Category Archives: Behavior & Psychology

The Usability Acid Test

I slagged eMarketer last week for misleading reporting on Twitter usage, so in the spirit of fair play, I’ll show them some love for an interview they did with Kevin Ertell, Vice President of Retail Strategy for ForeSee Results.

In the interview, Kevin nailed the top thing that every single business should have on the top of their to do list:

“We’re seeing at many, many retailers that the amount of people that say they came to make a purchase today is 20% or higher. Yet, those people’s conversion rates are nowhere near 20%. So, there’s a massive gap there, and a lot of that gap can be attributed to usability issues. ”

Kevin is talking retailers, but developing a core usability practice should be a no brainer for any type of business, no matter what their online objectives are. It just doesn’t make sense to spend all that time, money and effort driving leads to a website that then lets those leads slip through hundreds of cracks. I’m a big believer in picking one thing and doing it really, really well. For online marketers, that one thing should always be delivering a great user experience. If you have to make a sacrifice to do it, do it. Nothing is more important than this.

This is one of those things that falls into the common sense category, but very very few companies do usability well. There are a lot of really horrible user experiences out there. Here are 5 usability acid tests to hold yourself to:

Have you crawled inside your customer’s minds? The percentage of companies I know that have done robust research into understanding how their prospect’s brains tick is almost nil. This is the first place you have to start. Why are they coming to your site? What do they want to do? Like I always say, a good place to start is just to stand over a prospect’s shoulder when they’re on your site and start asking why. Sure, it’s not sophisticated usability testing, but it’s a beginning. The important thing is just to start doing something!

Can they find what they’re looking for? Prospects are coming to your site because they’re looking for something. Everybody is looking for something. And the vast majority of your visitors will be looking for a handful of common things. Make sure they find them. Make sure the cues and paths are easy to find, clearly lit and simple to follow. Provide site wide assistance in the form of clear sitemaps and internal search tools that don’t suck.

Can they do what they want to do? Again, prospects come to your site with an objective – something they want to do. The better you understand that objective, the more successful you can be in helping them meet it. Your job – your only job as the site designer – is to understand the paths your visitors want to take and remove any possible friction on those paths. You’ll have business objectives (i.e. capturing lead information) but these should never take priority over your visitor objectives.

Do You Make Your Visitors Do Too Much Thinking? (thanks Steve Krug!) – We do very little thinking when we navigate websites. Most of our online wayfinding is done subsconsciously. The minute you make a prospect stop and think, you’ve introduced friction and reduced their site experience. You should be able to get to where you’re going on the site quickly and intuitively. It’s not a puzzle to be solved. It’s a tool to be put in the hands of your prospects to help them do the things they want to do.

Do you have a servant based site philosophy? – This final point sums up all the previous ones. You don’t own your website..your customers do. Your goal is to meet their needs. Call it a servant based site design philosophy. Never make them sacrifice their objectives to meet yours (as in collecting lead information in a long form before they can get to where they need to get). If you provide enough value, they’ll meet you half way, but never force the issue.

This acid test for usability, if answered honestly, will help you understand how far you are away from a robust usability discipline. Assess and then make it a priority for 2010. There is no better place to spend your time!

Socially, We’re Suckers for a Deal

Razorfish’s new FEED 2009 report found that consumers like to spread the word digitally about great deals on brands. In fact, this far surpassed their desire to just talk about brands.

Humans are still Humans, even Online

Here’s the thing that gets me. When we talk digital channels, we seem to forget that humans are humans. We’ll still be the way we’ve always been, we’ll just do in on a new canvas. The “finding” of FEED 2009 discovered that we like to talk about deals. This has been hardwired into humans since we crawled out of caves. In a bit, I’ll share the findings of an interesting study that looked at how this social news spreads through our networks.

The Results of FEED

But first, let’s look at the other results of the study. Despite my morning grumpiness, this is a report worth downloading:

FEED09_Chart-Q1765% of consumers have had a digital experience that either positively or negatively changed their opinion about a brand. Again, this is behavior that is common, we all have perception altering brand experiences. As we spend more time online, it’s natural that this will happen here too.

