Category Archives: Corporate Strategy

Marissa Mayer and Yahoo’s Regression to the Mean

First published July 26, 2012 in Mediapost’s Search Insider

There is not a lot of overlap between the universes of Gord Hotchkiss and Marissa Mayer, but our orbits have intersected on a few occasions in the past. I’ve had the opportunity to talk to Mayer about various aspects of search on a handful of occasions, so it was with some interest that I watched the announcement and subsequent buzz about her appointment as Yahoo CEO.

Much has been said about Mayer’s personal qualifications for the job, and the general consensus is that this is a good thing for Yahoo. If this were a movie, I’m thinking she would score an 82% on the Tomatometer, handily qualifying as “fresh.” Personally, I would agree. Mayer has a razor-sharp (and somewhat intimidating) intellect, a core love for search and an innate sense of what’s right for the user. All of these things will be big plusses for Yahoo. What she hasn’t been tested on is her ability to run a big company. And that’s where things could get interesting.

No doubt Google still imparts its own “halo” effect on anyone who has spent time at the “Plex” in a leadership position. And few have spent as much time there as Mayer, who, as hire number 20, was Google’s first female engineer, logging 13 years with bosses (and hopefully still friends) Page and Brin.  These three tied a tight little knot in the early days of Google, but from the outside, that knot seems to have frayed just a little in the past few years. Mayer’s recent moves in the company have been more lateral than vertical, as later additions to the Google team were promoted above her. Undoubtedly, this was a contributing factor to the parting of the ways with Google.

But how much value does Mayer’s vast inside knowledge of Google and its past successes bring to Yahoo? It must have played a major role in her selection as the new chief Yahooligan. But was she instrumental in the streak of seemingly picture-perfect management calls in the early days of the Internet’s Golden Child? And, even if she were, does it really matter?

Earlier this year, I took part in an open forum on search at an industry conference. Our moderator tossed a ticking time bomb at the panel, in the form of this delicately stated question: “What the #%^&$ is Google doing lately? Have they gone insane?” We each offered our opinions, which ranged in the degree of madness ascribed to Google’s executives. I started my response with this, “I think we tend to downplay the role luck played in the early days of Google. Maybe their luck is just running out.”

There is a much fancier name for the hypothetical situation I described, which is called “regression to the mean.”  In his recent book, “Thinking, Fast and Slow,” (a HIGHLY recommended read) psychologist and Nobel laureate Daniel Kahneman explores how this can lead us to overvalue executive talent when it’s combined with the halo effect. Kahneman even uses Google as an example: “Of course there was a great deal of skill in the Google story, but luck played a more important role in the actual event than it does in the telling of it. And the more luck was involved, the less there is to be learned.”

Regression to the mean simply means that when you take a snapshot in time that represents either exceptionally good or bad performance, subsequent snapshots tend to move closer to the average. And those highs and lows generally involve luck to some extent. So you can poach talent from a company on a hot streak, only to find that it wasn’t the executives responsible for the performance, but simply the planets aligning in a favorable way.

As an ex-CEO of a company, albeit a tiny one, I find it hard to swallow that leadership might not be as important as we think in the fortunes of a company. But I generally find Kahneman to be an incredibly astute observer of human errors in judgment, so I have to resist the urge to go with my own cognitive biases here and trust Kahneman’s research.  He doesn’t say leadership is inconsequential, but he does caution against ignoring the role of timing and sheer luck.

This is also not to downplay the role Marissa Mayer will play in the future of Yahoo.  Somebody has to lead the company, and Mayer is at least as good a choice as anyone else I can think of.

Who knows? Maybe Yahoo’s luck is due to change. In their case, “regression to the mean” means there’s no place to go but up.

Bet Big on Digital Acceleration

First published July 19, 2012 in Mediapost’s Search Insider

The other day, I was going through some background research for a client. What struck me, as I waded through the reams of PowerPoint decks and research reports, was how integral digital was to the core functions of this particular industry. Whether it was key influencers in the purchase decision, reasons for doing business with a company or competitive differentiators, technological proficiency was right up there with traditional factors like price, value, convenience and reliability.

As potential customers, we expect companies to have their digital acts together. More than this, it appears we’re ready to reward companies that aggressively invest in raising the bar of their own connected maturity level. Why, then, are companies so loath to place significant bets on their own digital future?

