Short intro here:

Long view here:

Not seeing it yet? You can probably turn it on here (though in some countries you may also need to be logged into a Google account). In time Google intends to make the is a default feature turned on for almost everyone (other than those with slow ISPs and older web browsers). And if you don't like it, the feature is easy to turn off at the right of the search box, but to turn it off it uses a cookie. If you clear cookies the feature turns right back on.

Here is an image using Google's browser size tool, showing that when Google includes 4 AdWords ads only 50% of web browsers get to see the full 2nd organic listing, while only 20% get to see the full 4th organic listing.

Its implications on SEO are easy to understate. However, they can also be overstated: I already saw one public relations hack stating that it "makes SEO irrelevant."

Nothing could be further from the truth. If anything, Google instant only increases the value of a well thought out SEO strategy. Why? Well...

• it consolidates search volume into a smaller basket of keywords
• it further promotes the localization of results
• it makes it easier to change between queries, so its easier to type one more letter than scroll down the page
• it further pollutes AdWords impression testing as a great source of data

Lets dig into these, shall we?

1. Bing Adds NBA Instant Answers to Mobile Search Site
2. Google Brings Click to Call to Mobile Ads
3. Google AdWords Enables Mobile Device and Carrier Targeting, Plus Special Link for Mobile Apps

1. AT&T Says Google Voice Restricts Calls; Google Says “Yeah, So?”
2. Consumer Groups Look To Block Google Admob Deal
3. Google Launches Gesture Search for Android

But in spite of those, there is no denying that he is an astute marketer. So I thought it would be fun to ask him about his background in SEO and to articulate his take on where some of our differences in opinions are. Interestingly, it turns out we shared far more views than I thought! Hope you enjoy the interview. :)

Throughout your history in the SEO field, what are some of your biggest personal achievements?

The first one would have to be digging myself (and my Mom) out of bankruptcy when we were still a small, sole proprietorship. Since then, there have been a lot of amazing times:

• The first time I spoke at a conference (SES Toronto in 2004)
• Transitioning from a consulting to a software business
• Taking venture capital
• Building a team (not just making hires)
• Having dinner with the UN Secretary General (Ban Ki Moon) and presenting to their CTO on SEO - it was amazing to hear stories about how people in conflict-ridden parts of the world used search to find safe havens, escape and transmit information and the UN's missed opportunities around SEO. I'd never really thought of our profession as having life-or-death consequences until then.
• Making the Inc 500 list for Fastest Growing Companies in the US (during a nasty recession)
• Probably my biggest personal achievement, though, is my relationship with my wife. I know that no matter what happens to me in any other part of my life, I have her support and love forever. That gets a guy like me through a lot of tough times.

My wife and I in San Franicsco (via her blog)

What are the biggest counter-intuitive things you have learned in SEO (eg: that theoretically shouldn't work, but wow it does (or the opposite - should work but doesn't)?

The most obvious one I think about regularly is that the "best content rarely wins." The content that best leverages (intentionally or not) the system's pulleys and levers will rise up much faster than the material the search engines "intended" to rank first.

Another big one includes the success of very aggressive sales tactics and very negative, hateful content and personalities. Perhaps because of the way I grew up or my perspective on the world, I always thought of those things as being impediments to financial success, but that's not really the case. They do, however, seem to have a low correlation with self-satisfaction and happiness, and I suppose, for the people/organizations with those issues, that's even worse.

A very specific, technical tactic that I'm always surprised to see work is the placement of very obvious paid text links. We realized a few months back that with Linkscape's index, we could ID 90%+ of paid link spam with a fairly simple process:

1. Grab the top 10K or 100K query monetizable terms/phrases (via something like a "top AdSense payout" list)
2. Find any page on the web that contains 2+ external anchor text links pointing to separate websites (e.g. Page A has a link that says "office supplies" linking to 123.com and another link that says "student credit card" linking to 456.com)
3. Remove the value passed by those links in any link metric calculation (which won't hurt the relevancy/ranking of any pages, but will remove the effects of nearly all paid links)

We've not done the work to implement this, so perhaps there's some peculiar reason why applying it is harder than we think. But, it strikes me that even if you could only do it for pages with 3 or 4+ links in this fashion, you'd still eliminate a ton of the web's "paid" link graph. The fact that Google clearly hasn't done this makes me think it must not work, but I'm still struggling to understand why.

BTW - I asked some SEOs about making this a metric available through Linkscape/Open Site Explorer (like a "liklihood this page contains paid links" metric) and they all said "don't build it!" so we probably won't in the near term.

One of the big marketing angles you guys tried to push hard on was the concept of transparency. Because of that you got some pretty bad blowback when Linkscape launched (& perhaps on a few other occasions). Do you feel pushing on the transparency angle has helped or hurt you overall?

I think those inside the SEO community often perceive a conflict or tiff internally as having a much broader reach than it really does. I'd agree that folks like you and I, and maybe even a few hundred or even a thousand industry insiders are aware of and take something away from those types of events, but SEOmoz as a software company with thousands of paying subscribers and hundreds of thousands of members seems to be far less impacted than I am personally.

Re: Linkscape controversy - there have been a few - but honestly, the worst reputation/brand problems we ever had have always been with regards to personal issues or disputes (a comment on someone's blog or something we wrote or allowed to be published on YOUmoz). I don't have a good explanation for why they crop up, but I can say that they seem to have a nearly predictable pattern at this point (I'm sure you recognize this as well - think I've seen you write fairly eloquently on the subject). That does make it easier to handle - it's the unpredictable that's scary.

We certainly maintain transparency as a core value and we're always trying to do more to promote it. To me, core value means "things we value more than revenue or profits" and so even if it's had some hard-to-measure, adverse impact, we'd maintain it. We've actually got a poster hanging up in the office that our design team made:

An excerpt from our TAGFEE poster

There's a quote I love on this topic that explains it more eloquently than I can:

"(Our) core values might become a competive advantage, but that is not why we have them. We have them because they define for us what we stand for, and we would hold them even if they became a competitive disadvantage." - Ralph Larson, CEO of Johnson and Johnson

What type of businesses do you think do well with transparency? What type of businesses do you feel do poorly with it?

Hmm... Not something I've tried to apply to every type of business, but my feeling is that nearly every company can benefit from it, though it also exposes you to new risk. Even being the transparency-loving type, I'd probably say that military contractors, patent trolls and sausage manufacturers wouldn't do so well.

How have you been able to manage the transparency angle while having investors?

I thought it would be tougher after taking investment, but they've actually been very supportive in nearly every case (some parts of Linkscape, particularly those re: our patent filings being exceptions). I don't know if that would be true had we taken on different backers, but that's why the startup advice to choose your investors like you choose your husband/wife is so wise.