Branding is now a participatory experience. We’re no longer passive consumers of brand messaging. We now expect to roll up our sleeves, get in and muck around with the building of brands. We want to do things with the brand. We will now participate in building the aggregate story of a brand. 73% of study participants had posted a product or brand review on web sites like Amazon, Yelp, Facebook or Twitter. We now have a voice and we’re using it.

We’re becoming Brand Fans. 40% of consumers have “friended” a brand on Facebook and/or MySpace and 26% of followed a brand on Twitter. Again, this isn’t new, it’s just going digital. There are certain brands that inspire fierce loyalty: Apple, Harley Davidson, Nike. It’s natural that these Brand Fans would now be expressing themselves online. One word of caution for Brand Marketers here. People won’t suddenly become fans just because you’re on FaceBook. You have to be a brand that people care about.

FEED09_Chart-Q27Here’s the study tidbit that was “surprising”. Of those that follow brands on Twitter, 44% said access to exclusive deals is the main reason. Same is true for those that “friended” a brand on Facebook or MySpace..accounting for 37% of participants. The next highest reason for following a brand on Twitter? Being a current customer, at 23.5% And again, this would be for those brands that inspire an unusually high degree of loyalty.

Strength of Weak Ties

Sometime ago, I talked about a fascinating study by Frenzen and Nakamoto that looked at how rumors, or in this case, news of a bargain, spread through social networks. It explored the roll of Mark Granovetter’s famous “Weak Ties” in social networks. Social networks tend to be “clumpy”, rather than uniformly dense. There are dense clumps, representing our families, closest friends and co-workers that we see every day. You’re connected to these people with “Strong Ties”. But the clumps are also connected with “Weak ties” that span the gaps. These are ties between more distant family, casual friends and acquaintances. As Granovetter discovered, news spreads quickly through the strong ties within a clump, but it’s the ability to jump the weak ties that really causes word to spread throughout the network. We rely on the “connectedness” of these weak ties for things like news on potential jobs, social tidbits and yes, the scoop on a great bargain. If you look at the nature of these weak ties, you’ll realize that it’s exactly those types of ties we tend to maintain on Twitter and Facebook.

In 1993, Jonathon Frenzen and Kent Nakamoto decided to explore the conditions that had to exist for news to jump from cluster to cluster across those weak ties. They tested the nature of the message itself and also how the news would impact the person delivering the message, a condition called moral hazard. In other words, would the messenger lose something by spreading the word? The scenario they used to test the conditions for this social “viralness” was news of a sale. There were three variables built into the study: the structure of the network itself (strongly connected vs weakly connected), the attractiveness of the sale (20% off vs 50 to 70% off) and the availability of the sale item (unlimited vs very limited quantities – introducing the aspect of moral hazard).

Frenzen and Nakamoto found that in all cases, news of the sale spread quickly through the strong clusters. But when the message wasn’t that remarkable (the 20% off example), word of mouth had difficulty jumping across weak ties. Also, when moral hazard was high (quantities were limited) again, the message tended to get stuck within a cluster and not be transmitted across the weak ties. If you look back at the original post, I go into more depth about how this impacts our inclination to spread news through our networks.

Twitter: The Weak Tie Pipeline

So, let’s take this back to the Razorfish study. There needs to be a few conditions present for news to spread along weak ties: The information has to be valuable (50 to 70% off) and it can’t put the person holding the information in moral hazard (if I share this information amongst too many people, there will be nothing left for me or my family). The example given in the study, following a Brand on Twitter to get news of exclusive offers, is our “weak tie” to the brand, so we can be first to benefit. And, if the discount is substantial and there is low moral hazard, we will in turn Tweet about it ourselves.

