When I say that search and social are interdependent, I don’t just mean that any effective digital strategy ensures that you do both well. Of course, they are both strong drivers of relevant traffic to your sites. But I also mean that they are interrelated. That is, you can’t do search effectively without an effective social strategy and you can’t do social effectively without an effective search strategy. Since this is a controversial position, allow me to explain now and explain after the jump.
Continue reading “How Search and Social are Interdependent”Book Review: Content Strategy by Bailie and Urbina
It’s not every day that I’m extensively interviewed for a book. And it’s even more rare that I thoroughly approve of the book in which I am interviewed. So I’m thrilled to have the opportunity to read and review Content Strategy: Connecting the dots between business, brand, and benefits by Rahel Bailie and Noz Urbina.
My updated bookshelf with Content Strategy taking its rightful place.
The book is a comprehensive approach to corporate content strategy from the perspective of two seasoned consultants, with decades of hard-won content strategy experience between them. (Full disclosure: I am a friend of Rahel’s and her publisher sent me the book for review.)
The best part of the book is its collection of case studies, which show how companies large and small have used content strategy to improve their businesses. The message that comes out of these stories, and is reinforced through clear and compelling prose, is that content is one of your most precious corporate assets. Investing in good content strategy doesn’t just help companies save costs over time, it helps them drive revenue, build brand loyalty, and manage risk and compliance. And the alternative to good content strategy can be disastrous.
One of the biggest challenges for content strategists is convincing their executives to invest in the people and tools they need to produce, publish and maintain quality content for customers. The authors do a great job of building effective business cases based on the often under appreciated value of content. After the jump, I’ll outline three ways the book helps content strategists demonstrate the value of their work.
Cutting costs
Of course, content is very expensive. Good writing is one of the few things that can’t be automated. We can use tools like Acrolinx to automate some of the editing and translation efforts. We can implement governance to ensure that we are not creating duplicate content. We can figure out ways of building responsive designs that enable more automated content sharing and curation. We can reduce call volumes at the support centers by answering customer questions with better content experiences. All these efforts will help you cut costs, and so pay for themselves over time. But there’s no substitute for client-centric, clear, concise, compelling, credible, conversational, and clean content.
Quality content is expensive to produce because it requires a lot of smart people with excellent writing, editing, and content strategy skills. If the only way you can get funding for content strategy is through cost savings, one key expectation is that you will reduce head count for writers and editors. This can ultimately hurt the business by reducing content quality over time. That’s why I’m pleased that the authors spend so much space on other ways content can generate return on investment (ROI).
Driving revenue
I’m especially pleased that the authors gave our practices at IBM so much space in the book (pp. 107-109). It all started with a meeting with Rahel over breakfast at Intelligent Content 2010, in which I explained how we get funding for strategic content initiatives at IBM–revenue. The way we grow our business with content is by mining the search and social behavior of our target audience (mostly prospects), and building content experiences for them. If these experiences help them complete their information tasks in a pain-free way, they start to develop loyalty to our brand. This loyalty results in completed response forms on our site, which results in new leads for our business. When new leads result in sales, we grow our business.
Of course, we also need to close the loop with existing customers. This means improving the customer experience with content for the entire customer journey, from learning to solving to comparing to purchasing to installing to optimizing to getting support, and looping back to learning again when it’s time to upgrade. Every customer who has an excellent content experience with the dozens of assets she touches in her journey becomes an advocate for the brand.
Building brand loyalty
This is really where the book shines. It is unique in stressing the long view when it comes to building content strategies that result in ROI. On the ever-more-social web, customer loyalty is expressed through content. It is the way that clients and prospects help each other make better purchasing decisions. In this environment, bad content experiences not only do damage to that one customer’s loyalty, but to everyone in her network. Quality, findable, sharable content is no longer optional. It’s table stakes. If you want to win, you need to invest more than table stakes. You need to differentiate yourself from the competition by building excellent content experiences across the whole customer lifecycle. The book makes a compelling case for this, and helps content strategists tailor this message for their executives.