I deal with big companies all the time, and when it comes to investing in their own websites, online marketing, web support platforms and other planks in their digital platform, they seem to prefer hedging their bets, squeezing out miserly budgets at a level that would make Ebenezer Scrooge seem hopelessly profligate. None of them are looking at digital proficiency as a way to distance themselves from the competition. Instead, it seems that they prefer the security of the herd, nervously watching the pack for signs of movement and only investing when they feel they have to to avoid being trampled by a stampede. It’s Geoffrey Moore’s classic Crossing the Chasm behavioral pattern, writ large.

It’s not the first time this has  happened. The same thing took place about 100 years ago, as Industrial America embraced electrical power. The entrenched manufacturers had all invested heavily in steam power. Despite the obvious benefits that electricity offered (cleaner, safer, more efficient factories) they never did fully embrace it, jury-rigging factories and doing ad hoc retrofits, stranding themselves in a competitive no-man’s land between electricity and steam. New competitors built new factories that maximized their advantages, and the old guard never recovered. In a decade, most of them were gone.

Economists refer to this as a regime transition. In hindsight, it seems hedging your bet when it comes to new technology is not really “playing it safe.”

To me, it seems obvious we’re in exactly the same place. History is repeating itself. If these companies look at their own research, it’s easy to see the signs. Yet research tends to be digested in context, and often people see what they want to see in it. What’s potentially worse, they fail to see what they don’t want to see. Even more frustrating, the cost of making a significant, best-in-class investment in accelerating digital maturity is relatively minimal — perhaps even infinitesimal — given the other operating costs these companies are carrying.

When it comes to digital maturity, I find the real acid test is how effectively companies connect with their customers, both present and future, through online channels. Is the website truly effective? Do they have good search visibility? Have they found a way to play in social that recognizes the importance of authenticity and the forging of true relationships? Do they understand how their customers might use a mobile device to connect with them? If a company can do these things right, chances are they’re well advanced in the digital maturity model.

The other thing to look for is how the company is using digital technology to reinvent the traditional ways it does business, especially when it comes to handling relationships with real people. I find sales to be one of the last bastions of “we’ve always done it this way” thinking. If a company is seriously considering how to make its sales force more effective by leveraging digital channels, it’s a good sign for the future.

In my opinion, betting the farm on digital maturity seems to be a no-brainer — especially when, in terms of real dollars and cents, it’s a relatively small farm we’re talking about here.

Three Myths About Customer Love

First published July 5, 2012 in Mediapost’s Search Insider

Today, I want to talk about the last of the three posts by Harvard Business Review bloggers, Karen Freeman, Patrick Spenner and Anna Bird  I have been surveying: “Three Myths about What Customers Want.” Specifically, I want to look at this post’s implications for online marketing.

Myth #1: Most consumers want to have relationships with your brand.

This myth is at the crux of many, many social media campaigns. The theory is, a “like” = “intent to buy.” I have said before that I believe this is hogwash. The HBR bloggers concur:

“Only 23% of the consumers in our study said they have a relationship with a brand. In the typical consumer’s view of the world, relationships are reserved for friends, family and colleagues. That’s why, when you ask the 77% of consumers who don’t have relationships with brands to explain why, you get comments like ‘It’s just a brand, not a member of my family.’”

Marketers being marketers, we tend to think the entire world revolves around whatever it is we’re trying to sell. We believe people actually give a damn. They don’t, at least not in the vast majority of cases.  In contrast, relationships endure. They are there for the long haul. Consumer consideration runs on much shorter timelines.

There are degrees to consider here, however. What consumers can develop for a brand is loyalty. This falls into the category of beliefs, and that is what drives a lot of consumer behavior. We can believe a brand offers good value without having a relationship with it. Beliefs are heuristic decision shortcuts, which help consumers cut through cognitive overload.

Myth #2: Interactions built relationships.

Actually, say the HBR team, relationships are built on shared values:

“Of the consumers in our study who said they have a brand relationship, 64% cited shared values as the primary reason. That’s far and away the largest driver. Meanwhile, only 13% cited frequent interactions with the brand as a reason for having a relationship.”