The Razorfish study indicated surprise that more people were engaging in social networks to learn about discounts and not to evangelize brands. Again, if we look at human behavior, there is no surprise here. Brand evangelization engages a completely different part of our brain, the same part, incidentally, that gets triggered when we talk about religion and other unusually strong beliefs. These are things most of us hold closer to our chest. We share them with our strong ties, but we don’t usually spread that across weak ties. There are exceptions, of course, but I think most marketers assume all of us are willing to build public shrines to their products. That’s just not how humans tick.

But, humans can’t resist spreading the word if that word has social value (a great bargain) and we don’t miss out ourselves by spreading the word. Those are the messages built to set Granovetter’s weak ties singing in a social network. We’ve been this way for a long, long time. And now that Twitter and FaceBook are here, we’ll still be that way.

The Common Denominator between Brains, Cities and the Internet (..oh..and ants too)

If you took the time to look at an ant colony..really look at it…you’d be amazed. In his book Emergence, Steven Johnson did just that. And here’s what he found. Ant colonies are perfectly designed. The food supply of the colony is the perfect distance away from trash pile, and both are strategically placed to be the greatest possible distance from the ants’ graveyard. It’s as if some ant mastermind somewhere took the time to plot out the colony design on some ant-sized draftboard. Of course, that didn’t happen. What did happen is that even ant sized brains can remember a set of simple rules and over time, even with the complexity of thousands of ants doing their thing, a sort of order emerges. Patterns that look to be deliberated planned emerge out of complex and seemingly chaotic activity.

The Organized Cesspool: Manchester

In the 1800’s, the industrial revolution caused the city of Manchester, England to explode in size, from 24,000 in 1773 to 250,000 by 1850. The growth was not steered by any form of urban planning. Factories sprung up anywhere. Factories needed workers, so new neighborhoods, many shantytowns housing the poorest of the poor seeking work, suddenly sprouted up. People need some basic form of support, so new shops and services suddenly appeared. All this happened without a plan in place, a seemingly hopeless mishmash of urban development. Alex De Toqueville described it like this, “From this foul drain the greatest stream of human industry flows out to fertilize the whole world. From this filthy sewer pure gold flows. Here humanity attains its most complete development and its most brutish; here civilization works its miracles, and civilized man is turned back almost into a savage.”  Dickens was even less kind, ” What I have seen has disgusted and astonished me beyond all measure.”

One of the visitors to Manchester saw something different, however. Frederich Engels, who would become co-author of the Communist Manifesto with Karl Marx, came to Manchester to see first hand the horrific struggles of the Industrial-era working class. Certainly he found what he came looking for, but he also saw something that surprised him. There, in the squalid chaos that was Manchester, he found a strange sort of order that had emerged. Manchester had developed so that the factory owners that lived in the upper class neighborhoods could live for years in the city without seeing a working class neighborhood. Thoroughfares, businesses and social institutions emerged so that the city just “worked” for it’s inhabitants. Just like the ants, the citizens of Manchester had some social rules that dictated the pattern of the city that emerged.

Brains and Cities: Evolved Functionality

citybrainThis natural evolution of cities is the subject of a recent study that comes from Rennselaer Polytechnic Institute. The finding? Cities are organized like human brains.As cities grow, they not only increase in physical size, they also become more densely interconnected. As brains increase in complexity from species to species, you don’t just get more neurons, you also get more efficient neurons. Both can handle more traffic.

The study used Seattle and Chicago as examples. You couldn’t just take Seattle and triple it to become Chicago. The traffic corridors wouldn’t be able to handle the increased flow. There wouldn’t be enough on ramps and off ramps, and the ones that did exist would be would be too small. The services and support needed to accommodate the population wouldn’t be efficiently planned. As cities grow, they evolve to meet the needs of their citizens. Every time I visit New York, it amazes me that Manhattan can work at all. It seems to be an impossibly delicate act of magic..keeping that many people on an island fed and functioning. This is one of the reasons high growth cities struggle to keep up with infrastructure such as required freeways and public transit – they’re growing faster than the infrastructure, handcuffed by the need for administrative approval, can change to support them.