When you took investment money did you mainly just get capital? What other intangibles came with it? How have your investors helped shape your business model?

It certainly made us much more focused on the software model. As you noted, we dropped consulting in 2010 entirely, and we've generally limited any form of non-scalable revenue to help fit with the goals of a VC-backed business. We did gain some great advisors and a lot more respect in many technology and startup circles that would have been tough without the presence of venture funds (although I think that's shifting somewhat given the changes of the past 2-3 years in the startup world).

Have you guys ever considered buying out your investors? Are you worried what might happen to your company if/when it gets sold?

While we'd love to, I doubt that would ever be possible (barring some sort of massive personal windfall outside of SEOmoz). Every dollar we make gets our investors more excited about the future of the company and less likely to want to sell their shares before we reach our full potential. Remember that with VC, the idea is high risk, high reward, so technically, they'd rather we go for broke and fall to pieces than do a mid-size, but profitable deal. Adding $5 or $10 million dollars back to a $300+ million fund is largely useless to a VC, so a bankruptcy while trying to return $50 or $100 million is a very tolerated, sometimes preferable result.

I wrote about this more in my Venture Capital Process post (where I talked about failing to raise money in summer 2009)

Now that you are already well known & well funded you are taking a fairly low risk strategy to SEO, but if you were brand new to the space & had limited capital would you spam to generate some starting capital? At what point would you consider spamming being a smaller risk than obscurity?

You ask great questions. :-)

While I don't think spam has any moral or ethical problems, I don't know that I'd ever be able to convince myself that spam would be a more worthwhile endeavor than brand building for a white hat property. Overnight successes take years of hard work, and I'd much rather get started as a scrappy, bootstrapping company than build up a reserve with spam dollars and waste that time. However, I certainly don't think that applies to everyone. As you know, I've got lots of friends who've done plenty of shady stuff (probably a lot I don't even want to know about!), but that doesn't mean I respect them any less.

Speaking of low risk SEO, why do you think neither of our sites has hit the #1 slot yet in Google for "seo"? And do you think that ranking would have much business impact?

We've looked at the query in our ranking models and I think it's unlikely we could ever beat out the Wikipedia result, Google or SEO.com (unless GG pulls back on their exact-match domain biasing preference). That said, we should both be overtaking SEOchat.com fairly soon (and some of the spammier results that temporarily pop in and out). Some of our engineers think that more LDA work might help us to better understand these super-high competitive queries.

SERPs analysis of "SEO" in Google.com w/ Linkscape Metrics + LDA (click for larger)

In terms of business impact - yeah, I think for either of us it would be quite a boon actually (and I rarely feel that way about any particular single term/phrase). It would really be less the traffic than the associated perception.

As an SEO selling something unique (eg: not selling a commodity that can be found elsewhere & not as an affiliate) I have found word of mouth marketing is a much more effective sales channel than SEO. Do you think the search results are overblown as a concern within the SEO industry? Do you find most of your sales come from word of mouth?

I see where you're coming from, but in our analyses, it's always been a combination of things that leads to a sale. People search and find us, then browse around. Or they hear of us and search for information about us. Then they'll find us through social media or referring site and maybe they'll sign up for a free account. They'll get a few emails from us, have a look at PRO and go away. Then a couple months later they'll be more serious about SEO and search for a tool or answer and come across us again and finally decide, "OK, these guys are clearly a good choice."

This is what makes last touch attribution so dangerous, but it also speaks to the importance of having a marketing/brand presence across multiple channels. I think you could certainly make the case that many of us in the SEO field see every problem as a nail and our profession as the hammer.

What business models do you feel search fits well with, and what business models do you feel search is a poor fit for?

I think it's terrific for a business that has content or products they can monetize over the web that also relate to things people are already searching for. It's much less ideal for a product/service/business that's "inventing" something new that's yet to be in demand by a searching population. If you're solving a problem that people already have an identified pain point around, whether that's informational, transactional or entertainment-driven, search is fantastic. If that pain point isn't sharp enough or old enough to have generated an existing search audience, branding, outreach, PR and classic advertising may actually do better to move the needle.

Have you ever told a business that you felt SEO would offer too low of a yield to be worth doing?

Actually yes! I was advising a local startup in Seattle a couple years ago called Gist and told them that SEO couldn't really do much for them until people started realizing the need for social-plugins to email and searching for them. This is the case with a lot of startups I think.

In an interview on Mixergy you mentioned up racking up a good bit of debt when you got started in search. If a person is new to the web, when would you recommend them using debt leverage to grow?

Never, if you're smart. Or, at least, never in the quantities I did. The web is so much less costly to build on nowadays and the lean startup movement has produced so many great companies (many of them only small successes, but still profitable) from $10K or less that it just doesn't make sense, especially with the horror that is today's debt market, to go too far down that route. If you can get a low-cost loan from a family member or a startup grant through a government-backed, low interest program, sure, but credit card debt (which is where I started) is really not an option anymore.

How were you able to maintain presence and generally seem so happy publicly when you first got started, even with the stress of that debt?

To be honest, I really just didn't think about it much. If you have $30K in debt, you're constantly thinking about how to pay it off month by month and day by day. When you're $450K in debt with collectors coming after you and your wife paying the rent, you think about how to make a success big enough to pay it all off or declare bankruptcy - might as well go with the former until life runs you into the latter. There's just not much else to do.

As Bob Dylan says - "when you got nothing, you got nothing to lose."

Many people new to the field are afraid to speak publicly, but you were fairly well received right off the start. What prepared you for speaking & what are keys to making a good presentation?

Oh man - I sucked pretty hard my first few presentations. I think everyone does. The only reason I was well received, at least in my opinion, is because I'd already built a following on the web and had a positive reputation that carried over from that. The only thing that really prepared me for big presentations (things like the talk to Google's webspam/search quality team or keynotes at conferences) was lots and lots of experience and for that I'll always be grateful to Danny Sullivan for giving me a shot.

I'd say to others - start small, get as many gigs as you can, use video to help (if you're great on camera, you'll be good in front of a live audience) and try to emulate speakers and presentations you've loved.

When large companies violate Google's guidelines repeatedly usually nothing happens. To cite a random example...I don't know...hmm Mahalo. And yet smaller companies when outed often get crushed due to Google's huge marketshare. Because of the delta between those 2 responses, I believe that outing smaller businesses is generally bogus because it strips freedoms away from individuals while promoting large corporations that foist ugly externalities onto society. Do you disagree with any of that? :D

I think I agree with nearly all of that statement, though I'd still say it's no more "bogus" to out small spammers than it is to spam. I would agree it's not cool that Google applies its standards unfairly, but it's hard to imagine a world where they didn't. If mikeyspaydayloans.info isn't in Google's index, no ones thinks worse of Google. If Disney.com isn't in Google (even if they bought every link in the blogosphere), searchers are going to lose faith and switch engines. The sensible response from any player in such an environment is to only violate guidelines if you're big enough to get away with it or diversified enough to not care.

