In this era of smart spending, many organizations are evaluating every expense – including domain names. Sure, domains are dirt cheap through many services these days, but if you have a few domain names, and you buy several extensions to each, you’re eventually spending real money.

So, how important is it to maintain the renewals? As with many things in life, “it depends.” In this case, the root questions we can turn to are:

1) Is there a potential impact to your brand if the domain that lapses falls into the hands of a competitor or other site you’d rather not be associated with?

2) If that happened, what would be the cost? That includes the impact on your brand, legal fees, time that could have been spent on proactive efforts, etc.

3) Most importantly, is the savings now worth the risk of what might happen later?

Chances are that makes it a simple question.

The only real gray area is which extensions are important. You’re going to find many differing opinions on which matter, but here’s our take:

The “no brainers” to protect:

• .com
• .net
• .org

For key domain names, consider also:

• .biz
• .info

And if you do business in other countries (or think you might someday):

• reserve the relevant country extensions as well

The next most commonly asked question is – what about .mobi? Personally, I don’t see it taking off. Technology now enables a site to adapt itself to the browser, which is much more elegant (read: user friendly) than forcing people to learn a new domain extension. A quick check of some popular sites reveals even in highly competitive markets, few companies have bothered to reserve a .mobi domain.

If you are interested in doing everything you can be to protect your sites’ domain name (just owning it isn’t always enough!), see also: http://www.circleid.com/posts/help_domain_name_hijacked/.

Also, please note that there are some good ways to maintain the domain names in your organization that you should think about before things get too messy!

Pure Visibility recently supplied a visualization challenge to several students in Professor Mick McQuaid’s Information Visualization 649 course at the University of Michigan School of Information. And the results, a visualization system design for SEO Word Market Analysis by HCI Designers Jasper Liu and Li Li, were fantastic!

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Two months ago, Google Analytics Motion Charts were hot. Now, they’re not, at least if we trust the amount of traffic coming to this blog looking for information on the charts and the amount of new content being produced around this feature. Is this a natural consequence of time since the feature was released, or is there something about the Motion Charts that make them less-than-user friendly? Did Google possibly goof?

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Have you ever wanted to be systematic about testing different versions of a popular page on your site, but felt overwhelmed by questions of how long a test should last, which traffic channels should be sent to the pages being tested, and how certain your results are? Landing Page Optimization by Tim Ash is the most comprehensive book available on test design, analysis, and the finer points of both.

The book’s clarity is its strongest feature. The risks, advantages, and disadvantages of A/B versus multivariate tests are explicitly defined, and examples that put success in terms of revenue are used throughout the book.

Another memorable aspect is Tim’s observation that both the visits to the site, and the element variations being tested on a page (for example, the font, or a graphic, or any other aspect of the page design) are are independent of one another in effects. This is something we’ve discussed here at Pure Visibility on multiple analytics projects. For example, you may have a page for which you are testing two background colors, and two very different button designs. It may be very well be the case that the color and the button design displayed effect each other, either positively (increasing the conversion rate) or negatively (canceling each other’s positive effects). In this simple scenario, it is relatively easy to add tests for each pairwise combination of elements, to determine the truly winning “recipe”. However, in a more complex test, separate tests of each combination increase the time and data needed for the test. Sometimes, independence must be assumed to some degree. Kudos to Tim for addressing this in a book anyone with basic stats knowledge can understand.

Separate your content from its presentation. It is a best practice to keep the code on your website that controls of the appearance of your site separate from the actual content. It’s good for accessibility and it’s good for flexibility, in case you want to go back and change stuff on your site later. I recently read an article by Aaron Gustafson on A List Apart, Understanding Progressive Enhancement, that reinforced this concept from a bit of a different angle.

“Progressive enhancement” dates back to 2003. This article starts with contrasting progressive enhancement with graceful degradation. Whereas graceful degradation focuses on giving the latest browsers the best experience while not completely breaking the experience for older browsers, progressive enhancement takes the opposite perspective: starting with a good experience and making it better depending on what technology you’re using. This is the angle the interesting angle. It’s not just about making sure that a website works for everyone. A highly interactive site can engage users and may increase conversion rates, and progressive enhancement takes the content as the foundation on which you can build a great website.