And if I think Manhattan is a miracle, the complexity of what the human brain has to deal with daily represents a feat of impressiveness several magnitudes greater. Indeed, the functioning of the human brain is so complex, all the combined efforts of science have barely scratched the surface of how the damned thing actually works.

The Emergence of the Internet

This common theme of functional evolution and patterns emerging from complexity is also playing out currently on the Internet. Much like Industrial age Manchester, the Internet is growing exponentially without any master plan. And yet, it seems to work. And, as the internet evolves, just like brains and cities, it becomes more interconnected. Functionality is increased through API’s and mash-ups. The internet is evolving into an incredibly complex ecosystem that is remarkably workable. And, like all complex systems, the emergence of workable patterns will depend on a handful of universal rules: the ability to find information, the ability to do things, the ability to talk to people, the ability to have fun and the ability to buy stuff. That’s all we really want and the Internet will naturally emerge in the way best suited to accomplish those simple goals.

The Top 10 Reasons We Love Top Ten Lists

Somedays it seems to me that the whole world has become a search results page. I fear we have become obsessed with ranked and ordered lists. I’m not sure what it is in the human psyche that loves lists conveniently numbered for our perusal, but heaven knows we’re suckers for the Top Ten.

The Internet has fed this addiction to the point that I feel like the whole world can be sorted like an Excel spread sheet. Sort my best friends by geographic proximity and likelihood to lend me a wheelbarrow. Rank all the parties my teenage daughter will be invited to this year by availability of alcohol, physical presence of dictatorial parents and incidence rate of teenage boys who think they “have a shot”. Give me a list of the 10 things my wife hates so I can create a Pivot Table of my odds of doing one of them in the foreseeable future.

As any direct marketer, blogger, magazine publisher or show organizer will tell you, slapping the “Top Ten” on the front of anything virtually guarantees you an audience: The Top Ten Hot Dog Stands in Manhattan, The Top Ten Ways to Get Rich if You Love Wearing Pajamas All Day, The Top Ten Christmas Crafts that Can Be Made From Recyclable Yard Waste..It’s like we’re being spoon fed our lives by some idiot with a ranking algorithm for everything.

Why are we like this? Well, I think it’s because thinking is hard. It’s much easier to take someone else’s opinion about something, especially when it’s offered in the irresistible format of a ranked list. We can choose to agree or disagree, but we don’t actually have to think about it too much. Someone else has done it for us. Also, we travel in social herds, so it’s really important to know what everyone else feels about anything. And finally, the world just has too much complexity now. There are too many choices to think about in every aspect of our lives, even the stupid ones. I don’t really want to spend a lot of time wondering who the Ten Sexiest Olympians are this coming February. I know somewhere some obliging magazine publisher or blogger will do that Herculean intellectual task for me.

I guess ordered lists offer us the illusion of control. If we can slow the frenetic pace of the world down by looking at a list that someone has conveniently put numbers beside, our lives seem a tiny bit more orderly and organized. Yes, I know the economy and the environment is going to hell in a handbasket, yes, I know the global forces of power and control are undergoing a fundamental shift, but right now I’m focused on the 7 Greatest Reality TV Show Moments of 2009. I’ll worry about global warming some other day.

Of course, the urge to put a numbered list in as part of this post is overwhelming (get it..irony), so, I’ll give you the “Top 8 Reasons Why I Gave In and Did It”:

  1. I have the bladder control of an 80 year old man and have already had 2 cups of coffee, so I had to finish this post somehow
  2. I really want to see just how many of you will Tweet this list because you’ve been helplessly programmed to do so
  3. I’m obsessed with PostRank and I spend way too much of each day worried about my Engagement Score
  4. Given the choice between thought provoking content and a cheap laugh, guess which way I’ll always lean
  5. I’m still figuring out how numbered lists work in my blogging platform and needed the practice
  6. I felt guilty teasing you with a title about Top Lists and felt obliged to deliver. See, I really care about you, my readers and didn’t want to disappoint you
  7. I wanted to prove to my daughters that my brain is still capable of counting up to 8. There has been some question lately
  8. I believe that children are our future (Okay, I ran out of reasons, but I felt that Whitney deserved a plug because she’s trying really, really hard)

