So, you have set up your website (or blog), have put together a wonderful product to sell, and have devised a careful strategy to drive tons of traffic to the site/blog. Now, you are waiting for the cash registers to ring. Is that the end of your efforts? Well, not likely! Like every good marketer, [...]
Category Archive for ‘Search Engines’ 
How To Get New Web Sites To Rank Quickly
What is the difference between an unremarkable no value add thin ecommerce site, and a top ranked site? In some industries the difference is simply site age. Sites that were around a few years ago had fewer competitors, so it was easier for them to rank. As they aged they got trusted more, and some of those top rankings lead to many self-reinforcing links.
If your site is brand new and you want to compete against established sites directly on their most important keywords then you need to be good at public relations, have a better brand strategy, or have some remarkable feature that makes people want to talk about you. Without conversation and links it is hard to pass up sites that have been accumulating links for years.
But what if you could roll back the clock, and quickly grab market leading positions? You can.
10 Reasons to Elbow Into New Web Directories
New directories are a valuable tool for Web sites that need that extra boost in search engine ranking or in their number of visitors. They make for a great way to increase Web exposure and expand your Web site’s advertising. Since many of the top Web directories are quite expensive and take time to be edited, I have made a list of the benefits that can be acquired through new directories.
A Small Business Marketing Success Story: K9cuisine.com
Being small is hard enough. But being small and in retail? That’s like having two strikes against you before the game even begins. From setting up relationships with banks, to finding trustworthy suppliers, to building a loyal customer base, being a small retailer is a challenge many businesses can’t meet. And if you’re an online-only small retailer? Well, that adds a whole new set of pros and cons into the mix.
K9cuisine.com is one such business that’s so far been able to meet all the challenges of being a small, internet-only retailer. The nine-employee company sells premium pet foods and accessories from a warehouse in the remote town of Paris, Illinois — about 100 miles west of Indianapolis and 200 miles south of Chicago. Owner Anthony Holloway launched the company in May, 2007, because he was frustrated with trying to find quality dog food locally and online. After opening K9cuisine.com, he learned there were a lot of other pet owners sharing his frustrations. “Our business took off quickly and has grown at the rate of 50% each month for the last year,” Anthony says. The web site, he says, currently gets close to 5,000 unique visitors per day, and has generated about $2.5 million in sales in the last 12 months.
Peeking Into Google’s Use of Data
Google is showing users how it takes data from their history of searches and their location to customize the results it displays. So far it is not displaying similar information about data it uses to target advertising.
Five Steps To Successful Site Architecture For B2B SEO
A couple months ago, I noted that one of the 6 mistakes B2B marketers continue to make with organic search was inadequate site architecture-the fact that many B2B sites don’t have sufficient content to respond to desired search terms. The solution, however, isn’t simply adding more content. Proper site architecture is also critical. Here are five steps to success.
1. Identify potential keywords
Keyword strategy in B2B SEO is downright difficult. I talked about many of the reasons why in a previous Search Engine Land article about navigating B2B keyword strategy. Erik-Jan Bulthuis had a great post on Joost de Valk’s site in which he also describes some of the challenges and proposes a good approach to B2B keyword research. Your goal is this first step is not to make keyword choices or judgments, but rather to create the gross list, being as inclusive as possible of the potential terms actual prospects might use.
Focus on generic keywords; don’t get caught up in proprietary brand lingo. Think of the types of products and services you sell. What are your revenue streams? What do customers and prospects call things? Will their search string express the product/service sought, the problem they’re experiencing, or the type of company potentially offering solutions? Does geography play a role in the search string?
2. Determine relative popularity
Once you’ve created the gross list of potential keywords, you need to determine the relative popularity of those search terms. Often paid search keyword research tools (such as Google’s Traffic Estimator) won’t have data because traffic for these terms is low. In some cases, there will be data, but it will show very low activity. That’s okay. Don’t pay too much attention to that. Rather, use tools like Keyword Discovery to determine relative historical popularity of your keywords. This will give you some idea of which search terms are used more often than others on your list. The actual raw number of searches for a given search term really doesn’t matter much.