Values can be a powerful driver of how we form beliefs. The brand I probably have the strongest affinity for is Apple. And it’s not because I have a relationship with Apple (never having visited its Facebook page). It’s because I believe Apple shares my values of creative freedom, uncompromising design and aesthetically pleasing experiences. I interact with an Apple device every day of my life. But I interact with the company only when I need something.

Myth #3: The more interaction, the better.

Marketers want to dominate a prospect’s time, in the mistaken belief that it will make the relationship “stickier.” If “stickier” means frustrating and annoying, they could be right.

“There’s no correlation between interactions with a customer and the likelihood that he or she will be ‘sticky’ (go through with an intended purchase, purchase again, and recommend),” writes the HBR team. “Yet, most marketers behave as if there is a continuous linear relationship between the number of interactions and share of wallet. That’s why, as the Wall Street Journal recently reported, you see well-established retailers like Neiman Marcus, Lands’ End and Toys R Us sending customers over 300 emails annually.”

We all have lots to do. The last thing on that list is to spend unnecessary time interacting with a brand because they’ve targeted us as a “loyal” customer. Here’s a question to ask yourself: Who benefits most from all these interactions — the customer or the marketer? If the answer is the marketer, then why should the customer care?

The danger of becoming marketers is that we gain a distorted perception of reality. Our job is to love a brand. It consumes our professional lives. This does weird things to a human brain. It makes it almost impossible to look at our brands the same way the rest of the world does. We care because we have to. We get paid to. The rest of the world doesn’t share the same motivation.

Paralyzed by Choice

First published June 28, 2012 in Mediapost’s Search Insider

In last week’s column, I looked at how Harvard Business Review bloggers Karen Freeman, Patrick Spenner and Anna Bird spelled the end of the purchase funnel. Today, I’d like to look at the topic they tackled in the second of the three-part series, “If Customers Ask for More Choice, Don’t Listen.”

Barry Schwartz, the author of “The Paradox of Choice,” believes we’re overloaded with choices. In fact, we have so many choices to make, often about inconsequential things, that we live with the constant anxiety of making the wrong choice.

This paradox meets today’s consumer head on, over and over, in situation after situation. The other factor, which I’ve seen play a massive role in buying behaviors, is the degree of risk in the purchase. The bigger the purchase, the higher the risk.

The final piece of the buying puzzle is the reward that lies at the end of the potential purchase. Our brains are built to balance risk and reward in fractions of a second. But we don’t do it by a calm, rational weighing of pros and cons, thus engaging the enlightened thinking part of our brains. We do it by unleashing emotions from the dark, primitive core of our brain. The risk/reward balance whips up a potent mix of neural activity that sets our decision-making engine in motion.

The degree of risk or reward sets the emotional framework for a purchase. High reward, low risk generally means a fairly fast purchase, such as an impulse buy. High risk, low reward may mean a very long purchase cycle with an extended consideration process. Whatever the buying path, there will be an undercurrent of emotion running just below the surface.

Now, let’s match up the findings of the HBR team. High-risk purchases automatically ramp up the level of anxiety we feel. We’re afraid we’ll make the wrong decision. And, in a complex purchase, there’s not just one decision to be made – there are several. At each decision point, we’re bombarded by choices. If the hundreds of purchase path evaluations I’ve done are any indication, the seller spends little time worrying about presenting those choices in a user-friendly way. Catalog pages are jammed with useless and irrelevant items. Internal site search results are generally abysmal. And product information typically takes the form of a long shopping list of features. Very little of it speaks to buyers in a language they care about.

This is a dangerous combination. We have the natural anxiety that comes with risk. We have a gauntlet of decisions to make, each raising the level of anxiety. And we have websites that contribute greatly to the frustration by making it difficult to navigate the information that does exist, which is either too little, too much, too irrelevant or too salesy — never does it seem to be just right.

Again, Freeman, Spenner and Bird ask us to make it simpler for the buyer. Provide them with fewer choices, and make them as relevant and compelling as possible. Ease the burden of risk by providing information that reassures. Realize that one of the components of risk is the degree of bias in the information we’re given. It that information reeks of marketing hyperbole, it will be discounted immediately.