I'm unhappy with how Google treats these issues, but I'm equally unhappy with how spam distorts the perception of the SEO field. Barely a day goes by without a thought leader in the technology field maligning our industry - and 9 times out of 10 that's because of the "small" spammers. If we protect them by saying SEOs shouldn't "out" on another, we bolster that terrible impression. I don't think most web spam should even have the distinction of being classified as "SEO" and I don't think any SEO professionals who want our field to be taken seriously by marketing and engineering departments should protect those who foist their ugly externalities onto us.

I know we disagree on this, but it's always an interesting discussion :-)

One of the most remarkable things about the SEO industry is the gap in earnings potential between practicing it (as a publisher) and teaching it / consulting. Why do you think such a large gap exists today?

Teaching has always been an altruist's pursuit. Look at teachers in nearly every other field - they earn dramatically less than their production/publishing oriented peers. Those who teach computer science never earn what computer scientists who work at Google or Microsoft make. Those who teach math are far less well compensated than their compatriots working as "qaunts" on Wall Street. It's a sad reality, but it's why I have so much respect for people like Market Motive, Third Door Media and Online Marketing Connect, who are trying to both teach and build profitable businesses. I love the alignment of noble pursuits with profitable ones.

You guys exited the consulting area in spite of being able to charge top rates due to brand recognition. Do you think lots of consultants will follow suit and move into other areas? How do you see SEO business models evolving over the next 3 to 5 years?

I don't think so - our consulting business was going very well and I've heard and seen a lot of growth from my friends who run SEO consulting firms. The margins and exit price valuations wouldn't have made sense for VCs, but I don't think it was a bad business at all and others are clearly doing remarkable things. Just look at iCrossing's recent sale to Hearst for $325million. You can build an amazing company with consulting - it's just not the route we took.

In regards to the evolution of the SEO business model, I'd say we're likely to see more sophistication, more automation, more scalability (and hopefully, more software to help with those) over the next few years from both in-house SEOs and external agencies/consultants. It's sometimes surprising to me how little SEO consulting has progressed from 2002 vs. things like email marketing or analytics, where software has become standard and tons of great companies compete (well, Google's actually made competition a bit more challenging in the analytics space, but creative companies like KissMetrics and Unbounce are still doing cool, interesting things).

Small businesses in many ways seem like the most under-served market, but also the hardest to serve (since they have limited time AND small budgets). Do you think the rise of maps & other verticals gives them a big opportunity, or is it just more layers of complexity they need to learn?

Probably more the former than the latter. The small business owners I know and interact with in my area (and wherever I seem to visit) are only barely getting savvy to the web as a major driver of revenue. I think it might take another 10 years or more before we see true maturity and savvy from local businesses. Of course, that gives a huge competitive advantage to those who are willing to invest the time and resources into doing it right, but it means a less "complete" map of the local world in the online one, which as a consumer (or a search engine) is less than ideal.

When does the delta between paid search & SEO investment begin to shrink (if ever)?

I think it's probably shrinking right now. Paid search is so heavily invested in that I think it's fair to call it a mature market (at least in global web search, though, re: your previous question, probably not in local). SEO is ramping up with a higher CAGR (Compound Annual Growth Rate) according to Forrester, so that delta should be shrinking.

via Forrester Research's Interactive Marketing Forecast 2009-2014

Often times a Google policy sounds like something coming out of a conflicted government economist's mouth. But even Google has invested in an affiliate network which suggests controlling your HTML links based on payment. How much further do you think Google can grow before they collapse under complexity or draw enough regulatory attention to be forced to change?

I think if they tread carefully and invest heavily in political donations and public relations, they can likely maintain another very positive 5-10 years. What the web looks like at that time is anyone's guess, and the unpredictable nature and wild shifts probably help them avoid most regulation. Certainly the rise of Facebook has been a boon to their risk exposure from government intervention, even if they may not be entirely happy with their inability to compete in the social web.

I remember you once posted about getting lots of traffic from Facebook & Twitter, but almost 0 sales from it. Does there become a point where search is not the center of the web (in terms of monetization), or are most of these networks sorta only worthwhile from a branding perspective?

As direct traffic portals, it's hard to imagine a Facebook/Twitter user being as engaged in the buying/researching process as a Google searcher. Those companies may launch products that compete with Google's model or intent, but as they exist today, I don't foresee them being a direct sales channel. They're great for traffic, branding, recognition and ad-revenue model sites, but they're of little threat to marketers concerned with the relevance or value of search disappearing.

What are the major differences between LDA & LSI?

They're both methodologies for building a vector space model of terms/phrases and measuring the distance between them as a way to find more "relevant" content. My understanding is that LSI, which was first developed in 1988, has lots of scaling issues. It's cousin, PLSI (probabilistic LSI) attempted to address some of those when it came out in 1999, but still has scaling problems (the Internet is really big!) and often will bias to more complex solutions when a basic one is the right choice.

LDA (Latent Dirichlet Allocation), which started in 2002, is a more scalable (though still imperfect) system with the same intuition and goals - it attempts to mathematically show distances between concepts and words. All of the major search engines have lots of employees who've studied this in university and many folks at Google have written papers and publications on LDA. Our understanding is that it's almost universally preferred to LSI/PLSI as a methodology for vector space models, but it's also very likely that Google's gone above and beyond this work, perhaps substantially.

The "brand" update was subsequently described as being due to looking at search query chains. In a Wired article Amit Singhal also highlighted how Google looks for entities in their bi-gram breakage process & how search query sequences often help them figure out such relationships. How were you guys able to build a similar database without access to the search sessions, or were you able to purchase search data?

In a vector space model for a search function, the distances and datasets leverage the corpus rather than query logs. Essentially, with LDA (or LSI or even TF*IDF), you want to be able to calculate relevance before you ever serve up your first search query. Our LDA work and the LDA tool in labs today use a corpus of about 8 million documents (from Wikipedia). Google's would almost certainly use their web index (or portions of it).

It's certainly possible that query data is also leveraged for a similar purpose (though due to how people search - with short terms and phrases rather than long, connected groups of words - it's probably in a different way). This might even be something that helps extend their competitive advantage (given their domination of market share).

Sometimes one can see Google's ontology change over time (based on sharp ranking increases and drops for outlier pages which target related keywords but not the core keyword, or when search results for 2 similar keywords keep bouncing between showing the exact same results to showing vastly different results). How do you guys account for these sorts of changes?