When you’re doing this work, remember to enter the root word(s) or root phrase, letting your research tool return permutations and long-tail options. Not only will this give you a larger list to consider, but the results will often lead you down a path you hadn’t previously considered.
3. Make your draft picks
Now determine for which search terms your site will be optimized. In B2B keyword research, usually there will not be clear-cut winners. Instead, for each B2B product or service, there will be one or two relevant search terms that rank highly, three to five more that place as strong “seconds”, and a host of others that have good potential.
As you’re evaluating relative popularity of the search terms related to each product or service, remember to look at the whole list, including long-tail strings with lower search volume. Sure, these strings may not yield much traffic, but they may represent a more likely buyer or one closer to making a purchase decision.
4. Find a home for them
When you’ve fully reviewed things and made your selections, often, you’ll wind up selecting three or more search terms for the same product or service-and these terms will be sufficiently different from one another that you won’t be able to have a single web page serve as the landing page for all three terms. In fact, you may need many pages, one for each term.
In some cases, having three different product pages essentially taking about the same thing may be okay (as long as it isn’t seen as duplicate content.) In other cases, it may look strange both to site visitors and from a useability standpoint. If so, here’s where you need to get creative. You need to find a home for these “extra” search terms. Where else can these landing pages go on your site? In other words, where else on your site can you create a credible landing page that is going to respond well to organic search for the given term?
Thankfully, on B2B sites there often are (or can be) some other good alternatives to product pages. Can a case study page act as the landing page for the search term? What about a white paper page? A page in the Knowledge Center or thought leadership section of your site? What about in the news section? A blog posting? There are lots of options.
Obviously the way you handle a search term in the copy of a product section will be different than how you might handle the same term in a case study. And that’s okay. Actually, it will force you not to create duplicate content. The important part is that you have sufficient landing pages for the desired search terms.
5. Link it up
Once you’ve identified a home (i.e., a channel or section of your site) for each landing page, you need to work these pages into your navigation. Some of these pages might be directly accessible through your site’s primary navigation. Some may be in the sub-navigation of a given section, while others may only be accessible through text links in the body copy of a page. Keep the landing pages for the most popular search terms closest to the home page, the least amount of clicks possible to get to the landing page. Landing pages related to less popular, more obscure, or long-tail search terms can reside deeper in your site.
Finally, make sure you have intra-site linking between related search terms. If there are three landing pages for a given product-say a product page, a case study page, and a blog posting-make sure that the site visitor can easily get from her landing page to the other related pages. In other words, if your site visitor land on the case study page, make sure you have a link there to get to the related page in the product section of your site.
If you follow these steps, you’ll create a site that has sufficient landing pages for each of your desired search terms, and your content will be organized into a logical, user-friendly architecture that responds well to organic search.
All this assumes you can write good B2B SEO copy that’s also persuasive to the site visitor. But that’s the subject of another article.
Galen De Young is Managing Director of Francis SEO, a Michigan firm specializing in B2B search engine optimization. Francis SEO is a division of Francis Marketing, one of the leading marketing consulting firms specializing in repositioning B2B companies and their brands. You can reach Galen at gdeyoung@francis-seo.com. The Strictly Business column appears Wednesdays at Search Engine Land.
Comparing Search Engine Performance: How does Cuil Stack Up to Google, Yahoo!, Live & Ask
Posted by randfish
This week marked the arrival of Cuil on the search engine scene. Being a huge fan of search technology and how search engines work in general, I’ve been spending some time playing around with the new service and thought it would be valuable to expose my data on how the classic market leaders – Google, Yahoo!, Live & Ask compare to the newcomer.
When judging the value and performance of a major web search engine, there’s a number of items I consider critical to the judging process. In order, these are — relevancy, coverage, freshness, diversity and user experience. First, let’s take a quick look at the overall performance of the 5 engines, then dive deeper into the methodology used and the specific criteria.
