on for more details about the AMA Hot Topic Series day’s sessions.

Here are some pictures I snapped of each of the speakers (except for moi):

Stephan Spencer

Stephan Spencer, opened the day, speaking on “Inside the Head of the Searcher”, and he also later spoke on “Link Building Your Way to the Top of the Rankings”

Alan Rimm-Kaufman

Dr. Alan Rimm-Kaufman spoke on management of paid search programs in “You Gotta Pay to Play – Winning at Pay-Per-Click Search” – Alan went into a number of the complex and constantly-evolving issues which can impact paid programs. (Alan’s blog may be found at www.rimmkaufman.com/rkgblog)

(not pictured: Chris Silver Smith)

I spoke on “Organic Search is All About Content” which went over basic Search Engine Optimization tactics.

Amanda Camp

Amanda Camp from Google’s Webmaster Tools, spoke on “The Straight Scoop from Google”, which went into basics of how Google crawls and indexes pages, their strong tools they provide to webmasters, and some approaches which Google frowns upon.

Gene Chan

Gene Chan from HP spoke on “It’s All About the Bottom Line – Measuring Search Marketing with the Long Tail”, using real-world examples from HP’s best-in-class paid search campaigns.

Neil Patel

Neil Patel of Advantage Consulting Services spoke on “Social Media Marketing – Leveraging Online Communities to Create Links and Buzz”. Neil is expert on integrating with these Web 2.0 or Social Media sites like MySpace, Digg, and StumbleUpon, so this is probably some of the most cutting-edge stuff in this Hot Topic workshop day!

This AMA Hot Topic seminar day will be happening again in New York in May, and Chicago in June – so, sign up now if you’re interested in attending one of these sessions!

Finally, as promised, here is the link to my “Content is the basis of SEO” presentation from the day, if you have the patience to download a 8.4 mb file!

One is always a little cautious about postulating grand theories into the wide world. But after studying over 1 million unique unbranded keywords across 25 major retailer search programs, we couldn’t resist – referring to the concept we outline as “Page Yield Theory.” This is an underpinning notion that the “long tail” of unbranded search keyword traffic is inextricably linked to the website’s number of uniquely indexable site pages. To those of us who subscribe to the “every-page-should-sing-its-own-song” philosophy, that seems like an obvious statement.

Yet the challenge behind it, and the impetus for the research, arose from the fact that many (unoptimized) well-branded multichannel retailers have 10′s/100′s of thousands of unique and indexed website pages. However most of their natural search traffic (usually over 90%) comes from searches related to their own company name. How could such strong brands and massive websites produce such little traffic for generic terms, terms other than the company name?

Big deal you say — it’s all relative, Brian. Big brands are supposed to have lots of brand searches. Yeah, I know. But here’s my riddle – why do the vast majority (usually over 95%) of those thousands of pages also yield no natural search traffic? What’s the connection?

What we find is that big brand retail sites happen to be laden with freeloader pages: sales people on the payroll, not earning their keep (worse – not willing to make a cold call. Even more worse – not given a phone or a list to make the cold call.)

So “Page Yield Theory” is our humble attempt to frame the correlation of these two phenomenon – suggesting that a small # of unbranded term traffic is a predictable indicator that a large website also has a small # of unique pages yielding search traffic. And vice versa – large amounts of unbranded traffic is caused by an increasing number of unique pages yielding search traffic. Some readers may have no idea how many pages are yielding traffic. No worries – based on the data, we provide a matrix that models these connections, based on the known mix of brand and non-brand natural traffic experienced in an average month.

So what of it? I think this “theory” raises important questions, and maybe a few creative ideas, for managers of large dynamic websites, around how to optimize for the long tail of unbranded keyword traffic. The scale involved practically demands that traditional SEO approaches evolve overnight into more of a “yield management” discipline featuring KPIs, robust reporting platforms, and testable strategies.

I can hear some screaming – but wait! Science? Reporting? Testing? Brian, I thought SEO was more art than science?

Ok, you’ll just have to read the story.

Brian

Most of the major SEOs and top companies keep such figures as closely-guarded secrets. Even the search engines keep the numbers of searches by various keywords secret, using various techniques to hide actual values.

The much-touted Eye Tracking Study conducted by Enquiro and Did-It show that the first listings on Google SERPs are looked at and clicked upon the most by users. Most pros already concluded this through common sense, but it’s difficult to get actual traffic amounts associated with the rankings of listings on SERPs.

