Slides and Video Cover What You Need to Know About Search

A client asked me to prepare a one-hour seminar on the basics of search engine optimization (SEO), and I thought it was worth sharing. I live in Birmingham and was having a hard time find the best SEO in Birmingham, until I came across This is more than your standard chalk talk. I pulled together slides from several presentations I’ve used over the last few years, updated them and wrote a complete script, which is included as slide notes in the in the PowerPoint. You can download the presentation and read the notes or watch the video.

I’m not an SEO expert by any stretch, but I’ve learned a lot by osmosis. For those who are mystified by Google magic, this deck will get you up to speed. If you’re already a guru, skip it and head to more advanced sites like Search Engine Land, SEOmoz, TopRank or Biznology.

Thanks to Mike Moran, HubSpot and McDougall Interactive for permitting me to steal from them.

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Cool & Useful Sites for the Holidays

Webby AwardsThe folks at the Webby Awards sent along a super-helpful list of Web resources to use over the holidays. They range from social shopping to gift recommendations to real-time TV and music sharing. While I was familiar with several of these sites, I hadn’t heard of gems like, Wantful and Trippy. Definitely bookmarkable. The descriptions below were provided by the Webby Awards.

1. Skype 

Video chatting is now a standard activity for most Internet users – in fact, earlier this year, Skype reported that their users log 300 million minutes of video calls daily. Skype has recently added a new multi-party platform that allows up to 10 people to video chat with each other, which is a great way to get the family together, even if you’re all far away from each other.

2. Google+ Hangouts

Yet another way to connect groups of people over video chat – but Hangouts also enable the chat participants to share and enjoy digital content like YouTube videos in real time.

3. Crackle

Sony has brought together two of its popular platforms by creating virtual movie theaters on Playstation 3 that stream content from Crackle – and it’s planning to add more digital hangouts later this year.

4. brings together the social experience of the Web and music. Users can create or join listening rooms for friends – or strangers – and DJ their favorite songs for each other.

5. YapTV

A great app that brings people together around their favorite TV shows – it shows every program on television at any moment and lets you socialize with other viewers. It pulls in tweets about the show and has a built-in chat functionality so you can talk while you watch. This is especially useful for every “Elf” re-run on TBS or if you’re sucked into another “A Christmas Story” 24-hour-marathon.


Through sites like this, shopping online is no longer an isolated event. Shopping online is now social. These sites allow you converse with friends (through Skype and chat), compile lookbooks for your friends and family’s seal of approval, and most importantly, buy online.

7. SocialVest

SocialVest is an online retail platform that allows customers to buy and give at the same time. With SocialVest, you can make purchases at your favorite stores – like Target, Walmart, Bloomingdales, and more – and a percentage of all your purchases will go to a charity of your choice.


Make someone’s day brighter with this site that allows you to send a lucky person a gift of your choosing. All you need to submit is your first name, general location, and a picture of the gift you’re sending, and the site will generate a random address.


The site suggests an array of thoughtful gifts based on information you provide about the recipient – everything from age and relationship status to how often the cook and their level of neatness.


With a well-designed, streamlined interface and smart use of filters, Hipmunk makes it easy to find the right flight or the best hotel. The site also has an app available for your phone or tablet device.


It makes it easy for you to get recommendations and tips for what to do (whether you are heading home for the holidays or on a dream vacation and have a nice picnic and bring your cooler from Survival Cooking List of Best Coolers) from your friends who already know you and your interests and needs, helping you travel better.


Whether it’s a 6-hour flight home or over-the-river-and-through-the-woods, every trip is a little shorter with good book. Now, Amazon allows you to share your favorite books with your friends. Each loan lasts 14 days and are automatically returned to your library at the end.

How Will Computers Serve Us in 2020?

Live-blogging from the IBM Watson University Symposium at Harvard Business School and MIT Sloan School of Management. Additional coverage is on the Smarter Planet Blog. .

Panel discussion: What Can Technology Do Today, and in 2020?

Moderator: Andrew McAfee – MIT Sloan, CDB

Panelists: Alfred Spector, Google; Rodney Brooks, MIT, Heartland Robotics, David Ferrucci,IBM

Alfred Spector, Google
Alfred Spector, Google

Spector: We focused in computer science for many years on solving problems where accuracy and repeatability was critical. You can’t charge a credit card with 98% probability. We’re now focusing on problems where precision is less important. Google search results don’t have to be 100% accurate, so it can focus on a bigger problem set.