In our numerous eye-tracking studies, we’ve found that in most instances, three to four options seems to be the right number to consider on a Web page. These can be easily loaded into working memory and compared without causing undue wear on our mental mechanics. So, on a landing or home page, three or four groups of coherent and relevant information seems to be an optimal level. We call them “intent clusters.” For navigation bar options, we try to keep it between five and seven choices. If we expect mostly transactional traffic, we ensure there is a “fast path” to purchase. If we expect a lot of purchase research, we aim for rich promises of relevant and reliable information.

As Freeman, Spenner and Bird remind us, “The harder consumers find it to make purchase decisions, the more likely they are to overthink the decision and repeatedly change their minds or give up on the purchase altogether. In fact, regression analysis points to decision complexity and resulting cognitive overload as the single biggest barrier to purchase.”

As marketers, our job is to eliminate the barriers, not erect new ones.

The Death of the Purchase Funnel

First published June 21, 2012 in Mediapost’s Search Insider

A recent series of three posts on the Harvard Business Review blog by Karen Freeman, Patrick Spenner and Anna Bird explored some of the myths about how consumers make decisions. I think each of these has direct implications for search marketers, so over the next three weeks I want to explore them one at a time.

The first, titled “What Do Consumers Really Want? Simplicity,” talks about the breakdown of the purchase funnel. The HBR bloggers contend the funnel, which has been around for well over a hundred years, no longer applies to consumer behaviors. I concur, and said as much in my book, “The BuyerSphere Project.”

We differ a little on the reason for the demise, however. The HBR team credits the demise to cognitive overload on the part of the consumer. We’re simply bombarded by too much information on the purchase path to fit it all into the nice, simple, rational filtering process captured in St. Elmo Lewis’s elegant funnel-shaped model. The accompanying research, a survey of 7,000 consumers, shows decision simplicity was the number-one thing people wanted when making a purchase.

I agree that information overload is part of it, but I also believe that two other factors have led to the end of the purchase funnel. First, the purchase funnel assumes a rational filtering of options based on careful consideration of a consumer’s requirements. I don’t think this was ever the case. Emotions drive our decisions, and more often than not, rationality is applied after the fact to justify our choices. Prior to the Internet, emotion was tough to distinguish from rationality, as buyers didn’t have much control over the content they accessed during the consideration process. They were limited to whatever the marketer pushed out at them. So, whether driven by emotion or logic, they tended to go down the same path and display many of the same behaviors. Given the pervasive believe in humans as rational animals at the time, it was not surprising that a logic-driven model emerged.

The other factor, as I alluded to, was that the Internet shifted the balance of power during the purchase process. Suddenly, we could choose which paths we took during the consideration process. We weren’t all forced down the same path, according to some arbitrary notion of a funnel-shaped model.

What became clear, when consumers could choose their own path, was that the simplicity of the funnel model bore little relation to the actual paths consumers took. And those paths were driven by emotion. People bounced all around, depending on what they were looking to buy. They could go all the way to a shopping cart, then suddenly abandon it and go back to a destination that would be considered “upper funnel” and start all over again. From the outside looking in, this resembled a bowl of spaghetti much more than it did a funnel.

So, we have a trio of suspects in the death of the purchasing funnel: cognitive overload, emotion trumping logic, and consumers gaining more control over their consideration path. All lead to an interesting concept to consider: laying an online path that anticipates the emotional needs of the buyer, and yet keeps the information presented from overwhelming them. For example, marketing has traditionally taken a “turf war” approach to persuading a prospect: “as long as they’re on our turf, we do everything possible to close the sale.

But this doesn’t really match up with the three trends we’re talking about. What online consumers are looking for, according to the HBR research, is a safe online zone that will make their decision easier. Rather than going from site to site, collecting information and filtering out overt marketing hyperbole, what consumers want is a single information source they can trust. They want to be able to lower their “anti-BS” shields, because being a rational, cynical shopper takes a lot of time and effort.

Today, it’s extremely rare to find that trustworthy information on a site you can actually purchase from, but it’s starting to happen in some high activity categories, where independent portals facilitate this simplified approach to shopping. Travel comes to mind.

But let’s consider what would happen if a brand’s website took this approach. Rather than bombard a prospect with exaggerated sales pitches, putting them on the defensive, what if a more neutral, objective experience was provided?  After all, why shouldn’t the decision path be built on your own turf, giving you a home field advantage?