Thus far, we haven't been changing the model - it just launched last week. However, one nice thing we get to do consistently is to run our models against Google's search results. Thus, if Google does change, our scores (and eventually, the recommendations we hope to make) should change as well. This is the nice part about not having to "beat" Google in relevance (as a competing search engine might want to do) but simply to determine where Google's at today.

For a long time one of the thing I have loathed most in the SEO space was clunky all-in-one desktop tools that often misguide you into trying to change your keyword density on the word "the" and other such idiocy. Part of the reason we have spent thousands of Dollars offering free Firefox extensions was my disgust toward a lot of those all-in-one tools. A lot of the best SEOs tend to prefer a roll-your-own mix and match approach to SEO. Recently you launched a web application which aims to sorta do all-in-one. What were the key things you felt you had to get right with it to make it better than the desktop software so many loathe?

I think our impetus for building the web app was taken from the way software has evolved in nearly every other web marketing vertical. In online surveys, you had one-time, self built systems and folks like Wufoo and SurveyMonkey have done a great job making that a consolidated, simple, powerful software experience. That goes for lots of others like:

• PPC - Google has really taken the cake here with Adwords integration and the launch of Optimizer and even GA
• CRM - Salesforce, of course, was the original "all-in-one" web marketing software, and they've shown what a remarkable company you can build with that model. InfusionSoft and other players are now quickly building great businesses, too.
• Email Marketing - Exact Target, Constant Contact, Mailchimp, MyEmma, iContact and many more have built tens-hundreds of millions of dollar/year businesses with "all-in-one" software for handling email marketing.
• Banner Ads - platforms like Aquantive, DoubleClick, AdReady, etc. have and are building scalable solutions that drive billions in online advertising
• Analytics - remember when we had one-off, log file analysis tools and analytics consultants who built their own tools to dig into your data? Those consultants are still here, but they're now armed with much more powerful tools - Google Analytics, Omniture, Webtrends, etc. (and new players like KISS Metrics, too)

You're likely spot-on in thinking that power players will continue to mash up and hack their own solutions, build their own tools and protect their secret processes to make them more exclusive in the market and (hopefully) competitive. But, these folks are on the far edge of the bell curve. In every one of the industries above (and many others), it looks like the way to build a scalable software product that many, many people adopt, use and love is to optimize of the middle to upper-end of the bell curve (what we'd probably call "intermediate" to "advanced" SEOs, rather than the outlier experts).

When you gather ranking data do you use APIs to do so? If not, how hard was it been on the technical front scaling up to that level of data extraction?

Some data we can get through APIs, but most isn't available in that fashion, so relatively robust networks are required to effectively get the information. Luckily, we've got a pretty terrific team of engineers and a VP of Engineering who's done data extraction work previously for Amazon, Microsoft and others. I'd certainly say that it ranks in the top 10 technical challenges we've faced, but probably not the top 3.

What do you gain by doing the all-in-one approach that a roll your own type misses out on?

Convenience, consistency, UI/UX, user-friendliness and scalability are all big gains. However, the compromise is that you may lose some of that "secret-sauce" feeling and the power that comes from handling any weird situation or result in a hands-on, one-to-one fashion. Plenty of folks using our web app have already pointed out edge-case scenarios where we're probably not taking the ideal approach, and those kinks will take time to be ironed out.

Some firms use predictive analytics to automatically change page titles & other attributes on the fly. Do you see much risk to that approach? Do you eventually see SEO companies offering CMS tools as part of their packages to lock in customers, while integrating the SEO process at a much deeper level?

When we were out pitching to take venture capital last summer, a lot of VCs felt that this was the way to go and that we should have products on this front.

Personally, I don't like it, and I'd be surprised if it worked. Here's why:

• Editors/writers should be responsible for content, not machine-generated systems built to optimize for search engines. Yes, those machine systems can and should make recommendations, but I fear for the future of your content and usability should "perfect SEO" be the driving force behind every word and phrase on your site.
• With links being such a powerful signal, it's far better to have a slightly less well-targeted page that people actually want to link to than a "perfect" page that reads like machine-generated content.
• I think content creators who take pride in their work are the ones who'll be better rewarded by the engines (at least in the long term - hopefully your crusade against Demand Media, et al. will help with that), and those are the same type of creators who won't permit a system like this to automatically change their content based on algorithmic evaluation.

There are cases I could see where something like this would be pretty awesome, though - e.g. a 404 detector that automatically 301s pages it sees earning real links back to the page it thinks was the most likely intended target.

On your blog recently there was a big fuss after you changed your domain authority modeling scores. Were you surprised by that backlask? What caused such a drastic change to your scores?

We were surprised only until we realized that somehow, our internal testing missed some pretty obvious boneheaded scores.

Basically, we calculate DA and PA using machine learning models. When those models find better "correlated" results, we put them in the system and build new scores. Unfortunately, in the late August release, the models had much better average correlation but some really terrifically bad outliers (lots of junky single-page keyword-match domains got DAs of 100 for example).

We just rolled out updated scores (far ahead of our expected schedule - we thought it would take weeks), and they look much better. We're always open to feedback, though!

When I got into SEO (and for the first couple years) it seemed like you could analyze a person's top backlinks and then literally just go out and duplicate most of them fairly easily. Since then people have become more aware of SEO, Google has cracked down on paid links, etc. etc. etc. Based on that, a lot of my approach to SEO has moved away from analysis and more toward just trying to do creative marketing & hope some % of it sticks. Do you view data as being a bit of a sacred cow, or more of just a rough starting point to build from? How has your perception as to the value of data & approach to SEO changed over time?

I think your approach is almost exactly the same as mine. The data about links, on-page, social stats, topic models, etc. is great for the analysis process, but it's much harder to simply say "OK, I'll just do what they did and then get one more link," than it was when we started out.

That analysis and ongoing metrics tracking is still super-valuable, IMO, because it helps define the distance between you and the leaders and gives critical insight into making the right strategic/tactical decisions. It's also great to determine whether you're making progress or not. But, yes, I'd agree that it's nowhere near as cut-and-dried as it once was.

The frustrating part for us at SEOmoz is we feel like we're only now producing/providing enough data to be good at these. I wish that 6-7 years ago, we'd been able to do it (of course, it would have cost a lot more back then, and the market probably wasn't mature enough to support our current business model).

How much time do you suggest people should spend analyzing data vs implementing strategies? What are some of the biggest & easiest wins often found in the data?

I think that's actually the big win with the web app (or with competitive software products like Raven, Conductor, Brightedge, etc). You can spend a lot less time on the collection/analysis of data and a lot more on taking the problems/opportunities identified and doing the real work of solving those issues.