Conclusion
That’s only a small snapshot of a book, about which one revue could not do justice. It’s not just about ROI, it’s about best practices and governance and content management and taxonomy and SEO and translation and…. If I had one complaint, it’s that the book is a bit overwhelming. I found myself skipping and skimming a lot over aspects of the book that don’t apply to my work. And that’s OK. Good books help readers get what they need out of them. This book does that for a wide range of readers, in start-ups and large enterprises and everything in between. So I will leave you to the task of getting what you need out of the book.
I want to close with one admonishment: if you’re serious about content strategy, this book is not optional.
What is Relevance, Again?
Since before I started this blog with my co-author Frank Donatone, I’ve been engaging in a long and fruitful virtual debate with a group of people I lovingly refer to as the search haters. My latest blog about this can be found on Biznology: “Five Critical Roles that Need SEO Skills.” Not that the group of search haters is organized or has its own user group. But there is a long line of folks who are willing to trash the practice of SEO on the basis of two facts:
- SEO has sometimes been practiced by unscrupulous agencies to try to gain unfair advantage for their clients, thus this is what most SEO amounts to
- Search results are sometimes wildly irrelevant to search queries, thus search is not all that helpful in providing relevant content to audiences
I write this in the hope that I might influence a few search haters into a more sympathetic understanding of SEO. As the above Biznology post indicated, I spend the majority of my time training folks on SEO. Much of this is in countering myths 1. or 2. above. If I can preempt some of this training by influencing a few people now, I just might be able to get down to business with new hires in digital marketing sooner.
A Smashing Debate
Since I wrote the above blog post, several of my colleagues have alerted me to a couple of long and detailed blog posts in Smashingmag.com. The first is called “The Inconvenient Truth about SEO.” In it, author and apparent search hater Paul Boag makes some good points about the way SEO is sometimes practiced. But he also makes some logical and factual errors. Most of the logical or factual errors were well countered in a follow-on blog called “What The Heck Is SEO? A Rebuttal”
The most important is the counter to point 1. above. Authors Bill Slawski, Will Critchlow rightly say that this is a straw man. Most SEO is in fact practiced by people who only want the search traffic commensurate with the value of their content, using legitimate means of attaining it. SEO spam is like junk mail spam or email spam: Even though it is not representative of all SEO, we remember SEO spam (aka black hat SEO) because it is so annoying, So our tendency is to over generalize from black hat SEO to all SEO. The authors also did a good job curating the results of a poll of SEOs in describing what it is SEOs actually do.
I highly recommend that you read both posts, especially the accounts of what SEOs actually do in the rebuttal. As an SEO, I do all of those things and then some. The picture that emerges is that SEOs are really just digital strategists who will do whatever is needed to ensure that clients get ROI for their web development efforts. Since most people search for information “often or always,” being available in search results for the queries your target audience cares about is job 1. So, as I describe in Biznology and elsewhere, the role of an SEO is helping everyone else on the team understand how their work affects search results, i.e., training.
Still, the rebuttal is incomplete. I won’t take Boag’s post apart in detail. But I do want to point out a fallacy in the hopes that it will illuminate why myth number 2. above is a commonly held belief. Here is what Boag says:
Your objective should be to make it easier for people who are interested in what you have to offer to find you, and see the great content that you offer. Relevant content isn’t “great content”. Someone searches for a pizza on Google, and they don’t want prose from Hemingway or Fitzgerald on the history and origin of pizza — they most likely want lunch. An SEO adds value to what you create by making sure that it is presented within the framework of the Web in a way which makes it more likely that it will reach the people that you want it seen by, when they are looking for it.
What is Relevance, Again?
First of all, I completely agree with everything in the above quote, except the bold part. The way I read it, he is saying that content need not be great in order to be relevant. Considering that I say content quality is a proxy for relevance, the bold statement in the Boag quote is a problem for me.
Let’s revisit our definition of relevance. Content is more or less relevant to the audience to the extent that:
- It maximizes the audience’s ability to achieve their information goals
- It minimizes the effort required by the audience to achieve those goals
We unpack these two conditions in probably more detail than most of the readers of our book need. But if you are interested in the complete picture, see Audience, Relevance and Search. For most of you, it suffices to say that content is optimally relevant if it helps the audience get the information they need in the shortest possible time. (Note that it sometimes takes longer to grasp overly condensed text. So I don’t say, “in the smallest possible space”.)