Interesting Notes from the Data:
- I’m not that surprised to see Yahoo! come out slightly ahead. Although their performance on long tail queries isn’t spectacular, when you weight all of the items equally, Yahoo!’s right up there with Google. There’s a reason why people haven’t entirely switched over to Google, despite the far stronger "brand" they’ve created in search.
- Google is good across the board – again, not surprising. They’re the most consistent of the engines and perform admirably in nearly every test. To my mind, despite Yahoo! eeking out a win in the numbers here, Google is still the gold standard in search.
- Ask has some clear advantages when it comes to diversity and user experience, thanks to their 3D interface, which IMO does provide some truly excellent results, particularly in the head of the demand curve.
- When it comes to index size, Yahoo! appears to have the win, but I think my test is actually a bit misleading. Although Yahoo! clearly keeps more pages on many of those domains indexed, I suspect that Google is actually both faster and broader, they simply choose to keep less in their main index (and that may actually help their relevancy results). Google’s also excellent at canonicalization, an area where Yahoo! and the others all struggle in comparison.
- The biggest surprise to me? Microsoft’s Live Search. I’m stunned that the quality and relevancy of Live Search is so comparatively high. I haven’t done a study of this scale since 2006 or so, but the few dozen searches I run on Live each month have always produced far worse results than what I got this time around. Clearly, they’re making an impact and getting better. Their biggest problem is still spam and manipulative links (which their link analysis algorithms don’t seem to catch). If they fix that, I think they’re on their way to top-notch relevancy.
- Cuil doesn’t permit a wide variety of very standard "power" search options like site:, inurl:, intitle:, negative keywords, etc. making it fairly impossible to measure them at all on index size (though the lack of any results at all returned for terms & phrases where the other engines had hundreds or thousands speaks volumes). It also put their technical and advanced search scores in the doldrums – none of the "technorati" are likely to start using this engine, and that’s an essential component of building buzz on the web Cuil’s missed out on.
- Cuil was foolish to launch now. Given the buzz they had and the potential to take market share (even a fraction of a percent is worth millions), they should have had lots of people like me running lots of tests like this, showing them how clearly far behind they were from the major engines. You only get one chance to make a first impression, and theirs was spoiled. I won’t predict their demise yet, but I will predict that it will be a long time before Michael Arrington or anyone in the tech or mainstream media believes their claims again without extremely compelling evidence. Their index, from what I can see, is smaller than any of the major engines and their relevancy is consistently dismal. I feel really bad for them, personally, as I had incredibly high hopes that someone could challenge Google and make search a more interesting marketplace. Oh well… Maybe next time (assuming VCs are willing to keep throwing 30+ million at the problem).
Methodology: For each of the inputs, I’ve run a number of searches, spread across different types of query strings. This is an area where understanding how search engine query demand works is vital to judging an engine’s performance. Some engines are excellent at returning great results for the most popular queries their users run, but provide very little value in the "tail" of the demand curve. To be a great engine, you must be able to answer both.
In most instances, I’ve used search terms and phrases that mark different points along the query-demand scale, from the very popular search queries (like "Barack Obama" and "Photography") to long-tail query strings like ("pacific islands polytheistic cultures" and "chemical compounds formed with baking soda") and everything in between. You can see a full list of the queries I’ve used below each section. During the testing, I used the following scale to rate the engines’ quality:
Now let’s dive into the lengthy data collection process…
Relevancy
——————–
Relevancy is defined by the core quality of the results – the more on-topic and valuable they are in fulfilling the searcher’s goals and expectations, the higher the relevancy. Measuring quality is always subjective but, in my experience, even a small number of queries provides insight into the relative value of the engine’s results. To collect relevancy, I simply judged the degree to which the top results resolved my inquiry, and weighted those that provided the best answers in the first few positions higher than those that had better results further down.