Big wins in our new web app for me have been ID'ing pages through the weekly crawl that need obvious fixing (404s and 500s are included, like Google Webmaster Tools, but so are 20+ other data points they don't show like 302s, incorrect rel canonicals, etc.)

Blekko has got a lot of good press by sharing their ranking models & link data. Their biggest downside so far in their beta is the limited size of their index, which is perhaps due to a cost benefit analysis & they will expand their index size before they publicly launch. In some areas of the web Google crawls & indexes more than I would expect, while not going to deeply into others. Do you try to track Google's crawls in any way? How do you manage your crawl to try to get the deep stuff Google has while not getting the deep stuff that Google doesn't have?

Yeah - we definitely map our crawls against Google, Bing and Majestic on a semi-regular basis. I can give you a general sense of we see ourselves performing against these:

• Google - the freshest and most "complete" (without including much spam/junk) of the indices. A given Linkscape index is likely around 40-60% of the Google index in a similar timeframe, but we tend to do pretty well on coverage of domains and well-linked-to pages, though worse on deep crawling in big sites.
• Bing - they've got a large index like Google, but we actually seem to beat them in freshness for many of the less popular corners of the web (though they're still much faster about catching popular news/blogs/etc from trusted sources since they update multiple times daily vs. our once-per-month updates).
• Majestic - dramatically larger in number of URLs than Google, Bing or Linkscape, but not as good as any of those about freshness or canonicalization (we'll often see hundreds of URLs in the index that are essentially the same page with weird URL parameters). We like a lot of their features and certainly their size is enviable, but we're probably not going to move to a model of continuous additions rather than set updates (unless we get a lot more bandwidth/processing power at dramatically lower rates).

the problem with maintaining old URLs became more clear when we analyzed decay on the WWW

In terms of reaching the deep corners of the web, we've generally found that limiting spam and "thin" content is the big problem at those ends of the spectrum. Just as email traffic is estimated to be 90%+ spam, it's quite possible that the web, if every page were truly crawled and included, would have similar proportions. Our big steps to help this are using metrics like mozTrust, mozRank and some of our PA/DA work to help guide the crawl. As we scale up index size (probably December/January of this year), that will likely become a bigger challenge.

---

Thanks Rand. You can read his latest thoughts on the SEOmoz blog and follow him on Twitter at @randfish.

1. Jeremy Schoemaker (aka Shoemoney) Interview
2. Interview of Tedster from WebmasterWorld
3. Jon Glick Interview

Google knows this. Now you do as well. Easy always wins. Take a moment and picture your website or your blog or your product or service in your head right now. Now, think of Google’s. Which one is easier? No, you're not a search engine, you're probably a small business owner with a variety of products services, entrepreneur with a business idea, or blogger . But the comparison remains because regardless of what it is you do easy will always win.

So keep thinking about your Web business. Is what you’re selling easy to buy? By that I mean; when somebody comes to buy from you, or to simply get information from you like a phone number or to download a white paper… is it easy to do? Or are you making it too hard?

Picture Google.com again in your head. It's pretty darn easy, no? There's a logo and a big input box underneath it. You put in what you're looking to find, and hit search and boom, you find it. Easy. Google understands that customers use them for one reason, to have a problem solved, and therefore, that’s what they deliver, without all the frills that other search portals like Aol or Yahoo! try to offer.

Your opportunity right now is to figure out the main one or two reasons people visit your website, because despite what you might think, your customers probably have only those one or two things on their mind when they visit you.

If you visit the home page of Orbtiz.com, you’re probably there to do one of a few things only. Book a flight, find a car, or make a hotel reservation. Possibly all three at once. But honestly, that’s pretty much it, right? I would bet that 99% of their traffic is trying to do one of those things. The same goes for you and your website, blog, membership site or anything you produce online.

What exactly are your customers looking for? You need to find out and find out right now! Check your analytics (I recommend Google Analytics, it's free! www.Google.com/Analytics) to find out things like the most viewed pages of your website, as well as the most exited pages too. You may find out that 90% of your visitors are focusing on the free white paper download page and ignoring the other pages you thought were important. That’s great news! Now, you at least know what your customers want. And now you can make it easier for them to get it. You may also find out that a large percentage of your visitors always leave your website on one specific page, giving you the insight that perhaps they aren't finding what they're looking for, getting frustrated, and surfing away. That's bad.

So what should you do with that knowledge to make things easier for your visitor, and better for your business? If you're getting a lot of traffic to your free white paper download, go ahead and take that download information and make it stand out on your home page. If done right, you'll make it as easy as possible for your visitors to get what they were looking for, and you’ll see even more downloads, and happier visitors because you didn’t make them work so hard.

Now, you may also find out that the page you really wanted your visitors to see is not being viewed enough. This could be the specials page on your e-commerce site, or the packages page on your consulting site or maybe your customer support contact information page. Whatever it may be, once you know what it is, that page obviously needs to be viewed more, and while you can’t force it down your visitors digital throats, you can redesign your page so that it limits the other choices that can distract your visitor.

Make it easy and simple, then win!

For over 15-years, Jim Kukral has helped small businesses and large companies like Fedex, Sherwin Williams, Ernst & Young and Progressive Auto Insurance understand how find success on the Web. Jim is the author of the book, "Attention! This Book Will Make You Money", as well as a professional speaker, blogger and Web business consultant. Find out more by visiting www.JimKukral.com. You can also follow Jim on Twitter @JimKukral.

1. Two Quick, Simple Social Media Tips
2. A Few Warnings When Selling Online Business Websites
3. Selling SEO Services: A Consultative Approach

Just a short post tonight.

First, off, I'm honored to be interviewed by Aaron Wall. We've had our differences and maintain some divergent opinions on a few topics, but we both have an insane passion for helping make SEO professionals better at their job and work hard to grow the credibility of SEO as a whole.

Second - we've got a lot of reason to be thankful. SEOmoz was recently named the 334th fastest growing company in the US by Inc Magazine. I was named to Seattle's 40 Under 40 List (I'm guessing it's a typo) and we've recently passed 6,000 PRO subscribers (actually, we're up over 6,300 as of today).

As amazing as all that is, nearly everyone at SEOmoz is thinking not about these milestones, but about one of our own - Jen Lopez - who noted on her Twitter feed that she's out battling cancer. We are all with you Jen - every last one of us, with all our hearts. And we agree: #fuckcancer

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1. Whiteboard Friday Interview: The Bing Team
2. Whiteboard Friday – Interview with Google’s Maile Ohye
3. Mixergy Interview

1. Google Includes Place Pages Ad Info on Placement Performance Reports
2. AdWords Makes Product Extensions Available to All U.S. Advertisers
3. Google Tweaks Product Search Just in Time for the Holidays

• lower earnings because few people are online today
• since almost nobody is online, any hours worked today are me getting ahead of the market ;)

Working hard & working long hours can almost be a disease...the web makes it easy to be addicted.