The heart of progressive enhancement is the content – writing content that is properly marked up so it is versatile and can be displayed in all sorts of different technologies. Gustafson uses the analogy of a peanut M&M to discuss this – the content is the peanut, the chocolate is presentation (CSS), and the hard candy shell is the flashy, snappy interactive features that use the best that browsers have to offer. Although almond M&M’s are obviously superior to the peanut variety, this is a good analogy.

This approach makes sense. Foremost, if people can’t access your content, why bother having a website? Solid and versatile content is good for people who have disabilities. There’s always going to be plenty of users who do not have the very latest browser – plus, you never know who’s going to come out with a brand new browser next. Browsers may not even be the main way customers interact with your content, one day.

This progressive enhancement concept plays well with SEO. You’ve got to ensure that search engines can figure out what your site is all about, so making your content adaptable is going to help. From a user experience perspective, also, this stuff matters. You don’t want to go around cutting off potential customers from reading your site just because they’re on a mobile device or are paranoid about having Javascript turned on.

Color perception is a tricky business – the way a color makes a person feel, the colors we choose to wear and identify with, is about as subjective a topic as you can yet. But studies in perceptual psychology have also shown certain colors to have certain effects across subjects, albeit with sometimes contradictory results. Use of color on websites becomes an interesting area of investigation. How does one strike a balance between the colors the designer prefers, and the associations that color might bring up for users? What facts can we be sure of when it comes to the effects colors produce?

Not too long ago Mike wrote a post discussing a report from the Journal of Usability Studies, originally published here. The take-away is that a study on color combinations on websites showed that both classical and expressive aspects of aesthetics (meaning both formal guidelines, and more subjective ‘feelings’ produced by colors) both affect users. Particular color combinations were shown to be more effective than others – specifically, “the split-complementary color schemes that utilized a cool primary color (blue) for the top or global part of the page and then used either another cool color (medium blue) or a warm color (orange) for the secondary page components provided the color balance that users found most aesthetically pleasing”, in comparison to double warm colors.

This information is incredibly useful to designers, and raises the question of what further conclusions might be drawn. But searching the web for what others have to say about color in web design brings up the expected contradictions and unsupported facts – for instance, did you know that
“white is associated with youth and freshness,”, or that “orange is associated with fun and youth?” What’s funny is that the first site cites the second for information.

So no definitive source exists. While I typically prefer data to back up guidelines, my desire for further guidelines led me to turn to what some of the seminal thinkers on form and color had to say about what colors mean. Wassily Kandinsky, the early abstract modern artist, developed his own theory of color early in the last century, one that has been much referenced by researchers following him in art theory as well as other fields. Why? Even if modern art isn’t your thing, its hard to deny Kandinsky’s talent (skill?) using color to produce effects on a viewer. The experience of viewing a Kandinsky up close, is, (imo), difficult to reproduce.

So what does he have to say? Blue, found to be effective in main navigation on sites, is associated with depth and restfulness; yellow is its opposite, the most aggressive, insistent, and disturbing color. The mid-point of these two “active colors” is green, a color that feels stationary as a result, and is thus even more restful than blue. Black and white, neither of which are “active colors” themselves, represent silence, but one (white) with possibility, while the other (black) brings up connotations of death or impossibility. These two opposites also combine to form an even more motionless, silent color, grey. Red is an intense warm color, but lacks the quality of reaching out to the viewer that makes us perceive yellow as so aggressive. Orange lies between the two in seeming closeness to the viewer. Brown is passive, and violet’s connotations depend on the amount of red/blue creating it.

What I like about Kandinsky’s ideas is that they are a basic guideline that describe the less tangible qualities (degree of seeming “motion”, for example) over focusing on more debatable connotations.

Have time to read a blog post? What if I told you in just a few short minutes you could walk away with increased knowledge of persuasive design techniques?

B.J. Fogg, a well-known researcher in the land of web design and info architecture, who’s been influential in discussions of web credibility, is also the author of a book on Persuasive Interaction. In short, “captology” as he calls it, is the idea of computers as persuasive technologies.