I’m going to change this situation right here, right now, thanks to new data that Google has graciously begun providing to the public, and thanks to a brief reshuffling of rankings on a top keyword for one of the sites that I manage. Read on, and I’ll elaborate.

Recently, Google had a sudden and inexplicable reshuffling of keyword rankings for one of the most hotly-contested keyword terms on the internet, and this seemingly-arbitrary reshuffling affected one of the sites that I manage. Now, due to my work I have to play the boring old “proprietary information” card just like everyone else, so I cannot reveal the site nor the precise keyword that was affected. Suffice it to say, though, that some companies have paid literally millions of dollars in an attempt to gain first ranking for this key term, and suffice it to say that my longterm work has helped to keep our site in the first position for this term since at least the year 2000. (We optimize on millions of keyword combinations, and come up first on a great many of those, so I’m not revealing any proprietary information here.)

Even though I can’t reveal all those “proprietary” specifics, I can give enough specific info to make this very interesting, and I can reveal traffic specifics about some top keywords that have been hitherto Secrets held by various companies.

For a couple of days, our rank on the hotly-contested term suddenly dropped to second slot across most Google data centers. Nothing major was changed on our site/environment nor on the site that popped up to the first slot, and our analysis showed no clear reason for the sudden shift. We thought it could be that Google tweaked some thresholds on the various factors they use in rankings. The change was inexplicable, because it seemed very unlikely that the competitor site could be considered more relevant for the keyword, compared with our site, for a variety of reasons.

After a couple of unhappy days of obsessive checking for SEO mistakes or other environmental issues, the rankings started reverting back to their former order, and it seemed clear that there was some sort of odd and temporary mistake which took some days of processing in Google before the rankings for these sites and this keyword returned to their previous equilibrium.

Now the downside of seemingly-arbitrary reshufflings is that you may lose some traffic. The cool side of it is that it provided very interesting metrics to compare with the historical data.

For the sake of convenience, let’s refer to the keyword in question as Term X.

I can tell you that our site receives approximately 30k of visits on average per day from Google, just from keyword searches for Term X. There’s typically one or two Sponsored Links just above us on the SERP, and a few Sponsored Links on the right side column, too.

When we dropped to second slot on the SERP for Term X, we lost approx 18k of visits per day. So, there it is: the difference between the number one slot and the number two slot for a major keyword term comes to about a 60 % change in visits!

Now, to make this even more interesting, we can now relate this data about a keyword that we do know Google referral traffic for, with some keywords for which we don’t have direct data. This can be done by comparing search traffic for terms using the recently-launched Google Trends interface.

By submitting a few keyword terms to Google trends, separated by commas, Google will return back a graph which shows the amount of searches over time for each of the keywords. If you know how much traffic is produced by one keyword term, and then find some other keyword terms which have histograms which are near to it on Google Trends, you can deduce that their search traffic in Google is very similar, and you can further deduce that their clickthrough values for sites which share the same keyword rank slots on the SERPs will be closely similar to your known value as well.

For example, I found that the keywords “restaurants”, “nyc”, “miami”, “seattle”, and “television” all have histograms that are very close to my Term X during 2006:

Because I know how much traffic I receive from Google on Term X, I now have a very, very good idea of how much referral traffic may be associated with the top slots for Restaurants, NYC, Miami, Seattle, and Television! Occupying the top position for each of those keywords likely would bring a site about 30k in visits!

It’d be nice if Google would actually spell out the units for the vertical dimension on their Trends graphs, to make this utility even more useful. But, we can achieve the next best thing through deduction and interpolation.

Now, how do you estimate the referral traffic for a keyword which has a significantly different vertical value on the Google Trends graphs, from your known keyword value? We can’t immediately assume that the pale gray bands on the vertical dimension are consistent units, since Google likes to obfuscate actual values. (For example, Google doesn’t display actual search values for their Zeitgeist comparison of popular search terms, nor do they show actual numbers of searches in their advertising estimation tools. And, they also don’t tell actual PageRank values for sites.) Just as with the PageRank indicator in the Google Toolbar, it’s possible that their Trends graphs are made on a logarithmic scale. They aim to just show us vague, quantitative values for the volume of searches by keywords.

I don’t know why they insist on obfuscation when it becomes easily possible for us to estimate some true values with the data provided, as I’ve demonstrated. (This reminds me of how the US Government used to block one of the three values provided by the GPS satellites in order to make it harder for terrorists to target missiles. Yet, a few researchers demonstrated that it was no hard work to triangulate the coordinate data from a few different satellites in order to estimate the blocked values with fairly good accuracy.)