But for every person who is putting in hard work trying to help people there is another person selling image.

The big issue with the image game is the risks. As the lies pile up they corner people into a bad situation, to where they can (and do) lose everything.

If I had to take a single point of reference to help a stranger judge the difference between a hack and someone who wants to honestly help people, I would say it is this: do they encourage you to take on debt.

• If they do then there is a good chance they are the type of person who will go out of their way to screw you.
• If they do not then they are likely not a maximizer type (because if they were then they would be encouraging you to go into debt to sell you more stuff).

It is not that all debt is evil (when I got started online I was naive enough to start on a credit card), but life and markets are unpredictable. If I wasn't smart enough to get a job to cover my 6 or so months of education before going full time online who knows where I would now be. What seems like a short term gain can lead to longterm failure. We are human, and so we are flawed. Wen you have debt/leverage you have no spare parts. So if something goes wrong you are done. Nassim Taleb spoke about the importance of savings and diversity of revenues as keys to survival, while noting that the very structure of our public markets encourages risk + leverage (options encourage short term performance & volatility rather than sustained growth, and you hope the guy on the next watch is stuck holding the Madoff ponzi bag).

The falls of past empires have typically been preceded by rapid inflation in food costs. Our food supply, like most other aspects of modern day life, has been so extended as to be poisonous. Fishes soaked in chemicals literally change sex back and forth, and shrimp in the ocean (with traces of Prozac) swim toward the light - where they get ate.

Its not about fixing the conversation. Its about filling in the blanks. If people are prone to click on something that is exactly what they will get, even if it is not something they want.

We misinform kids about sex in a way that can screw up the rest of their lives. Against the will of people data is collected so that they may be stalked and harassed. If you once thought you were fat in the past, long after becoming anorexic there will still be ads reminding you how fat you are, following you around the web.

When bits of culture die the life lessons wrapped in it fade as well. Sure there may be HTML codes for emotions, but (beyond ad targeting) it is hard to reduce people to number.

Is the push toward homoginization to increase yield and chasing the lowest common denominator making people happier or more miserable?

I realize that reading the above can quickly make me sound like some ultra left-winged hippie, but the point of this post is not a political one ... rather one on the basic rule of law.

We justify (or downplay) harming ourselves, our environments, and the environments of other animals so we can have more and better. But to do this we often take on debt and leverage and put ourselves in precarious situations. Worse yet, we often have *others* decide to take on leverage for us, without our desire or permission.

Why is it that the government is <a href="http://techcrunch.com/2010/08/30/google-invests-86-million-in-low-income-housing/
">giving Google tax credits to build more low income housing while the Federal Reserve is sitting on over $1 trillion in bad mortgage paper? How can the government want to make housing cheaper / more affordable while simultaneously propping up (and thus ensuring overvaluation of) virtually the whole of the market? How can the government taking both sides of the same bet lead to anything but waste, fraud & abuse?

If you believe in efficient market theory then banking should represent a small portion of the profit pool (since banks are all dealing in the same commodity of cash). And yet the banking class keeps representing a growing portion of the profits, while the bad sides of their trades (the losses) are passed on to tax payers.

I don't mind someone else levering up with risk so long as they have to pay the consequences of their failures. But capitalism without failure is like religion without sin.

These banks threatened tanks in the street if they didn't get their bailouts.

They went so far as to say even auditing the Federal Reserve would threaten the financial system. Sorry, um, but that is exactly what the banking class did. If they are not punished for committing crimes then the lawlessness will only grow more extreme, as it has.

When the bubble popped some of these scammers, charlatans, shysters, swindlers, and tricksters claimed that "nobody saw it coming," but in fact as things started to go wrong these folks leaned into it and made it worse.

Rather than having CDOs go unsold they engaged in self-dealing & kept mixing the bad chunks in, sorta like making new sausage out of old sausage. They knew what they were doing. They intended to commit fraud:

"On paper, the risky stuff was gone, held by new independent CDOs. In reality, however, the banks were buying their own otherwise unsellable assets."
...
"One rival investment banker says Merrill treated CDO managers the way Henry Ford treated his Model T customers: You can have any color you want, as long as it's black."

Its labor day. The criminal bankers who ripped you off in the past, who are currently ripping you off with more crimes, and who will rip your children off are stealing your labor. And since neither political party cares to stop it its up to you how much you want to give...there is no end to how much they would love to take. Time for me to take a break. ;)

1. Financial Steroids
2. Embedded Structural Contempt for Personal Freedom
3. Yeah. Right. It Was the Ad That Ended Tiger’s Marriage

Last week at our annual mozinar, Ben Hendrickson gave a talk on a unique methodology for improving SEO. The reception was overwhelming - I've never previously been part of a professional event where thunderous applause broke out not once but multiple times in the midst of a speaker's remarks.

_
Ben Hendrickson speaking in last Fall at the Distilled/SEOmoz PRO Training London
(he'll be returning this year)
_

I doubt I can recreate the energy and excitement of the 320-person filled room that day, but my goal in this post is to help explain the concepts of topic modeling, vector space models as they relate to information retrieval and the work we've done on LDA (Latent Dirichlet Allocation). I'll also try to explain the relationship and potential applications to the practice of SEO.

A Request: Curiously, prior to the release of this post and our research publicly, there have been a number of negative remarks and criticisms from several folks in the search community suggesting that LDA (or topic modeling in general) is definitively not used by the search engines. We think there's a lot of evidence to suggest engines do use these, but we'd be excited to see contradicting evidence presented. If you have such work, please do publish!

The Search Rankings Pie Chart

Many of us are likely familar with the ranking factors survey SEOmoz conducts every two years (we'll have another one next year and I expect some exciting/interesting differences). Of course, we know that this aggregation of opinion is likely missing out on many factors and may over or under-emphasize the ones it does show.

Here's an illustration I created for a presentation recently to help illustrate the major categories in the overall results:

This suggests that many SEOs don't ascribe much weight to on-page optimization
_

I myself have often felt that from all the metrics, tests and observations of Google's ranking results, the importance of on-page factors like keyword usage or TF*IDF (explained below) is fairly small. Certainly, I've not observed many results, even in low competitive spaces, where one can simply add in a few more repetitions of the keyword, maybe toss in a few synonyms or "related searches" and improve rankings. This experience, which many SEOs I've talked to share, has led me to believe that linking signals are an overwhelming majority of how the engines order results.

But, I love to be wrong.

Some of the work we've been doing around topic modeling, specifically using a process called LDA (Latent Dirichlet Allocation), has shown some surprisingly strong results. This has made me (and I think a lot of the folks who attended Ben's talk last Tuesday) question whether it was simply a naive application of the concept of "relevancy" or "keyword usage" that gave us this biased perspective.