One interesting idea Fogg suggests is using cause and effect to persuade potential customers to convert: Fogg uses the example of how using curve of a simple graph symbolizing the growing nest egg of a customer can be juxtaposed with an image of one of the luxury perks, such as a hotel or yacht, that could result of the savings. I like this idea, but immediately begin thinking of other ways to show cause and effect online. Before and after type pictures are one obvious idea. But not everyone responds to pictures; some like hard facts, some like charts. Is there a “best” or “correct” way to use cause and effect?

An email newsletter I came across this week emphasized this same idea, cased as describing a service based on its benefits, rather than the logistics of what it entails. Reading it I imagine “fluffy” web copy, the kind that harks of empty promises and turns me off personally as a consumer. Thus as straightforwardly effective as the idea sounds, the same quandary presents itself: how can I speak to a variety of potential consumers on the same page?

The basis of the question seems rooted in people’s differences when it comes to preferred levels of specificity and presentation-types. A little research turned up Dave Young’s great resource on tailoring web design to different types of decision makers. The video uses a 4 quadrant grid to dichotomize fast versus slow decision makers as well as emotional versus logical ones. My dissatisfaction with over-generalized web copy describing benefits results from being a fast, logical decision maker. I want anything I’m going to read online to be quick to get to the facts.

One question that still lingers after watching Young’s video relates to whether there is any risk in combining so many types of content in a single page/site. I am thinking both of the example contractor’s site that Young uses, and Fogg’s example above of the graph in conjunction with the picture. The latter combines not only symbolic and realistic representations, but also emotional and logical ones. It is a fact that many people are scared of numbers and graphs. Is there a chance that some emotional folks will be scared off by certain charts, or numbers displayed too prominently? On the flip side, I do feel there are limits to how much “soft” marketing content I can handle before I am scared off.

Examples of sites that go to far in combining types of content would be appreciated!

Seth Godin posted a couple of thought-provoking blog posts recently about online ads: Ads are the new online tip jar and a follow-up, Beating the status quo.

What Godin proposes is, when you read a blog, “if you like what you’re reading, click an ad to say thanks.” If everybody engaged in this behavior, it would over time change the model of online advertising so that ads would pull in more people but they would be less well qualified.

He writes that your landing page gives you the opportunity to “immerse someone in an entire page you designed. In other words, a chance to convert mild interest into big interest.”

This is the part that is particularly interesting to me. The idea of landing pages (at least at this time) is it fulfills the promise made in the ad the user just clicked on. The ad is meant to pull in only people that are interested in learning more. The landing page, in turn, is meant to speak to people who found the ad interesting and want to learn more about the product that was advertised or finding a solution to a problem they experience. Godin’s vision entails people clicking on ads that they don’t actually care about.

We would be challenged to put together landing pages that speak to the casual visitor. We would have to grab the attention of these less-motivated visitors immediately to keep them from leaving. When talking about the product or service, different messages will appeal to different people, but the more messages you try to pack into a landing page, the harder it will be to get through to visitors.

The answer, then, may be to try to suck in visitors through content that is entertaining instead of presenting a purely informative page. Will that strategy work for every business, though? Perhaps the answer lies in crafting the message on a landing page to clearly and loudly tell visitors why this landing page is worth their time.

Godin’s idea intrigues me but I am not convinced. He proposes that the value of this new model to advertisers would be “begin[ning] to reach the unreachable non-clickers.” It will be hard to reach visitors whose motive for clicking on an ad is not to learn more about what you are advertising, but rather to generate income for the blogger whose work they enjoy.

At the end of July, Microsoft Research held its 2008 Faculty Summit to survey the state of computing R & D, which this year included a social media summit. A major topic of conversation included the transition of the internet from a network of documents to a network of people.

As participant (host) and Microsoft Scientist Matthew Hurst explains on his blog, “The PageRank era is marked by a very simple link with no explicit meaning and a simple assumption (a positive endorsement).” But this assumption of positive endorsement is becoming unnecessary as more and more direct evidence of people’s opinions and categorizations of content are available online. Research repeatedly reveals that others take notice of human-generated tags and reviews: “consumers report being willing to pay from 20% to 99% more for a 5-star-rated item than a 4-star-rated item (with variance depending on type of item/service)”, is just one example.