There is a reading of Boag in which his quote agrees with our definition. If by placing quotes around “great content” he means to connote “literary masterpieces,” then fine. A small percentage of your audience on the web is looking for highly crafted, poetic prose. An even smaller percentage is looking for long-winded stories told from a fictional voice. Highly relevant content on the web is typically brief, to the point, and abundantly clear. (Note that this does not make it boring. It is the antithesis of boring to the audience in that it answers their most pressing questions.)
Part of my insistence on spending entirely too much space in the book explaining how web content is fundamentally unlike print content is to emphasize this point. On the web, readers are in charge of the story. It’s their story. The writer must try to understand the reader well enough to figure out what they need to complete their story, and to provide it in the easiest and quickest way. Turns of phrase and other poetic language tend to reduce relevance on the web by introducing ambiguity in a fundamentally literal medium. Worse still, internal company jargon and other brain-dead colloquial language (e.g. “leverage,” “paradigm shift,” “next generation,” etc.) defeats relevance.
If this is what Boag means, then I agree completely with his quote. But, if this is what he means, why then does he take the side of the search hater? We published our book in 2010. I’ve spoken about it at high-end conferences a dozen times. The whole industry has rallied behind the vision outlined in the book (whether they were aware of it or not). The search engines have followed suit with algorithm changes like Panda that reward relevant content as we define it and punish black hat SEO. Most decent SEOs practice it as we preach it (again, whether they’re aware of our book or not).
Can we please dispense with the myths so we can give SEO its rightful place in digital strategy?
You’re Doing it Wrong: How to Build a Great Career
I’ve had a rant stewing in me since I saw a TED Talk by Larry Smith on why you will fail to have a great career. The gist of his unpleasant talk is that you will fail to have a great career because you will compromise on what you are most passionate about. And if you don’t do what you’re most passionate about, you will never have a great career.
When I first saw the video, I said “Yes!” So much so that I posted it on my Facebook page. But after a few days, lingering doubts about it caused me to delete it from my Facebook page. These doubts have only grown in the interceding months. It took an interview with Martha Stewart in Parade magazine this past Sunday to inspire me to express these doubts in a blog post. She says:
My father was the smartest guy, he said: ‘you can do anything you set your mind to.’
I know you have all heard these words from your parents and teachers. And I don’t want to discourage you from pursuing your dreams. But I’m here to tell you if you insist on doing whatever it is that you are passionate about, you are more likely to fail to have a great career. Great careers are made by people who listen to what the world needs and who learn to provide those things. They are not necessarily made by people who create things they are passionate about and hope the world needs them. If you think that is the way things work, you are setting yourself up for disappointment.
It certainly helps to be passionate about what you do. It is important to any happy career. And you probably can’t have a great career if your work makes you miserable. But learning to do unpleasant things well, and learning to enjoy success in things for which you are not gifted are essential to cultivating a great career. If you only do what you like to do and what comes easily to you, you are likely to fail. This is the gist of my rant against Larry Smith.
Two wrong turns in the pursuit of a great career
I was a bright-eyed college student, going to school on my own nickel, working two and sometimes three jobs while taking a full load. I was technically a pre-architecure student, meaning I was taking all the core classes one takes in preparation for entering a design school. I wanted to be an architect from the time I was 8 years old because it represented that Ancient ideal combination of art and science. I loved to draw and I was good at math–Rain Man good. So it seemed like the ideal career for me. I pursued it with gusto.
When it came time to apply for design schools, I applied to two. I got an early acceptance from the Rhode Island School of Design (RISD). Based on that, I assumed my home school (The University of Minnesota) would accept me. I was years ahead of other applicants in math, science and art education, and my portfolio was praised by the RISD acceptance committee. But I really wanted to go to the U of M. With confidence, I turned down RISD and waited for my acceptance letter from the U of M. It never came. To this day, I don’t know why. I was devastated.