Brand Beliefs and the Facebook Factor

First published May 17, 2012 in Mediapost’s Search Insider

Last week I talked about the power of our beliefs to shape our view of the world around us. I also mentioned how our belief constructs impact our view of brands. As luck would have it, two separate pieces crossed my path this week, both of which provide excellent examples of how we may perceive brands, and how marketers often get it wrong when trying to shepherd a brand through the marketplace.

The first piece was “Does Branding Need to be Rebranded?” by Mediapost’s Matt Straz in Online Spin. In it, Matt mentioned the backlash against Sir James Dyson (he of the cool vacuums) when he dared to mention that he doesn’t believe in branding. Now, to clarify, Dyson doesn’t believe in branding the way it’s practiced by many companies, where through sheer force of advertising, their heavily controlled (and often contrived) brand story is theoretically imprinted in your brain.  This isn’t so much branding as brain-washing. Let’s call it “brand-washing.”

But let’s go back to how our beliefs define our view of brands. We use beliefs as a heuristic short cut allowing us to operate efficiently in our world. We form beliefs so we don’t have to endlessly think through every single decision. Beliefs form based on our own experience, but they are also formed based on what we’re exposed to. All this input gets synthesized into a reasonably coherent and remarkably resilient belief. Once in place, this belief guides our action.

So, from our perspective, a brand can be defined as what the buyer believes a brand to be.  In the ad community, there is much debate about the definition of a brand. But, in the final analysis, the only definition of brand that matters is the one that rests in the mind of the buyer. All else are simply inputs into that final mental model, which is created solely by the customer.

James Dyson believes the best of those paths is by producing great products and then letting them speak for themselves. If you create products that consistently exceed expectations, that is enough to build an authentic and enduring brand belief. It’s hard to argue with that logic, and, in fact, it’s what P&G called the Second Moment of Truth with consumers: their experience when your product is in their hands. In this definition, brand is intimately coupled with the product itself.

But, if Dyson is right, why is there an advertising industry at all? Even Dyson buys ads to sell vacuum cleaners. This brings us to the second piece that I saw in the past week. It was a report out of Forrester called the Facebook Factor. This is a bit of a tangential detour, so bear with me.

The report posits that we can now quantify the value of a Facebook “like.” The reasoning is fairly simple. If you add a few questions to a typical customer survey, you can start to quantify the correlation between someone liking you on Facebook and subsequent purchasing of your product. But, as Forrester points out in the report, there is a correlation/causation trap here that could lead to many marketers making the wrong conclusion.

If you try to equate people who felt motivated to “like” you on Facebook with likelihood to purchase, you run the risk of mistaking correlation for causation. People didn’t buy your product as a result of “liking” you on Facebook.  The Facebook “like” came as a result of a positive “belief” about your brand. It was an effect, not a cause. At best, the Facebook Factor should be considered as nothing more than a leading indicator of brand preference.

But many marketers will confuse cause and effect. They will believe that driving Facebook “likes” will drive higher brand loyalty.  This is where brand and product can potentially become decoupled. Here, once marketers start assigning a value to a Facebook “like” based on Forrester’s methodology, they will start regarding Facebook “likes” as the end goal, trusting in the mistaken belief that a Facebook “like” will always correlate positively to purchase behavior.

Once this decoupling happens, the value of the Facebook “like” starts to erode. The motivation for the “like” often has little to do with a positive brand experience. It’s driven by a promotion or campaign that has just one aim: to drive as many likes as possible. From the customer’s perspective, it’s easy to hit the “like” button. They have no skin in the game. There is no belief behind the action.

In the end, I believe Dyson’s definition of brand is the more authentic one. It goes back to the very roots of branding, which was a reassurance to buyers that they were buying what they believed they were buying.

Read more: http://www.mediapost.com/publications/article/174966/brand-beliefs-and-the-facebook-factor.html#ixzz2ik9IjRDB

Believing is Seeing

First published May 10, 2012 in Mediapost’s Search Insider

In his book “The Believing Brain,” Michael Shermer spends several hundred pages exploring just how powerful beliefs are in forming our view of the world. Beliefs affect not just what we think, but they literally filter what we see and do. And, once in place, beliefs tend to be stubbornly unshakeable. We will go to great extents to defend our beliefs with rationalizations that are often totally or partially fabricated. As Shermer says, “Beliefs come first, explanations for beliefs follow.”