Two Different Views of Tweeting

DigitalNativeComparison2Last week in San Jose, I was talking to a group of marketers about how digital natives and digital immigrants use social networking. Inevitably, the subject of Twitter came up. In our recent BuyerSphere research, we found that Digital Natives (the younger generation that grew up with technology) use Twitter or microblogging platforms more than Digital Immigrants (the older generation that adopted technology as adults). Someone in the audience said that he thought it was common knowledge that younger people don’t “tweet” but older people do, running counter to our research. The following chart shows the percentage of difference in time spend each week between the Digital Natives and Digital Immigrants in our sample:

As you can see, Digital Natives spend significantly more time on social networks and Twitter..almost 50% more time than Digital Immigrants. Yet, Twitter is labeled as an older person’s platform. Today, from the PEW Internet group, new numbers came out on Twitter usage that seem aligned with our findings:

emarketertwitterThe core audience for Twitter is squarely in the Digital Native age group. I think the answer lies in how the respective groups use Twitter. And this difference in usage and attitude extends beyond Twitter to almost any social networking platform.

The Digital Immigrant views Twitter as a tool. It’s a way to get information out, build traffic to a blog, connect with someone. We treat it as technology that offers us another way to get things done.

But for the Digital Native, Twitter is just part of the world they live in..like air or water. They don’t treat it as technology. It simply is. This attitude towards technology as not being technology is common amongst Natives. They don’t have the same “Gee Whiz” awe of technology. They’re not constantly comparing Twitter or Facebook against the good old days. Why should they? For them, this is just part of the world they live it..there is no reference point in the past. That’s why Natives spend substantially more of each week interacting with technology that connects them with their lives and social circle. For myself, FaceBook is a destination, as is Linked In or Twitter. I only go there when I need to do something. But for the Native, it’s just part of their environment.

Finally, I want to share the view of another Digital Immigrant, Comedian C.K. Louis, who ranted about the Native lack of appreciation for technology.

The Cult of Technology

We held our B2B Expert Face-to-Face event yesterday in Redwood Shores, CA. Yes, we asked people to drive to the west side of the bay the same day the Bay Bridge was closed. Needless to say, it impacted our attendance somewhat. But it was also a smaller, more intimate opportunity to really talk about the challenges common in B2B digital marketing. The common themes that emerged what a tendency to “peg” search as direct response marketing, the realization that B2B is slower to adopt digital than B2C, the difficulties presented by the fragmentation of the B2B marketplace and why we’ve tended to silo off our digital strategies from the rest of our marketing. Most of the discussion came from the findings of the BuyerSphere Project, the extensive research we conducting into B2B buying behaviors.

Every timeI talk to a group of assembled search marketers, I can’t help but feel the palpable frustration in the air. The gulf between those that understand digital (particularly search) and those that don’t can seem impossible to bridge. We feel tied down by those within our organization that seem mired in the old way of doing things. Why the hell can’t everyone see the world as clearly as we can. Also, I mentioned that as marketers, we tend to focus too much on technology and not enough on the people that interact with that technology. Few companies invest in qualitative research As we chatted at the Hotel Sofitel In Redwood Shores, a thought struck me. One on the problems may be that we’re all too much alike. We’re suffering from cultural homogeneity.

If you look at most elements of human nature, there it a typical normal distribution curve, otherwise known as the Bell Curve. The majority of the population clusters around the mean, at the center of the curve. As you move further out, you have more deviation from the mean. The diversity of us humans: whether it be intelligence, wealth, behaviors, physical abilities or size, tends to spread out on this curve.

bell_curve

The same is true, as Everett Rogers discovered, about how quickly we adopt technology or (one supposes) adapts to change. His technology diffusion curve followed the typical Bell Curve model. A few of us adopt technology almost as soon as it becomes available. A few of us avoid adopting technology until it becomes common place for everyone else. The vast majority of us fall somewhere in the middle.

technology diffusion
But what happens when you’re constantly surrounded by people at one spot on the curve? What if everyone you knew had an IQ of 123, or you lived in a town where everyone was 6 feet 3 inches tall? Soon, you’d fall into the trap of thinking this represented the norm. If you never saw diversity, you’d start to forget that it exists.