The following are the queries I used to judge each of the engines on performance:
- Top Buzz: gas prices, iphone, facebook, dark knight, barack obama
- Popular: laptops, photography, rental cars, scholarship, house plans
- Mid-Range: fire prevention, calendar software, snow tires, economic stimulus payment, nintendo wii games
- Long Tail: pacific islands polytheistic cultures, chemical compounds formed with baking soda, genuine buddy 50 scooter reviews, google toolbar pagerank formula, getting a novel published
- Technical: metalworking inurl:blog, cricket -site:.co.uk -site:.com.au, dark crystal site:imdb.com, top * ways, definition sycophant
Coverage
——————–
Coverage points towards a search engine’s index size and crawl speed – the bigger the index and faster the engine crawls, the more pages it can return that have relevance to each query. To judge this metric, I focused on the coverage of individual sites (both large and small) as well as queries in the tail of the demand curve.
Queries used for evaluation:
- Large Sites: site:government.hp.com, site:research.ibm.com/leem, welsh rugby site:bbc.co.uk, search engine optimization site:w3.org, tango tapas seattle site:nytimes.com
- Mid-Size Sites: site:seomoz.org/blog, site:news.ycombinator.com, site:education.com/magazine, bumbershoot site:thestranger.com, snowboards site:evogear.com
- Small Sites: site:downtownartwalk.com, site:amphl.org/, site:totebo.com, dockboard site:loadingdocksupply.com, site:microsites.audi.com/audia5/
Freshness
——————–
Although coverage can help to indicate crawl speed and depth, freshness in results shows a keen effort by the engine to place relevant, valuable news items and other trending topics atop the results. I used a number of queries related to recent events both popular and long tail (including new pages from relatively small domains) to test the quality of freshness offered by the engine’s index.
Queries used for evaluation:
- Top Buzz: los angeles earthquake, obama germany, gas prices, ted stevens, beijing olympics
- Popular Queries: new york city weather, dow jones average, seattle mariners schedule, cuil launch, nasa news
- Mid-Range Queries: warp speed engine, unesco world heritage, movie times 98115, comic con 2008, most charitable us cities
- Long Tail Queries: melinda van wingen, over the hedge comic 7/28, seomoz give it up blog, scrabulous facebook, internet startups that failed miserably
Diversity
——————–
When search queries become ambiguous, lesser engines often struggle to provide high quality results, while those on the cutting edge can serve up much higher value by providing diversity in their results or even active suggestions about the query intent.
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Queries used for evaluation (I’ve only used 3 queries per level here, as more ambiguous query strings are very challenging to identify):
- Highly Ambiguous: mouse, ruby, drivers
- Moderate Ambiguity: comics, shipping, earth
- Relative Clarity: ibm, harry potter, graphic design
- Obvious Intent: seattle children’s hospital map, color wheel diagram, great gatsby amazon
User Experience
——————–
The design, interface, features, speed and inclusion of vertical results all play into the user experience. An engine that offers a unique display may rank well or poorly here, depending on the quality of the results delivered and whether the additional data provides real value. Rather than separate queries, I’ve judged each of the engines based on their offerings in this field (using both the data from the previous sets and my own past knowledge & experience).
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User experience was based on each of the following:
- Query Speed – the average time from hitting the search button to having a fully-loaded results page
- Results Layout – including the organization of results, ads, query options, search bar, navigation, etc.
- Vertical Inclusion – the inclusion of valuable vertical or "instant answer" style results where useful
- Query Assistance – the use of disambiguation, expansion, and similar/related queries
- Advanced Features – the ability to conduct site specific searches, search for terms only in specific URLs or titles, and narrow by website type, a given folder on a domain, etc.
For those who’d like to provide their own input about how to judge a search engine, Slate.com is running a reader contest to ask How do we know if a new search engine is any good? – I’d strongly encourage participation, as I know the audience here can contribute some excellent insight :-)
If you’re interested, here’s a screenshot of the Google Docs spreadsheet I created to conduct this research (and I’ve published the doc online here):
This kind of thing is a lot of work, and although this isn’t scientifically or statistically significant, and clearly biased (as I’m the only one who did the judging), I think the results are actually fairly useful and accurate, though it would be fascinating to run public studies like this on a defensible sample size.
p.s. Want to use any of the images or content from this post? Go for it - just please provide a link back 