When I started in computer science, It was either a mathematical or an engineering discipline. What has changed is that the field is now highly empirical because of all of that data and learning from it. We would never have thought in the early days of AI how to get 4 million chess players to train a computer. You can do that today.

The Next Big ThingThis is one in a series of posts that explore people and technologies that are enabling small companies to innovate. The series is underwritten by IBM Midsize Business, but the content is entirely my own.

Brooks: Here at MIT, all students take machine learning because it’s that important.

McAfee: Was there a turning point when you decided the time was right to take these empirical approaches?

Brooks: It was in the 90s. The Web gave us the data sets.

Ferrucci: Watson was learning over heuristic information. Plowing through all those possibilities through sheer trial and error was too big. You have to combine inductive and deductive reasoning.

Brooks: It’s easy to get a plane to fly from Boston to Los Angeles. What’s hard is to get a robot to reach into my pocket and retrieve my keys.

McAfee: Why does the physical world present such challenges?

Brooks: In engineering, you have to set up control loops and you can’t afford for them to be unstable. Once a plane is in the air, the boundaries of differential equations don’t change that much. But when reaching into my pocket, the boundaries are changing every few milliseconds.

McAfee: The things that 2-year-old humans can do machines find very difficult, and the things that computers can do humans find very difficult.

Rodney Brooks, MIT

Rodney Brooks, MIT

Brooks: One thing we have to solve is the the object recognition capabilities of a two-year-old child. A child knows what a pen or a glass of water is. There is progress here, but it’s mainly in narrow sub-fields. Google cars are an example of that. They understand enough of road conditions that they can drive pretty well.

Spector: We’re looking to attack everything that breaks down barriers to communication. Example: With Google Translate, we eventually want to get to every language.

Another is how to infer descriptions from items that lack them. How do you infer a description from an image? We’re at the point where if you ask for pictures of the Eiffel Tower, we’re pretty good at delivering that.

A third thing is to make sure that information is available always from every corpus, whether it’s your personal information, information in books or information that’s on the Web. We want to break down those barriers while also preserving property rights. How many times have you searched for something and you can’t find it? I turns out it’s in a place where you weren’t looking. When you combine that with instantaneity of access, you can be on the street and communicate with someone standing next to you in the right language and the right context. You can go to a new city where you’ve never been before and enjoy that city no matter where it is.

McAfee: You think in five years I’ll be able to go to Croatia and interact comfortably with the locals?

Spector: Yes.

Brooks: We think manufacturing is disappearing from the US, but in reality there is still $2 trillion in manufacturing in the US. What we’ve done is go after the high end. We have to find things to manufacture that the Chinese can’t. What this has led to is manufacturing jobs getting higher tech. If we can build robotic tools that help people, we can get incredible productivity. The PC didn’t get rid of office workers did; it made them do things differently. We have to do that with robots.

We can take jobs back from China but they won’t be the same jobs. That doesn’t mean people have to be engineers to work. Instead of a factory worker doing a repetitive task, he can supervise a team of robots doing repetitive tasks.

My favorite example is automobiles. We’ve made them incredibly sophisticated but ordinary people can still drive.

Spector: It’s machines and humans working together to build things we couldn’t build separately. At Google, we learn how to spell from the spelling mistakes of our users.

Ferrucci: This notion that the collaboration between the health care team, the patient and the computer can result in a more effective diagnostic system as well as one that produces more options. Everyone is well informed about the problems, the possibilities and why. I think we’re capable of doing that today much better than we did in the past. This involves exploiting the knowledge that humans use to communicate with each other already. This gets you as a patient more involved in making better decisions faster. It’s collaborating better with the experts.

McAfee: Don’t we need to shrink the caregiver team to improve the productivity of the system?

Ferrucci: The way you make the system more productive is to make people healthier. Does that involve a smaller team? I don’t know, but I do know you get there by focusing on the right thing, which is the health of the patient.

Andrew McAfee, MIT Sloan

Andrew McAfee, MIT Sloan

McAfee: If you could wave a wand and get either much faster computers, much bigger body of data or a bunch more Ph.D.’s on your team, which would you want?