In the world of consumerism, this becomes important in any number of ways. For one, we have beliefs about brands, both positive beliefs and negative ones. And, as previous neuro-research has shown, those beliefs can dramatically alter how we sense the world. In a study at Baylor University, Dr. Read Montague found that the reason Coke devotees are so loyal has almost nothing to do with the actual taste, and much more to do with the Coke brand and what it says about them as people. It’s not the taste of Coke we love; it’s the idea of Coke.

A few weeks ago, I saw a press release from another study that takes this concept even further. The implications for understanding consumer decision-making are dramatic. In the study, Ming Hsu from the University of California, Berkeley, conducted an fMRI test of individuals participating in a multi-strategy economic investment game. As they made decisions based on the actions of their opponents, the parts of the brain that were firing were recorded.

Games of this sort require that the participants learn from events and adjust their strategies according. Here’s an excerpt from the media release: “The researchers focused on two types of learning processes. So-called ‘reinforced-based learning’ (RL) operates through trial and error. In contrast, more sophisticated ‘belief-based learning’ requires decision-makers to anticipate and respond to the actions of others. The researchers computed the areas of the brain where activity tracks these two types of learning. In addition, they discovered that the prefrontal cortex is an area that processes learning about others’ beliefs. The same area also predicts an individual’s propensity to engage in either belief learning or simply RL.”

This is interesting. Reinforced learning is completely reactive in nature. It’s learning after the fact. But if that was the only way we learned, we wouldn’t survive long. So the brain needs to adapt a proactive learning framework, and that framework relies on beliefs as its primary construct. We act based on what we believe the best outcome will be, and alter as necessary based on the success or failure of our decisions.

Now, if we were purely rational and empirical in the way we form those beliefs, this would seem to be logical way to live our lives. But, as we’ve seen, our beliefs are often anything but rational. They are usually formed with little thought or input, and once formed, tend to resolutely remain in place, even in the face of overwhelming evidence to the contrary. If you think I’m exaggerating, consider this: 55% of Americans believe in angels, 39% believe in evolution, 36% believe in global warming and 34% believe in ghosts. I’ll leave it you to decide which of those stats you find most troubling.

The other note in the above excerpt that’s interesting is where this belief mechanism sits in the brain: the prefrontal cortex. This, by the way, was the same area of the brain that lit up in Montague’s test when his subjects knew they were drinking Coke. It’s the one part of the brain that really makes us who we are — quite literally, in fact.

Even in something as fleeting and supposedly unemotional as using a search engine, I’ve seen firsthand the powerful impact a strong brand belief can have. It physically alters what we see on the page of results. We’re just getting preliminary results from our own neuro-scanning study, done with Simon Fraser University, and it appears that looking for a favored brand affects how quickly we can find relevant information, how much time we spend looking at it (counterintuitively, we actually spend less time engaging with favored brands) and how easily distracted we are by other information on the page.

Truly, in consumerism, as in all areas of our lives, our beliefs determine how we see and sense the world around us.

 

Looking for the B2B Needle in the B2C Haystack

First published April 12, 2012 in Mediapost’s Search Insider

It’s not easy being a B2B marketer of the digital variety. Trust me. The problem is that 99% of the online world seems to be built specifically for the consumer market, and us B2B types have to try to divvy up the 1% that’s left. And that’s where it gets challenging.

The Tip of a hidden B2B Iceberg

One of the challenges is the lack of definition of the B2B market. It’s massive. But no one really seems to know just how big it is. When I was writing my book on B2B digital marketing, I tried in vain to try to find some reliable quantification of the immensity of the market, but I never did find a number that seemed fit for quoting. I had consumer market stats coming out of the ying-yang, but no one wanted to go on record to try to nail down the size of the business-to-business marketplace.

Consider this, though. For every consumer product that ends up in your hand, there is a long string of B2B transactions that precedes it. Some are materials and components directly incorporated into the end product, but many are indirect: equipment, services and supplies required to keep the long supply chain running.