This is almost never a healthy state of an affairs. A common ideology amongst the heads of Nazi Germany lead to a drive for cultural homogeneity. The unbelievable wealth that surrounded the French aristocracy (or the Russian, for that matter) led to revolts of the masses. History has not proved to be kind to groups that are too much alike in one aspect. At best, this homogeneity gives you a skewed view of the world that may cause you to make decisions that don’t map well to the general population.

And that, I realized on Wednesday morning, may be exactly what is happening to us digital marketers. We are in this business because we all love technology. We are all classic early adopters, lying at least one (and I suspect closer to two) standard deviations from the norm, here at the thin leading edge of the Bell curve. And because we are surrounded by others like us, we start to lose sight of what the large bulge in the middle is doing. We chase technology with an obsession worth of sex starved teenagers. Every digital marketer I know has a smart phone. More than half the digital marketers I know have iPhones. If you travel in the same circles as I, you would soon think that everyone has an iPhone. Yet the iPhone market share in the US is  still only 11% (although it’s growing quickly). Like I said, we live on thin edge of the curve.

I think this skewed view of the world makes us exactly the wrong people to be planning digital marketing strategies aimed at the general public. We live in a cult of technology. We’ve forgotten how the common person lives with their hopelessly antiquated mobile phone and without a Linked In profile that includes at least 500 connections. There are many, many people out there who have never Tweeted, don’t have a blog and are unsure what RSS means. They include almost all my relatives. Yet we never seem to take them into account where we’re salivating over the latest strategy for generating buzz on social networks.

So, how does a digital marketer keep their perspective when they’re so far removed from normality? They have to become digital anthropologists. They have to live with their prospects, watching them in their daily routines. They have to discover the way we were meant to discover, by watching other people, helping us to understand and empathasize with them. Evolution has equipped us with some very subtle tools for understanding other people when we’re face-to-face with them. To my knowledge, however, it hasn’t given us an inherent ability to generate pivot tables in Excel. Maybe we should spend more time doing what we were meant to do: hang around with real humans instead of technology.

In Search of Usefulness

First published October 29, 2009 in Mediapost’s Search Insider

A few years ago, I interviewed usability expert Jakob Nielsen about where search might go in the future. He shared an interesting insight:“I think there is a tendency now for a lot of not very useful results to be dredged up that happen to be very popular, like Wikipedia and various blogs. They’re not going to be very useful or substantial to people who are trying to solve problems.”

That stuck with me. Relevance, as determined by search algorithms, and usefulness are not the same thing. And then, John Battelle touched on the same topic in a blog post a few months back:  “So first, how would I like to decide about my quest to buy a classic car? Well, ideally, I’d have a search application that could automate and process the tedious back and forth required to truly understand what the market looks like.”

Navigating Complex Decisions

Again, this concept of usability comes into play. Let me give you another example. As my regular readers know, I love to travel with my family. But the available travel sites still require the tedious back and forth that Battelle talks about.

We’re not big on hotels or restaurants. We love home exchanges or renting apartments and homes directly from the owner.  We tend to fly on mileage points. We don’t take bus tours, but we do rent cars. We prefer staying in smaller towns rather than big cities. And our first day in a new location always involves a trip to the nearest grocery store.

There is no online destination that brings all the usefulness I need together into one place. I manually pull information from VRBO.com, Homeexchange.com, TripAdvisor.com, Kayak.com and a dozen other sites.

Planning a family holiday is a lot of work, but I’m willing to do it because it’s fun for me. What about tasks that aren’t as much fun? What about the planning that has no inherent reward, like a complicated purchase for your company, or a forced move to a new city? The title of Battelle’s post was “Search Frustration: It’s Still Hit or Miss on Complex Decisions.” I can relate.