I took a year off to consider my options. I had a philosophy minor while I pursued pre-architecture (again, following the Ancient ideal). So when I went back to school, I became a philosophy major. I excelled, pulling a 3.9 over the two years left for my B.A. And I loved it. I reveled in abstract thinking and debating. My teachers said I had a chance to do great things in philosophy, encouraging me to apply to several grad schools. I was accepted at a few and wound up at my home school, the U of M.
I worked on a PhD in philosophy for seven years. I can’t say I was a top student. But I did good work. I served as a teaching assistant and instructor in 20 classes. I got scholarships and fellowships. I got my M.A. I was all-but-dissertation (ABD). I thought I was on my way. But the department didn’t think so. I was one of several colleagues who were told, “You will no longer be allowed to pursue a PhD at this institution.” I was devastated.
I had pursued my passions. I had focused on what I was good at. I had followed my heart. And I was 0-2 with twelve years of post-secondary education and a mountain of student debt. In both cases, I consoled myself with wise words from mentors and advisors. One architect said, “I was a top student and graduated with a B. Arch. with honors. I’ve been a mere draftsman since, working for little better than minimum wage for 15 years.” A philosophy PhD had a similar story: “I went to the top school, had a top 10 advisor, published 10 papers and a book in my first five years out of grad school. But I spent my first 10 years wandering from one-year appointment to one-year appointment.” He was one of the lucky ones. When I was shown the door, there were 350 philosophy PhDs in the United States without any kind of teaching position.
The right approach to a great career
At 31, I changed my strategy, out of necessity. The new strategy was simple: Listen to what the world needs and learn how to provide it. I took the first job I could find: As an editor for the campus newspaper. Meanwhile, I entered a degree program for Scientific and Technical Communication. My new goal was to do what no one wanted to do and no one seemed to do well: tech journalism. I got a reporter job at the paper covering the science and tech beat. I learned. It was difficult. I was never good at English growing up. In fact I was am dyslexic. But I kept at it. Slowly, my career grew. I had many set backs. But I eventually got a break. I was hired as the managing editor of ComputerUser magazine and a month later, the editor in chief (EIC) quit. I got his job. And my career has taken off from there.
It doesn’t just take off on its own, however. You have to continually listen to what the world needs andlearn to provide it. I won’t bore you with all the twists and turns of my career. But one in particular is instructive. At a certain point, I became the EIC of ibm.com. We had a survey on our site that asked people if they had achieved their goals. If not, we asked them follow-up questions. When I started, content quality and search were the two most prevalent reasons people had not achieved their goals. After two years in which I focused on content quality, the survey indicated content quality was no longer a significant issue. But search remained an issue. So I shifted my whole focus to search and learned everything I could about how to improve our client search experiences. In the process, I wrote the book on the subject (with the help of my co-authors), and continue to grow my subject matter expertise. Point is, careers evolve. If you continue to listen and learn, you can proactively evolve your career, rather than letting your career evolve in ways that restrict your opportunities.
Two key traits of a great career
You might wonder how I could choose to do something that stretched my skills so severely. How does a dyslexic man become EIC? The thing is, after 20 years in this career, I am actually better at writing and editing skills than I ever was at math. I now struggle to tutor my son in geometry and trig, two subjects I aced when I was young. Why? Because the brain is a flexible organ. It will grow and develop in ways you want it to. (Conversely, use it or lose it.) It takes long hours of practice and hard work. But eventually you can do it. In this respect, Martha Stewart’s father is right. You can do whatever you set your mind to. But the thing is, you need not have passion for it first. You can develop a passion for the things the world needs you to do.
You might also wonder how someone can succeed without having initial passion for something. That is also not easy. But passions are transient. Even those that naturally spring forth from your heart need to be cultivated, lest they become stale. Boredom is a self-fulfilling prophesy. But if you really take an interest in your subject, it will begin to delight and fascinate you. That is what happened to me with technology, journalism, and search. And this fascination continues, as humans continue their relentless pursuit of knowledge, constrained only by Moore’s Law. Also, there is no escape from tedious work. The trick is, to learn how to enjoy what might seem tedious to some. By learning to love work that others find boring, you will never be short of opportunities.