Massive Fragmentation

If the B2B market is one massive iceberg that remains hidden, the challenges that face the B2B marketer start compounding when you consider that the market isn’t a monolithic one. Unlike the big consumer markets like automotive or consumer electronics, B2B markets are incredibly fragmented. The market lives in tiny little slivers spread across the online landscape. Suddenly our iceberg shatters into billions and billions of slippery little ice cubes.

This becomes apparent when you try to use a service like comScore or Hitwise to get market intelligence. Unless you’re GE, Siemens or Oracle, the vast majority of B2B websites have barely enough traffic to register in the datasets of these tools. Consumer markets tend to aggregate around a few landmark sites. But B2B traffic is scattered to the four winds. Even big B2B suppliers like 3M face the same problem in trying to obtain meaningful competitive data, once you go past the home page.

Consider that the main site, 3M.com, gets roughly the same traffic as just one site for a single PG consumer brand, Pampers.com. But within the 3m.site, no less than 70 different product divisions and hundreds of thousands of product lines are represented, from electronic components to liquid absorption materials that are used in, yes, those very same Pampers. If you try to slice and dice the traffic to get any meaningful intelligence, you soon find it would be easier to split an atom.

B2B Buyers look very much like B2C Buyers in the Data

Finally, you have the problem that when we have our B2B buying hat on, we still act much the same as when we wear our everyday consumer hat. We don’t suddenly change our search or online habits. For example, if you’re researching a possible solution for improving the water quality of a chain of coffee franchises, you’re likely to use pretty much the same keywords on Google that you might if you were looking for a home unit to fit under your kitchen sink.

When we search, we tend to start broad and only narrow down our searches when we have to. So when you look at search data available through Google or another tool, it becomes virtually impossible to segment B2B traffic from B2C. In the data, it often looks the same. So as you try to quantify opportunity, you start playing the B2B guessing game, where you arbitrarily discount the opportunity based on a WAG on what percentage could possibly be non-consumer in nature.

If you’re looking in a highly specialized product category, you might eventually use a B2B search tool like ThomasNet, GlobalSpec or KnowledgeStorm, but in all our research we have found that vast majority of B2B search activity happens in the same place as our consumer queries: namely Google, and to a lesser extent, Bing and the other alternatives.

Slim Pickens…

If you’re a consumer marketer, there is an increasingly rich set of digital marketing tools and data and targeting services to choose from. Everybody and their cousin are falling over themselves to cater to this market. But if you’ve decided to stake your flag on the B2B side of the divide, good luck! Only the foolhardy and brave seem to want to set foot here.

Reinventing AIDA

First published April 5, 2012 in Mediapost’s Search Insider

Last week, my column was about how branding differs between search and more traditional brand channels like TV and print. It came from a recent client conversation I had. Rob Schmults from Intent Media added a well-thought-out, on-the-mark comment that deserves a follow-up. There are three points in particular I want to dive deeper into.

“ I think part of the problem in attempting to do so is that branding is all too often an end in and of itself rather than a means.”

Absolutely. Most sales and marketing happens in dozens of disconnected siloes, with little thought about how the actions of one silo affect all the others. Each silo measures progress by its own metric and set its own agenda. The problem is that all these different initiatives are aimed at the same target, but there is little thought as to how each initiative can impact the prospect.

For the past year, I’ve been thinking about how to approach marketing by starting first with creating a common understanding of the buyer’s motivations and behaviors, and then mapping a decision landscape so we can begin to understand the path the buyer takes through it. Much of my writing over the past two years has explored various aspects of this landscape: things like the role of risk and reward, and how they affect the emotions drive our buying decisions.

If branding becomes disconnected and “an end in and of itself,” it starts to lose touch with the chain of “means” that translates brand awareness into action. I saw a particularly acute example of this in a recent meeting: a brand agency presented research showing each point of movement in its unaided brand awareness metric translated into X of additional revenue. I didn’t dispute the finding, as I believed it to be true. What was missing was the long chain of interdependent “means” taking us from there to here. It was like saying that each inch of rain translated into X increase of revenue at the local farmer’s market. We’re jumping from “A” to “Z” without worrying about the 24 intervening letters.

“SEM is clearly a means — it’s a step to driving a conversion event (typically a sale).”