Brooks: Robotics isn’t limited by the speed of computers. We’ve got plenty of data, although maybe not the right data. Smart Ph.D.’s are good, but you’ve got to orient them in the right direction. The IBM Watson team changed the culture to direct a group of Ph.D.s the right way. I think we’d be better off if universities were smaller and did more basic research that companies like IBM would never do.

Spector: When many of us in industry go to the universities, we’ve often surprised that the research isn’t bolder. Perhaps that has to do with faculty reward issues. We envision that there’s going to be need for vastly more computation. I’m sure Google data centers will continue to grow. If you stay anywhere near Moore’s law, these numbers will become gigantic. The issues will relate to efficiency: Using the minimum amount of power and delivering maximum sustainability.

With respect to people, there’s a tremendous amount of innovation that needs to be done. Deep learning is a way to iteratively learn more from the results of what you’ve already learned. Language processing is a way to do that. We learn from the results of what we do. Finally, data is going to continue to grow. We bought a company with a product called Freebase where people are creating data by putting semantic variables together. Just learning the road conditions in New York from what commuters and telling us is crowdsourced data, and that’s enormously useful.

David Ferrucci, IBM Research

David Ferrucci, IBM Research

Ferrucci: We need all three, but in order, it’s researchers, data, machines. Parallel is processing is important, but it’s less important than smart people.

McAfee: Do computers ultimately threaten us?

Brooks: The machines are going to get better, but for the foreseeable future we’ll evolve faster. There’s a lot of work going on in the area of putting machines into the bodies of people. I think we’re going to be merging and coupling machines to our bodies. A hundred years from now? Who the hell knows?

Spector: There will be more instantaneity, faster information. We can embrace that, like we did central heating, or reject it. I think we’re on a mostly positive track.

Audience question: What’s the next grand challenge?

Ferrucci: I think the more important thing is to continue to pursue projects that further the cause of human-computer cooperation. We tend to go off after new projects that require entirely different architectures, and that hurts us. I’d rather we focus on extending and generalizing architectures we’ve established and focus on applying it to new problems.

Brooks: I’d like to see us focus on the four big problems we need to solve.

  • Visual object recognition of a 2-year-old
  • The spoken language capabilities of a four-year-old
  • The manual dexterity of a six-year-old. Tying shoelaces is a huge machine problem
  • The social understanding of an eight-year-old child.

Facebook Grows Up

Thumbs-up logoThe race to socialize the Web got more intense this week with a major new announcement from Facebook that plays to its strengths at Google’s expense. This is shaping up to be an epic battle and the good news is that users stand to benefit regardless of who wins.

On the surface, Facebook’s move to make its famous “Like” button a fixture on many other websites seems unremarkable.  But it’s really the tip of the iceberg for future services that Facebook calls “Open Graph” and which will strengthen its position as the power broker of the social Web. Moreover, the way Facebook is approaching its strategy is a notable evolution from its past behavior.  This company is growing up fast and Google had better be on its toes.

What does it mean to “socialize the Web?”  As I’ve written in the past, the next great evolution of the Internet will be to move beyond static websites and toward services that travel with the user.  The most important of these will be persistent connections to the members of one’s social circle.  Basically, the experiences and advice of the people we trust will become part of our information-gathering experience, influencing and guiding us whenever we choose to consult them.

Facebook’s new features are an important first step. Visitors to a partner website will now be able to register their recommendations by pressing the famous blue button and having that endorsement added to their Facebook profile as well as to the destination website.  Their friends will then be able to see that opinion when they visit the parter site or check the person’s profile or news feed on Facebook.

Services that choose to partner with Facebook will benefit from immediately adding content from Facebook’s 400 million-plus members with minimal effort. They’ll also enjoy easier cross-enrollment with the social network. Facebook, Google, Twitter and LinkedIn have all been nibbling around the integration issue with features like Facebook Connect and Google Friend Connect, which enable people to log onto one social network using credentials from another.  Now Facebook is making this cross-registration so easy that it says it will discontinue Facebook Connect entirely.

Services like the consumer review site Yelp, which is one of Facebook’s early partners, are positively bubbly about these new developments. Yelp believes that the addition of Facebook friend recommendations will deepen the quality of its reviews and juice its membership. Yelp members will benefit from having their friends’ advice appear next to that of the strangers who now contribute most of the site’s content. Another partner, CNN, stands to gain from having Facebook members recommend stories and drive traffic to its website without any additional promotion of CNN’s part. Meanwhile, Facebook made it clear in its announcement that the “Like” button is just the first of many possible extensions of its service to other partners.