I want to close with one thought: Some of you might see a connection between the theme of our book and the theme of this blog post. The book is based on the notion that before you create content, it’s important to listen to what your audience needs. It is much more effective than writing what suits your fancy, publishing it, and hoping someone will find it useful. The most effective tool for this listening is keyword research. Listening for opportunities to grow your career is a bit more challenging than keyword research. I recommend seeing how the skills in LinkedIn grow and shrink in popularity. This is a good source of listening data on what skills are most needed in the marketplace.
The Psychology of Digital Content
I had the great fortune to attend the Cognitive Colloquium in early October of this year at the IBM Watson Research Center in Yorktown Heights, NY. It was one of those life-changing moments when you feel like you’re sitting on top of a mountain and you can see much more distant horizons. In my case, the horizon I saw involved using some of my mental energy to solve the grand problems of digital content using the methods of cognitive computing.
What are these methods ? Well, at IBM, we describe cognitive computing as a cluster of practices that use machine learning, natural language processing and high-performance computing to change the way computers work and how humans work with them. Heady stuff, I know.
Before you abandon this blog for more comfortable pursuits, please consider a ready example of this in Watson, the supercomputer that competed in Jeopardy! last year and beat the top champions the show had ever had. The IBM team taught Watson the rules of the game and he proceeded to improve his play through many months of live competition leading up to the televised show. He used natural language processing to understand the clues presented by the host, and devised likely questions for them. He used machine learning to get better and better at the game. He’s now being employed in medicine, marketing and several other domain-specific specialties, including our line of work.
Thinking, Fast and Slow by Daniel Kahneman
Job 1 for my new mission was to read Nobel Laureate Daniel Kahneman’s thick book Thinking, Fast and Slow. Kahneman was a keynote speaker at the Cognitive Colloquium. His talk triggered several new insights in me about the relationship between human psychology and content strategy. As I read the book (primarily on my train ride between my home in Beacon, NY and Grand Central station), I continue to solidify these insights. I can now articulate several of them. In the interests of space, I will cover one of them for the content strategists who are likely to read this blog. If you’re still interested, please read on.
(If you’re interested in the complete set, look for my forthcoming book: Outside-In Marketing: Using Big Data to Drive Your Content Marketing. I also highly recommend reading Kahneman when you find yourself with a hundred hours or so of unstructured time.)
The central framework of Thinking, Fast and Slow
The central thesis for Kahneman’s life’s work, spanning over forty years of research of practitioners of fields too numerous to list, is a kind of mental dualism. Our minds have two distinct systems, which Kahneman calls System 1 and System 2.
System 1 is the set of processes that happen automatically, in a flash. They are so automatic, we often can’t recall afterwards intending to do them. We just do them. Examples include the habits of driving, like putting on your turn signal prior to a turn. You don’t have to think about it, you just do it. Most of our lives and much of our communication is governed by System 1. We are faced with so much uncertainty in life and it all comes at us so fast, we need a system to make sense of it in the rough. Kahneman calls System 1 “a machine for jumping to conclusions,” because that is what it does. It judges things automatically before all the data are available.
System 2 is the logical and systematic part of our minds, which has been modeled by cognitive scientists since the discipline was conceived. Though it is accurate and precise, it is slow and lazy. There are times when we doubt the knee-jerk responses our System 1 provides. And these are the times we engage System 2 to analyze all the facts at hand and make a reasoned decision. But System 2 is so lazy, we don’t use it as much as the philosophers and other idealists like to believe. In his book, he documents decisions made by experts in a variety of fields based almost entirely on System 1 thinking, and laced with the biases that it uses to jump to conclusions.
Kahneman was the keynote speaker at the cognitive Colloquium because his framework serves as a new way to model human thinking. As he said, “If you want to build systems that think like humans, start with understanding how humans think.”
Computers have always been devices that needed to be right all the time, without fail. So of course we patterned them after System 2 thinking. The trouble is, it takes huge supercomputers to do somewhat ordinary human tasks, like scanning encyclopedic knowledge for a likely question that matches a cryptic answer. Watson takes up a decent sized room and consumes massive amounts of electricity. The machines of tomorrow need to get ever smaller and more efficient, approaching the efficiency of the human brain. To do that, we need to build systems that do much of their work like System 1, fast and imprecise. Only when accuracy is needed will they engage System 2.