This was the approach Microsoft decided to take with Bing.com, the “Decision Engine.” I think their instincts and strategy are right, but the execution is off. If I search for Bristol, England (we’re doing a home exchange there next summer) on Bing, I still see a pretty standard search results page. It’s not that useful to me.

I agree completely that there’s a strong need for more usability in search. Google’s Achilles heel at this point is its focus on relevance at the expense of usability.  We need a much deeper, more useful experience. Relevance is a poor proxy for usefulness. It still leaves all the heavy lifting up to the user.

Search or Decision Engine? Just Decide!

“Usefulness” is a difficult trick to pull off. It’s a tough road that Microsoft has chosen. But if you’re going to do it, commit fully to it. Don’t play the safe middle ground. This is not the place for half measures.

Whether by design or by luck, I think Microsoft picked the one area where Google is most vulnerable, but right now there isn’t enough differentiation between the two. If Microsoft truly wants to be a “decision engine,” its strategists have to build from the ground up to offer more usefulness.  I’m now four clicks into Bing for “Bristol, England” and still haven’t found anything particularly useful to me. Four clicks are way too many. The information forager in me would have already moved on to a new destination.

The next three years in search will be about aggregation of information and incorporating usefulness. Search will do much more than just organize the world’s information; it will allow you to do something with it. Search will become the ultimate mash-up. And increasingly, those intersections will happen on mobile devices. Microsoft is the only one of the major players to have declaratively set sail in that direction. My advice? Forget what search is today and move with all possible speed to what search needs to become tomorrow.

Talking Search with Dr. Jim Jansen at Penn State

JimJansen032105This is the full transcript of an interview with Professor Jim Jansen at Penn State University. Excerpts from the Interview are running in two parts (Part One ran a few weeks ago) on Search Engine Land. I wrote a column that provided a little background on Dr. Jansen on Search Engine Land.

Gord:
Jim, we’ll start by laying out some of the research you’ve been doing over the past year and a half and then we’ll dig deeper into each of those as we find interesting things. Just give me the quick 30- or 60-second summary of what you’ve been working on in the last little while.

Jim:
I have several research projects going on. One that I really find interesting is analyzing a five calendar year search engine marketing campaign from a major online retailer and brick-and-mortar retailer. It’s about 7 million interactions over that time, multi-million dollar accounts and sales and stuff. A fascinating temporal analysis of a search engine marketing effort.
I’ve been looking at that at several different levels – the buying funnel being one, aspect of branding being another, and then the aspect of some type of personalization, specifically along gender issues. And so that’s been very, very exciting and interesting and (has offered) some great insights.

Gord:
I’m familiar with the buying funnel one because you were kind enough to share that with me and ask for my feedback, so let’s start there. I know you went in to prove out some assumptions, for example, is there a correlation between the nature of the query and where people would be in the buying funnel? Is there identifiable search behaviours that map to where they might be in their purchase process? What did you find?

Jim:
I looked at it at several different levels. One goal was to verify whether the buying funnel was really a workable model for online e-commerce searching or was it just a paradigm for advertisers to, you know, get their handle around this chaos. And if it’s an effective model, what can it tell us in terms of how advertisers should respond?
In terms of the first question, we had mixed results. At the individual query level you can classify individual queries into different levels of this buying funnel model. There are unique characteristics that correspond very nicely to each of those levels. So in that respect, I think the model is valid.

Where it may not be valid is specifying this process that online consumers go through. We found that, no, it didn’t happen quite like we assume.  There was a lot of drop-out and they would do a very broad query and that might be all.
So we looked at the academic literature – you know, what theoretically could deal with that or explain that? – and the idea of sufficing seemed to fit. If it is a low cost, they won’t spend a lot of time, they will just purchase it and buy it.
In terms of classifying queries in terms of what advertisers’ payoff is, I think the most interesting finding was that the purchase queries – the last stage of the buying funnel – were the most expensive and had no higher payoff than the awareness or the very broad, relatively cheaper queries. From talking to practitioners, that is a phenomena that they have noted also … which is why a lot of people bid still on very broad terms, to snatch these potential customers at an early stage.