Many are excited by how much less processing-intensive the online content tagging process becomes with this trend – clusters of pages and facts seem to grow organically as a result of human tagging. This helps overcome previous problems related to content indexing within info retrieval, such as the gap between the language that the businesses or organizations use to label their content and the terminology preferred by their customers/users.

But there are challenges that arise as well in this transition that are less discussed. Says one scientist, aptly describing the phenomena, “fragmenting media and changing consumer behavior have crippled traditional [media] monitoring methods. Technorati estimates that 75,000 new blogs are created daily, along with 1.2 million new posts each day, many discussing consumer opinions on products and services. Tactics [of the traditional sort] such as clipping services, field agents, and ad hoc research simply can’t keep pace.” Call it what you will: Brand Monitoring, Online Image Tracking, Buzz Monitoring, Online Anthropology, Conversation Mining, Online Consumer Intelligence, Market Influence Analytics … The challenges remain the same. As an example, I think of a project I did here at Pure Visibility last year, which involved analyzing online review content related to a client’s company. After gathering the reviews (in the hundreds), I was faced with the daunting task of mining them for basic information like the overall majority sentiment expressed, and how this correlated with the source. My ultimate method was mostly manual and more than a little tedious.

Hurst’s blog contains a reference to a new book by Pang and Lee that surveys the state of Opinion Mining and Sentiment Analysis, (basically, data-mining and classification using human generated content). In addition to interesting facts on the power of opinions like those above, this book clearly outlines the process that such analysis requires, and the associated challenges. For example, incorporating user opinions into a search engine typically requires the following steps:

1. determining whether the user is looking for subjective information
2. accurately classifying docs into the opinionated and non-opinionated bins
3. identifying overall sentiments expressed and or/specific opinion regarding particular aspects
4. summarizing information, including aggregating votes via different rating scales, highlighting some opinions, representing disagreement/consensus points, id’ing opinion holders, etc

The challenges are numerous. To summarize some of the excellent points made by Pang and Lee, I sketched out the following table, which compares opinion mining to traditional text mining:

To clarify on this last point, the authors note that this fact alone does not make the task more difficult than traditional topic classification, since data-driven approaches can be applied to the latter to improve accuracy over classification using a human-picked keyword list. The problem is that the accuracy of a data-driven method for opinion analysis is only about 80%, which is still not comparable to the performance expected in traditional topic-based classification.

While these challenges may seem intimidating enough to remain on the horizon for years to come, the fact that this book was written by a Yahoo research scientist, and one of the country’s top CS schools suggests that the right people are thinking about these trends. Significant changes in how we use the web may not be far off.

It’s strange that we’ve started discussing branding, because there’s been a sudden boost in arguments that search results have a brand impact. This article from Search Engine Watch, for example implies that the paid search advertising executed by John McCain, who is currently spending enough to get four times as many paid search impressions as Barack Obama, will have a positive brand effect.

These assertions are a mystery to me, because they seem to intentionally miss the distinction between something that creates brand awareness and something that results in an actual branding effect. The distinction is actually pretty simple:

Brand Awareness is an “I know about” indicator. It is something people know in their heads.

Branding is an “I feel about” indicator. It is something people know in their gut.

So what I want to know is: how exactly is a John McCain for President banner ad going to accomplish the latter?

It can’t. Awareness is not branding. The only effective measure of branding is whether or not a person CHANGES BRANDS. Exposure to new brands is only part of the effort.

It is strange as an analyst to be making this distinction, but I have seen it repeatedly even among my friends. Branding is incredibly powerful, subtle, and pervasive. People who will insist to their last breath that they are unaffected by brand will be heavily influenced by it (to the point of self-parody). Branding–not awareness–is the only real measure of loyalty or purchasing trends.

The reason I am taking this specific stand is because branding is still the consequence of excellent products that have some emotional impact on a user. Search engine results do not provide that. They provide the OPPORTUNITY for that to occur at a fraction of the historical cost, which a key, critical point. But I don’t want to oversell its value. For branding to truly work there still needs to be that traditional marketing and self-identification that is so very hard to replicate or create.