Practice: How do users interact with websites?
Beyond the implications of Kahneman’s work for cognitive computing, some of his work has more direct practical applications for content strategy. Indeed, his framework can be used to approximate how users consume websites. Consider this scenario:
Lizzy is a highly educated millennial who works as an editor in the publishing field. She searches for “structured mark-up” in Google and gets a ton of results. She scans the first search engine results page (SERP) and clicks the most likely link without really reading the results. When she lands on the page, she scans it to determine if it is worth the effort. She decides that it is, and begins reading the long-form content on the page.
What does Lizzy’s mental state look like? Well, she uses both System 1 and System 2 in the process of her information journey. System 1 is the primary mechanism of her scanning and clicking behavior. Scanning SERPs and clicking is so familiar to Lizzy, it’s like using your turn signals while driving. She doesn’t need to think about it. System 2 is what she uses to read and digest the content.
A whole UX discipline has grown out of Steve Krug’s imperative, Don’t Make Me Think. If you make Lizzy think when she lands on your page, you force her to engage System 2, which is slow and lazy. Not only is Lizzy in a hurry, she really doesn’t want to waste mental energy either. If you force her to think, she will jump to the conclusion that your page is not relevant before even engaging System 2, and she’ll bounce back to the search engine to try another result.
When Lizzy does find your page relevant, she is ready to engage System 2. This means providing enough data, case studies and other stuff to help her complete her information task. Once she engages System 2, she does not want to have to go back to the SERP again. Ideally, she can get everything she needs on your site. Once she engages System 2, long-form content is what she needs.
For the longest time, we have had a raging debate in our field of whether users read on the web. All kinds of studies showed that “users don’t read” on the web, they just scan. I have tried to replicate these studies in ibm.com with mixed results. After analyzing the results, I came to a conclusion that seems obvious after the fact: If you get the Lizzy use case right, users do read on the web. They’ll even download a longish whitepaper and read it on the web if it is relevant and compelling. But if you don’t get the Lizzy use case right, they bounce off your page before reading regardless of how close the content is to the query.
I have not done a complete analysis. Provisionally, the studies that suggest that users just scan on the web suffer from the fallacy of small samples. They happened to choose content that was not easy to scan as the basis for the studies. It forced users to do something they were not willing to do: To engage System 2 prior to deciding whether the content was worth their time and attention. Since these users never relented to engage System 2, they never “read” in those studies.
As pages improve and the body of evidence approaches critical mass, similar studies have come to different conclusions. Thanks to Kahneman, we now have a framework for understanding these studies. The inflection point between scanning and reading seems to be a System 1 process that determines whether a page is worth a users’ time and attention or not.
Theory: Digital content relevance works like typical human psychology
Those of you who are familiar with my work know I have based much of it on Relevance Theory, which is a kind of psychology of communication. It is the keystone of my book Audience, Relevance, and Search: Targeting Web Audiences with Relevant Content. The theory defines relevance as a sliding scale with two extent conditions, which I sketch below:
- The stronger the cognitive effect in the audience, the more relevant the linguistic artifact to that audience
- The more effort a linguistic artifact requires, the less relevant it is
A cognitive effect is just a change in the mind of the audience. When we learn or are influenced or make a decision, there is a corresponding cognitive effect. Most of these are small and incremental. Some are breakthroughs. All things considered, breakthroughs are more relevant than small changes to our attitudes. The actual theory is quite a bit more complex than this, but we can gloss over that complexity for the time being.
As I read Kahneman’s book for the first time, it struck me that Sperber and Wilson—the authors of Relevance Theory—were describing communication in terms of System 1 and System 2. They just hadn’t made that connection. When they talk about cognitive effects, they are talking about System 2. Relevance Theory is based on work by H.P. Grice that describes how we reason when we communicate. Because reasoning falls into System 2, cognitive effects are, by definition, System 2 processes.