Why Search Engines Need Topic Modeling

Some queries are very simple - a search for "wikipedia" is non-ambiguous, straightforward and can be effectively returned by even a very basic web search engine. Other searches aren't nearly as simple. Let's look at how engines might order two results - a simple problem most of the time that can be somewhat complex depending on the situation.

For complex queries or when relating large quantities of results with lots of content-related signals, search engines need ways to determine the intent of a particular page. Simply because it mentions the keyword 4 or 5 times in prominent places or even mentions similar phrases/synonyms won't necessarily mean that it's truly relevant to the searcher's query.

Historically, lots of SEOs have put effort into this process, so what we're doing here isn't revolutionary, and topic models, LDA included, have been around for a long time. However, no one in the field, to our knowledge, has made a topic modeling system public or compared its output with Google rankings (to help see how potentially influential these signals might be). The work Ben presented, and the really exciting bit (IMO), is in those numbers.

Term Vector Spaces & Topic Modeling

Term vector spaces, topic modeling and cosine similarity sound like a tough concepts, and when Ben first mentioned them on stage, a lot of the attendees (myself included) felt a bit lost. However, Ben (along with Will Critchlow, whose Cambridge mathematics degree came in handy) helped explain these to me, and I'll do my best to replicate that here:

In this imaginary example, every word in the English language is related to either "cat" or "dog," the only topics available. To measure whether a word is more related to "dog," we use a vector space model that creates those relationships mathematically. The illustration above does a reasonable job showing our simplistic world. Words like "bigfoot" are perfectly in the middle with no more closeness to "cat" than to "dog." But words like "canine" and "feline" are clearly closer to one that the other and the degree of the angle in the vector model illustrates this (and gives us a number).

BTW - in an LDA vector space model, topics wouldn't have exact label associations like "dog" and "cat" but would instead be things like "the vector around the topic of dogs."

Unfortunately, I can't really visualize beyond this step, as it relies on taking the simple model above and scaling it to thousands or millions of topics, each of which would have its own dimension (and anyone who's tried knows that drawing more than 3 dimensions in a blog post is pretty hard). Using this construct, the model can compute the similarity between any word or groups of words and the topics its created. You can learn more about this from Stanford University's posting of Introduction to Information Retrieval, which has a specific section on Vector Space Models.

Correlation of our LDA Results w/ Google.com Rankings

Over the last 10 months, Ben (with help from other SEOmoz team members) has put together a topic modeling system based on a relatively simple implementation of LDA. While it's certainly challenging to do this work, we doubt we're the first SEO-focused organization to do so, though possibly the first to make it publicly available.

When we first started this research, we didn't know what kind of an input LDA/topic modeling might have on search engines. Thus, on completion, we were pretty excited (maybe even ecstatic) to see the following results:

Correlation Between Google.com Rankings and Various Single Metrics

(the vertical blue bars indicate standard error in the diagram, which is relatively low thanks to the large sample set)
_

Using the same process we did for our release of Google vs. Bing correlation/ranking data at SMX Advanced (we posted much more detail on the process here), we've shown the Spearman correlations for a set of metrics familiar to most SEOs against some of the LDA results, including:

• TF*IDF - the classic term weighting formula, TF*IDF measures keyword usage in a more accurate way than a more primitive metric like keyword density. In this case, we just took the TF*IDF score of the page content that appeared in Google's rankings
• Followed IPs - this is our highest correlated single link-based metric, and shows the number of unique IP addresses hosting a website that contains a followed link to the URL. As we've shown in the past, with metrics like Page Authority (which uses machine learning to build more complex ranking models) we can do even better, but it's valuable in this context to just think and compare raw link numbers.
• LDA Cosine - this is the score produced from the new LDA labs tool. It measures the cosine similarity of topics between a given page or content block and the topics produced by the query.

The correlation with rankings of the LDA scores are uncanny. Certainly, they're not a perfect correlation, but that shouldn't be expected given the supposed complexity of Google's ranking algorithm and the many factors therein. But, seeing LDA scores show this dramatic result made us seriously question whether there was causation at work here (and we hope to do additional research via our ranking models to attempt to show that impact). Perhaps, good links are more likely to point to pages that are more "relevant" via a topic model or some other aspect of Google's algorithm that we don't yet understand naturally biases towards these.

However, given that many SEO best practices (e.g. keywords in title tags, static URLs and ) have dramatically lower correlations and the same difficulties proving causation, we suspect a lot of SEO professionals will be deeply interested in trying this approach.

The LDA Labs Tool Now Available; Some Recommendations for Testing & Use

We've just recently made the LDA Labs tool available. You can use this to input a word, phrase, chunk of text or an entire page's content (via the URL input box) along with a desired query (the keyword term/phrase you want to rank for) and the tool will give back a score that represents the cosine similarity in a percentage form (100% = perfect, 0% = no relationship).

When you use the tool, be aware of a few issues:

• Scores Change Slightly with Each Run
  This is because, like a pollster interviewing 100 voters in a city to get a sense of the local electorate, we check a sample of the topics a content+query combo could fit with (checking every possibility would take an exceptionally long time). You can, therefore, expect the percentage output to flux 1-5% each time you check a page/content block against a query.
• Scores are for English Only
  Unfortunately, because our topics are built from a corpus of English language documents, we can't currently provide scores for non-English queries.
• LDA isn't the Whole Picture
  Remember that while the average correlation is in the 0.33 range, we shouldn't expect scores for any given set of search results to go in precisely descending order (a correlation of 1.0 would suggest that behavior).
• The Tool Currently Runs Against Google.com in the US only
  You should be able to see the same results the tool extracts from by using a personalization-agnostic search string like http://www.google.com/xhtml?q=my+search&pws=0
• Using Synonyms, "Related Searches" or Wonder Wheel Suggestions May Not Help
  Term vector models are more sophisticated representations of "concepts" and "topics," so while many SEOs have long recommended using synonyms or adding "related searches" as keywords on their pages and others have suggested the importance of "topically relevant content" there haven't been great ways to measure these or show their correlation with rankings. The scores you see from the tool will be based on a much less naive interpretation of the connections between words than these classic approaches.
• Scores are Relative (20% might not be bad)
  Don't presume that getting a 15% or a 20% is always a terrible result. If the folks ranking in the top 10 all have LDA scores in the 10-20% range, you're likely doing a reasonable job. Some queries simply won't produce results that fit remarkably well with given topics (which could be a weakness of our model or a weirdness about the query itself).
• Our Topic Models Don't Currently Use Phrases
  Right now, the topics we construct are around single word concepts. We imagine that the search engines have probably gone above and beyond this into topic modeling that leverages multi-word phrases, too, and we hope to get there someday ourselves.
• Keyword Spamming Might Improve Your LDA Score, But Probably Not Your Rankings
  Like anything else in the SEO world, manipulatively applying the process is probably a terrible idea. Even if this tool worked perfectly to measure keyword relevance and topic modeling in Google, it would be unwise to simply stuff 50 words over and over on your page to get the highest LDA score you could. Quality content that real people actually want to find should be the goal of SEO and Google's almost certainly sophisticated enough to determine the different between junk content that matches topic models and real content that real users will like (even if the tool's scoring can't do that).