As I mentioned last week, presence on the search page is very often a critical intermediate step between the lofty heights of brand-building and the nitty-gritty of bringing cash in the door. In fact, if you take the time to understand how search is typically used in the purchase process with your typical buyer, it typically falls into the “no-brainer” category, because the prospect has intent and is completely open to being persuaded. Which brings me to Rob’s next point:

“Branding has value, so the war Gordon describes doesn’t have to end with total victory and branding’s extinction.”

As effective as search is, it’s a channel with built-in limitations, including available inventory. If there is no awareness, there is no inventory. People can’t search for something they don’t know exists (at least, not yet). Branding creates awareness, which, if the dots are connected properly, eventually turns into intent. And when intent is present, search is very effective at converting that intent into action. The chain then is Awareness – Intent – Action, which is a variation on the venerable AIDA branding model: Attention – Interest – Desire – Action. If you combine the two you end up with Awareness – Interest – Desire – Intent – Action, or AIDIA. You need branding at the front end, to create awareness, spark interest and create desire. You need search at the back end to allow prospects to act on their intent and discover how to take action.

It’s interesting to note that the original AIDA model jumped all the way from desire to action without much explanation on how to get there. Given that two of the steps –“interest” and “desire” — seem pretty similar, it’s odd that there is such a huge chasm between the domain of branding and the ultimate transaction itself. The AIDA model was definitely biased towards the front end of the marketing process.

I think what digital has done, especially through search, is to provide much more granularity and clarity on the many steps you can take to get from desire to action. But, as Mr. Schmults reminds us, none of these steps is “an end unto itself.” They’re part of a journey. They depend on each other. And each is passed through by your prospects as they travel down the path of purchase.

To come full circle, that was my original point. I’m not calling for the abolition of branding. I’m just asking that we take the time to understand the journey our customers take, and be there at each step.

 

Marketing Physics 101

First published February 9, 2012 in Mediapost’s Search Insider

Physics has never been my strong suit, but I think I have a good basic grasp of the concepts of velocity and direction. In my experience, the two concepts have special significance in the world of direct marketing. All too often I see marketers that are too focused on one or the other. These imbalances lead to the following scenarios:

All Direction, No Velocity

As a Canadian, I am painfully familiar with this particular tendency. Up here, we call it a Royal Commission. For those of you unfamiliar with the vagaries of the Canadian political landscape, here’s how a Royal Commission works. It doesn’t. That’s the whole point. Royal Commissions are formed when you have an issue that you wished would simply go away, but the public won’t let it. So a Royal Commission deliberates over it for several months, issues a zillion-page report that nobody ever reads, and by the time the report comes out, everybody has forgotten why they were so riled up in the first place.

This is similar to a company’s strategists noodling for months, or even years, about their digital strategy without really doing anything about it. They have brainstorming sessions, run models, define objectives and finally, decide on a direction. Wonderful! But in the process, they’ve lost any velocity they may have had in the first place. Everyone has become so exhausted talking about digital marketing that they have no energy left to actually do anything about it. Worse, they think that because it lives on a shelf somewhere, the digital strategy actually exists.

All Velocity, No Direction

With some companies, the opposite is true. They try going in a hundred directions at once, constantly chasing the latest bright shiny object. Execution isn’t the problem. Stuff gets done. It’s just that no one seems to know which direction the ship is heading. Another problem is that even though velocity exists, progress is impossible to measure because no one has thought to decide what the right yardstick is. You can only measure how close you are to “there” when you know where “there” is.

Failing any unifying metrics grounded in the real world, people tend to make up their own metrics to justify the furious pace of execution. Some of my favorites: Twitter Retweets, Number One SEO rankings and Facebook Likes.  As in “our latest campaign generated 70,000 Facebook likes” — a metric heard in more and more boardrooms across America. Huh? So? How does this relate in any way to the real world where people dig out their wallets and actually buy stuff? Exactly what dollar value do you put on a Like? Believe me, people are trying to answer that question, but I’ve yet to see an answer that doesn’t contain the faint whiff of smoke being blown up my butt. I suspect those pondering the question are themselves victims of the “all velocity, no direction” syndrome.

Balanced Physics

The goal is to fall somewhere in between the two extremes. You need to know the general direction you’re heading and what the destination may look like. You will almost certainly have to make course adjustments on the way, but you should always know which way North is.

And if you have velocity, it’s much easier to make those course adjustments. Try turning a ship that’s standing still.