The extent condition that is more interesting to me is the one about effort. It seems to me that determining whether a page is nominally relevant—that is, whether it is worth the effort or not—is a System 1 process. The content buried within an opaque UX could answer Lizzy’s questions exactly, but she will determine it is irrelevant in a flash if it lacks the visual cues System 1 requires—tight punchy headings, bolded keywords, etc., in short, all the things Google’s algorithm looks for.
The one correction I would make to Relevance Theory after reading Thinking Fast and Slow is to reverse the extent conditions. I would put the one about effort first, because on the web, a page is functionally irrelevant if it doesn’t convince System 1 to devote the effort. And if it requires too much effort for the time being, it loses relevance fast. Only after it is deemed worth the effort do users judge to what extent it is relevant. If the page helps Lizzy make a breakthrough about structured mark-up, it is highly relevant to her.
The blog medium prevents me from stating more. All I hoped to do is plant a few seeds in the minds of enterprising readers to take these thoughts further than I could in this medium. As I said, I will have a great deal more to say in my book when it comes out this year. In the meantime, if one reader had a mountain top experience with this blog, I feel it is doing its job.
James Mathewson is the program director for search and content marketing for IBM.
Why search is so important for the executive audience
The other day, a colleague stopped by my desk and asked a question that took me aback: “Executives don’t really search that much, do they? That’s the domain of geeks, right?”
The question implies that most of my work has been misguided. I primarily work on sites built for the executive audience and I place search as the most important facet of content strategy for this audience type. I have written here and elsewhere that more than 85 percent of the executive B2B tech audience starts their journey with search and more than 70 percent of them continue to use search throughout the buy cycle. This information comes from numerous studies by Google, Tech Target and others.
If the premise of my colleagues’ rhetorical questions is correct, my work is a fraud. Also, if I’m wrong, site performance improvements I have seen over and over again using my methods are also a fraud. Fortunately, In the soul searching that followed his question, I have reassured myself. Not only do I trust the studies, but I have done deeper research on why executives use search so extensively to make purchasing decisions. I presented the research this summer at the Social Media Strategies Summit. But it bears repeating in this context. If you’re interested, please read on.
Search is the best way to learn new things
For as long as I have practiced SEO, pundits have been proclaiming the death of search. In articles too numerous to list, the self-proclaimed experts on the web have declared that users hate to search and they only do it because navigation is so screwed up, they are forced to search. My own opinion is quite the opposite: When users are presented with new information challenges and too many options to sort through one by one, they prefer to let the search engine filter them. It is simply the most efficient way to find new information. And it is getting better and better.
There are times when we prefer other ways of getting information. I use Twitter, for example, to get the best information on my area of expertise. If you follow the leading experts in a field, you are bound to get fed more information than you can possibly consume on a topic. This is what social media are best at: Helping you geek out on a topic.
But if you try to take a systematic approach to learning a new topic, you will miss a lot of information on social media platforms. First you have to know whom to follow, and that requires a degree of domain expertise. Once you follow the right people, you will miss a lot of information as it whizzes by like billboards on the Autobahn. This is where social media stumbles, and why executives especially like search. If you crack open the executive brain with me, you’ll see why.
Executives are generalists
Profile any senior executive and you will find one characteristic they all share: They have all led numerous diverse organizations. Executives climb the corporate ladder by moving from one organization to another and demonstrating leadership effectiveness at each stop along the way. To do this, they have to quickly get up to speed on the practices of the people they lead. Some of this involves trusting their people to help them get up to speed. Much of it requires research. In the digital age, where do they do this research? Search.
The executive understanding of the practices of their people is an inch deep and a mile wide. The more people that report up to them, the wider and thinner this understanding gets.
In contrast, developers and other geekier types (the people whom executives manage) are heavy users of social media. They learn from members of their communities the (sometimes closely held) tips and tricks of the trade. When I started in the tech field, forums were the places I would go to geek out. Now I just work really hard to follow the right people and publications on Twitter. And I try not to miss anything.
We are always learning new things, and for this we use search. Executives just have a lot more need of it than developers because they move around so much. When they make purchasing decisions, they don’t do it from an expert’s perspective using social media. They do it from a generalist’s perspective using search.