If you're trying to do serious SEO analysis and improvement, my suggested methodology is to build a chart something like this:

SERPs analysis of "SEO" in Google.com w/ Linkscape Metrics + LDA (click for larger)

Right now, you can use Keyword Difficulty's export function and then add in some of these metrics manually (though in the future, we're working towards building this type of analysis right into the web app beta).

Once you've got a chart like this, you can get a better sense of what's propping up your competitors rankings - anchor text, domain authority, or maybe something related to topic modeling relevancy (which the LDA tool could help with).

Undoubtedly, Google's More Sophisticated than This

While the correlations are high, and the excitement around the tool both inside SEOmoz and from a lot of our members and community is equally high, this is not us "reversing the algorithm." We may have built a great tool for improving the relevancy of your pages and helping to judge whether topic modeling is another component in the rankings, but it remains to be seen if we can simply improve scores on pages and see them rise in the results.

What's exciting to us isn't that we've found a secret formula (LDA has been written about for years and vector space models have been around for decades), but that we're making a potentially valuable addition to the parts of SEO we've traditionally had little measurement around.

BTW - Thanks to Michael Cottam, who suggested the reference of research work by a number of Googlers on pLDA. There are hundreds of papers from Google and Microsoft (Bing) researchers around LDA-related topics, too, for those interested. Reading through some of these, you can see that major search engines have almost certainly built more advanced models to handle this problem. Our correlation and testing of the tool's usefulness will show whether a naive implementation can still provide value for optimizing pages.

For those who'd like to investigate more, we've made all of our raw data available here (in XLS format, though you'll need a more sophisticated model to do LDA). If you have interest in digging into this, feel free to email Ben at SEOmoz dot org.

How Do I Explain this to the Boss/Client?

The simplest method I've found is to use an analogy like:

If we want to rank well for "the rolling stones" it's probably a really good idea to use words like "Mick Jagger," "Keith Richards," and "tour dates." It's also probably not super smart to use words like "rubies," "emeralds," "gemstones," or the phrase "gathers no moss," as these might confuse search engines (and visitors) as to the topic we're covering.

This tool tries to give a best guess number about how well we're doing on this front vs. other people on the web (or sample blocks of words or content we might want to try). Hopefully, it can help us figure out when we've done something like writing about the Stones but forgetting to mention Keith Richards.

As always, we're looking forward to your feedback and results. We've already had some folks write in to us saying they used the tool to optimize the contents of some pages and seen dramatic rankings boosts. As we know, that might not mean anything about the tool itself or the process, but it certainly has us hoping for great things.

p.s. The next step, obviously, is to produce a tool that can make recommendations on words to add or remove to help improve this score. That's certainly something we're looking into.

p.p.s. We're leaving the Labs LDA tool free for anyone to use for a while, as we'd love to hear what the community thinks of the process and want to get as broad input as possible. Future iterations may be PRO-only.

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1. Google Asserts That Keyword Meta Tags are NOT Used in Rankings
2. New & Interesting Insights Into Google Rankings & Spam from Pubcon
3. Google Dominates in Hitwise December 2009 Rankings

Today, I want to share two pieces of advice that are particularly useful to certain types of business - and will be exceptionally quick to implement. I've also created a free download that might help some people implement one of these ideas even more quickly.

About two years ago, I made a recommendation to a client in the UK, and I've just seen it used by a hotel in the USA. If your business offers public computers with internet access - such as those in hotel lobbies, libraries, etc - this is for you:

Tip 1: Put up a sign, next to your public computers, with a call to action; typically this could be something like 'Find us on Facebook' or 'Follow us on Twitter'.

Here's such a poster in use, at the Ledgestone Hotel in Yakima. (Click the image to embiggen.)

Sadly, it doesn't look like the Ledgestone is doing much with their Twitter account; this probably disappoints people who go to their page, and so they don't end up with as many followers as they could do. Remember - getting people to your Twitter page (or Facebook, or whatever else you're asking them to do) is only the first stage - there has to be something there for them when they arrive.

The second tip is more for people who offer wi-fi - this could be all manner of hotels, conference venues, airports, aeroplanes, train stations, coffee shops, etc. For places that offer free wi-fi, this can work even better:

Tip 2: You control the first page visitors see after logging on to your wi-fi. Don't waste this with a dull message; make the page interesting, and put some calls to action on there.

People have probably logged on to do something - but many will welcome a distraction - particularly if you keep the request brief. Create a nicely styled, but simple page, and add a couple of message on there. Some examples could include:

• Follow us on Twitter / Like us on Facebook: you could incentivize this, for example: if you're a coffee shop, then offer a free latte to new followers
• Sign up to our email newsletter: this will only take them a second if you make sure the form is right there on the page, and again this can be incentivized
• Don't forget to check in on foursquare: ideal for almost any location, and this is as good a time as any to remind them to check in
• If you're enjoying your stay, please review us: particularly useful for hotels, where online reviews can increase visibility; I'll go into a little more detail about this below.

There can be some issues with sites noticing that a lot of people from the same IP are visiting, particularly when it comes to review services. Local search expert David Mihm advised me that he's heard Yelp in particular does try to filter our multiple reviews from the same IP, and that TripAdvisor's fraud rules do include clauses that might get you into trouble (such as offering incentives for people to write reviews is not permitted.)

I'd recommend that there are two steps around this type of issue:

1. Try to appeal for reviews only from people who already have accounts on those sites (e.g.: "If you're a Yelp member, please review us here...." or "If you have a Google account, please leave a review here..."
2. Make this 'post-wifi-login' page available on the public internet; review sites should be able to recognize that lots of people are being referred to your page from the same URL - if it's public then they'll be able to visit that page, and should figure out what is going on.

I've built a quick free template for you to to download as a starting point. You can visit the file, or download it, by clicking this link: free wifi login CTA page.

(That was created based on a template from LayoutGala; I'm not going to add any licence to it, other than use it however you want. You should change the image that are in it to be local files at the very least.)

Honestly, it doesn't take long to print off a couple of small posters (or even to publish a nice wifi login page) so I'll hope to see social-media CTAs cropping up all over the place soon. :)

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