All we need to do now is to compare referral data from a few different keywords with significantly different vertical trend lines. That would give us enough data to estimate the vertical units of the graph scales. (I know I’m assuming a lot here — after all, they dynamically change the vertical scales according to the quantity of searches for different queries submitted to Google Trends. And, I’m assuming that referral traffic would be similar for the top keyword position for various different terms. But, once you know the vertical scale for a particular term, you can easily figure out how to resize the scale when comparing with other keywords, and it’s not unreasonable to figure that referral traffic for the top position sites may be fairly consistent, regardless of the keywords, based on the results from the Eye Tracking Study.)

I know a few nomographic tricks from back when I was a scientific illustrator, and compared with some conversion work I did for AASHTO engineering guides used by highway engineers, this should be a walk in a park!

We may still not know the raw number of searches on Google for particular keywords, but we will be able to accurately estimate how much referral traffic can go to a site if they occupy the top one or two positions on the SERP. And that’s what we mainly want to have, isn’t it? A good way of estimating traffic for different keywords and ranking positions, right?

Stay tuned, because I’ll likely have sufficient data to match up a vertical scale for those trend graphs after I have a chance to properly analyze them.

Following on the Q4 2005 holiday season, the drop in bids was not surprising given the seasonal nature of advertising.

Overall, the average bid has increased 1.4 percent since the September 2004 inception of the KPI when the average bid was $1.37. Although prices often vary dramatically day to day, average bid prices have settled in to a predictable range.

“Search marketing is growing at a robust 25 percent this year, and price stability helps that growth� said Matt McMahon, VP Marketing Services at Fathom.

What a gift it would be to possess photographic “peripheral memory”. Imagine being able to “remember” and explore conversations in full detail that you weren’t actually paying attention to when they occured.

Welcome to desktop search — Google desktop search, in particular. This will be a game changer for natural search optimization. For retailers, desktop search means all of a sudden, you’re playing the search game – whether by purpose or by accident.

With Google Desktop installed, any web page that your visitors have accessed, or any email they have received in their Outlook inbox (or web-based email clients like Hotmail or Yahoo mail), is now fodder for ANY future Google search they do. More importantly, those pages are given top-position on the page for keyword matches that may be – and this is the critical point – completely unrelated to what the customer was looking for when they originally visited that web page. Forget photographic memory. Peripheral memory is here.

For Google desktop users, this means that whether you intend it or not, your site and emails are already “indexed” for them by virtue of their viewing those pages. This provides the unfair advantage, the ultimate shortcut to the top of the Google results pile. No site restructuring or bloody IT battles. Just leveraging your existing customer traffic! Your mission is to make sure your copy, links, headings and titles are appropriately keyworded, in order to show up as more relevant than the OTHER sites that are in Google Desktop’s cache.

Adoption is still low. But as it grows Google Desktop (and other desktop search engines), raise the stakes for search engine optimization to keep drawing traffic. It will affect not only your web site, but your email campaigns which will also need to be carefully constructed to target the right keywords. This will enable retailers to extend the shelf life of campaigns and maximize repeat-traffic potential of existing customer visitors for months after they have forgotten about you.

Customers have better things to do than think about you all day long. Google desktop helps them “remember” things about you — things that they never even knew.

However, I have to say after using it, I’m not real impressed. The main problem I have with it is that I just don’t find their data to be believable. Too many discrepencies, too many gaps. Let me show you some specifics…

For starters, witness a huge spike in searches for “Christmas shopping” mid-year. Then it’s relatively flat during the Christmas buying season?!? This next one leaves me totally incredulous: no activity whatsoever throughout the year for the search term “holiday shopping” except April, May, and, to a lesser extent, December. Finally, for the very popular search term “shopping,” the month of April appears to have been totally lost.

So, although the PrioritySubmit tool sounds good in theory, until their data starts looking a lot more credible, I’ll be relying on WordTracker, Overture’s Search Term Suggestion Tool, and Google’s Keyword Sandbox for studying keyword popularity with search engine users. (In case you’re curious, according to Overture’s tool, keyword searches across Yahoo! and the rest of Overture’s network during the month of October for “Christmas shopping” was 13985, for “holiday shopping” was 2751, and for “shopping” was 2273098.)