Good Citizen

One aspect of this week’s announcement that particularly impressed me was Facebook’s decision to work with partners.  CEO Mark Zuckerberg (left) declared that “In the first 24 hours alone we’re going to serve one billion ‘Like’ buttons on the Web,”  meaning that Facebook has done its homework to enlist partners that will give its strategy instant legitimacy. This is an impressive evolution for a company that has a history of being arrogant and difficult to deal with.  It also demonstrates that Facebook is aware of the need to add value to other services instead of trying to steamroll them.

Contrast that with Google, which has appeared positively inept in some of its recent web socialization attempts.  Google Buzz has none.  Google Wave, which sounded good in theory, has been a flop in practice. I don’t know anyone who uses it. Knol, which was once seen as a competitor to Wikipedia, is all but invisible. Sidewiki attempts to add integrate friends’ recommendations into the Web browsing experience, but implementation is awkward and website owners may see it as more of a threat than a benefit.

In short, Google’s reputation as a good partner seems to be giving way to the kind of go-it-alone approach that’s typical of market dominators. This is happening just as Facebook is learning the value of collaboration. All in all, this is not a good omen for Google. While a company with 70% of the search market is in no immediate trouble, history has shown that even dominant companies can fall fast when the rules change. Facebook is trying to change the rules.

Why is Facebook’s initiative good for Joe and Jane Web user? Because it continues to move the value equation toward quality content. The more that online success is tied to peer endorsements, the more incumbent it is upon content providers to deliver value that others can recommend. The influence of marketing dollars continues to ebb while the influence of good information grows. What could possibly be bad about that?

Be Inclusive Or Be Irrelevant

In my column in BtoB magazine this month I discuss the contrasting media relations styles of two giants of the Internet age: Google and Apple. The column focused specifically on their communications styles, but I believe the business tactics of these two starkly different but successful companies have bigger significance.

Google and Apple are diametrically opposed in many respects. Apple creates delightful experiences. Its products are proprietary, closed and self-contained, but people love using them because they not only work but seem to function the way humans expect. Apple is a technology company whose vision is rooted in human-friendly design.

Google’s vision is rooted in the potential of technology. The company produces an amazing array of products, ranging from mapping software to CAD design to medical records organizers. Google shares its ideas quite openly in public “labs” and is also prone to ending public experiments with little notice or explanation. Even its self-deprecating error messages are emblematic of the corporate culture, as if to say “So it didn’t work; we’ll make it better.”

The public-facing strategies these companies employ also couldn’t be more different. Apple holds its new product plans close to the vest and reveals them with fanfare at elaborate press conferences that generate months of media speculation. The company may only hold a couple of press conferences a year, but you can be sure they’re memorable.

Apple not only doesn’t use social media, it has actively litigated against bloggers who have revealed sensitive information. The strategy works well for Apple because its rabid base of fans is more than happy to indulge in speculative frenzy and drive awareness that no amount of advertising could buy.

In contrast, Google rarely holds press conferences. Most of its products are announced in a low-key style via blogs. Its developers and product managers work the long tail through one-on-one interviews and frequent speaking engagements. The company uses every social media outlet it can but shuns the media spotlight.

So Which Are You?

Is your company Apple or Google? Most businesses model their public personae on the Apple example. Their plans are shrouded in secrecy, access to executives is granted only to the top media and leaks are dealt with harshly out of fear that they could compromise the goal of being first to market. The theory is that the market is hungry for information, so it’s best to withhold news until it can have the greatest impact.

That strategy works for Apple but not for most businesses. Today, customers are swimming in information and if they don’t get insight about where you’re going, they simply move to someone else. Companies that build products behind closed doors risk becoming irrelevant because no one talks about them. What’s more, they lose the advantage of involving customers in a process that can not only make their products better but form the basis for a word-of-mouth marketing force.

How about being first to market? That benefit is vastly overrated. History has demonstrated that the only advantage of being an early mover is that it gives you the opportunity to make mistakes that others learn from. Apple’s sole first-to-market experience – the Newton – was also its most notable failure. The history of technology markets in particular is littered with businesses that created innovations that others later made successful.

In a world of plentiful information, the winners are those that do the best job of talking about their innovations before they reach the market. Prospective customers want to be involved in the process, and they punish those businesses that don’t indulge them. Look at the companies that are making headlines today and you’ll find nearly all of them have adopted an open and inclusive path to the market.

The Apples of the world are few and far between. Nearly everyone would like to be an Apple, but few will ever get the chance.

Knol's greed appeal will make it a winner

In the two weeks since Google announced plans to unveil a Wikipedia-like encyclopedia called Knol, the blogosphere has been buzzing about its potential impact. Is this the Wikipedia-killer? A nefarious attempt to undermine media companies? A market-share play by a near-monopoly?

In my opinion, it’s none of those things. Knol is just a good idea that fills a gap in the market and that is likely to become a rich and useful alternative to Wikipedia. If Google and its contributors make money in the process, what’s wrong with that?

Knol will succeed because (for lack of a better term) it exploits the greed factor in community knowledge-sharing. Think of Wikipedia as public television or radio: it’s a public information source that is endearing, in part, because it’s so free of commercial interest. Sure, some people do use Wikipedia for business benefit, but most do so for the sake of sharing knowledge and contributing to the public good. Wikipedia’s anonymity is a virtue in that respect. There will always be value to that model and an audience for it.

Knol is a commercial play. According to sketchy details provided so far by Google, users will be able to attach bylines and profiles to their contributions and submit to community ratings. Articles will move up the popularity stack based upon a Digg-like process in which visitors identify the most useful content. Contributors could also see some financial reward if their work is heavily trafficked.

The fact that Knol promotes the identity of its contributors will give it significant commercial appeal, particularly for experts who don’t have the benefit of a big forum for their knowledge. I’ve written the past about an experiment called Wikibon that is a precursor to Knol. The creator of Wikibon, David Vellante, spent many years in market research and understands both the power and limitations of that model.

Market research firms charge high fees because they have a reputation for quality. The analysts who work there command big salaries and enjoy considerable influence in their markets. It’s the think-tank model and it’s tried and true.

The problem with think tanks is that they shut out the vast majority of potential experts. In most business-to-business markets, there is a huge body of knowledge locked up in the minds of practitioners, consultants and small businesspeople who don’t have the wherewithal to become part of the giant research firms. Their expertise is available only to the small number of people they can reach through whatever means they have available.

Wikibon is a long-tail experiment that tries to tap into that knowledge and create a quality information resource at a cost that’s potentially much lower than that of the think tanks. The idea is to remove all of the organizational overhead and just let people showcase their own expertise. If they do it right, they can grow their professional profile and improve their chance of landing good jobs or consulting assignments.

The same factors will apply to Knol, and that’s why it will be so successful. Few Web properties have Google’s capacity to showcase individual experts. There are many blogger networks out there, but Knol should quickly become the biggest blogger network of them all.

For individuals with the time, skill and savvy to promote themselves through a vehicle like this, the payoff could be significant. That’s why I say that Knol appeals to the greed factor. People will continue to contribute to Wikipedia because it reaches a vast audience. They will contribute to Knol because it promotes their personal interests. There will be a place for both models on the Web. There’s no reason that either has to be successful at the expense of the other.

A look ahead at tech PR in 2008

In the final Tech PR War Stories podcast of 2007, David Strom and I stretch out a little and ruminate on what’s ahead for 2008. Here, in no particular order, are our predictions. It’s going to be another wild year for tech PR, but one in which savvy PR pros can elevate their status with employers and clients:

  • The end of beats at technology publications. Reporters will become more generalized and contract experts will contribute more of the specialized coverage;
  • Fragmentation in coverage of technology; it will come from a variety of sources;
  • Google will buy Second Life and Skype. Paul sees big opportunities for the search giant to leverage those core technologies into franchise businesses;
  • PR pros will have to do a better job at creating meaningful relationships with press. They’ll also have to reach out to unexpected places for coverage;
  • Increasing concerns about privacy in social networks. Facebook’s Beacon was just the tip of the iceberg;
  • The Wall Street Journal will become a free service. Rupert Murdoch has already made it clear that he wants to take the paper in this direction and that will have big implications for tech coverage as the Journal asserts itself as a major online news force;
  • The rise of social search, addressing some of the inherent limitations of search. Mahalo and WikiaSearch are early proofs of concept of an evolution of the search utility;
  • Vendors will increasingly become publishers and will need help from PR people to create useful and interesting content.

Download the podcast here (19:00).