Gord:
Based on what you’ve seen, there are a couple of really interesting things. You and I have talked a little bit about this, but we similarly have found that you can’t assume a search funnel is happening because people use search at different stages and they’ll come in and then they’ll drop out of the process, and they may come in later or they may not, they may pursue other channels. But the other thing we found is sometimes there’s a remarkable consistency in the query used all the way through the process and that quite often can be navigational behaviour. It can be people who say, “Okay, the last time I did this, I searched on Google for so-and-so and I remember the site I found was the third or fourth level down,” and they just use the same route to navigate the online space over and over again. If you’re looking at it from a pure query level, it’s a bit of a head-scratcher because you’re going, “Well, why did they use the same query over and over?” but again, it’s one of those nuances of online behaviour. Did that seem to be one of the possible factors of some of the anomalies in the data?

Jim:
Well, that trend or something similar to it has been appearing in a lot of different domains and researchers are attributing it to “When I do a query, I expect a certain result.” So, you know, a query that may be very informational, what we’re finding is that searchers expect a Wikipedia entry. So in other words, a very navigational intent behind that very informational query. And I think the phenomena you’re describing is very similar. We have a transactional-type query and users are expecting a certain web page, a navigational aspect, and that “Okay, I have an anchor point here that I’m going to go to.” And then off search engine, maybe they do more searching and actually do some type of buying funnel process. But at the search engine, yes, we’re seeing a lot of that navigational aspect. I just looked at a query log from a major search engine and an unbelievable amount of queries were just navigational in nature.

Gord:
We’ve certainly seen that. A lot of our recent research has been in the B2B space, so it’s a little bit different but certainly it follows those same lines. When we looked at queries that people would use, a large percentage of them were either very specific or navigational in nature.

You know, the idea of satisficing, of taking a heuristic shortcut with their level of research is also interesting. It seems like if the risk is fairly low, the online paths are shorter. Is that what you were finding?

Jim:
Yes, and the principle of least effort is how it’s also presented. We see it in web searching itself generally in how people interact with search engines and how they interact with sites on the web. They may not get an optimal solution, but if it’s something that’s reasonable and if it’s good enough, they’ll go for it. That seems to be occurring in the e-commerce area also: “I want to buy something relatively cheap. This particular vendor may not have the best price, but it’s close to what I’m thinking it should be. Just go and get it done, get it over with, buy it.”

Gord:
I would suspect that that would also be true in product categories where you have mentally a good idea of what an acceptable price range would be, right?

Jim:
Yes.

Gord:
So if it’s a question of making a trade-off for $2 but saving yourself a half hour of time, as long as you’re aware of what those price ranges would be, you’re more apt to make that shortcut call, correct?

Jim:
Yes. It does assume some knowledge and risk mitigation –if it’s a small purchase and that varies a little bit for each of us, but you’re willing to cut your costs of searching and trying to find the best deal just to get it done.

Gord:
I suspect part of this would also  be your level of personal engagement with the product category you’re shopping in. So I’ll spend way too much time researching a purchase of a new gadget or something that I’m interested in just because I have that level of engagement. But if it’s a purchase that’s on my to-do list, if it’s just one task I have to get done and then move on to the next thing, I suspect that that’s where that satisficing behaviour would be more common.

Jim:
Yes. Now you bring up a really good point. If it becomes entertainment – like a gadget that you enjoy researching – it’s no longer work, it’s no longer something you get done. The process of doing it makes it enjoyable so you don’t mind spending a lot of time. In those kind of cases, the goal really is not the purchase, the goal is the looking.

Gord:
We found that alters the behaviour on the search page as well. So if it’s a task-type purchase where I just have to go and get there, you see that satisficing play out on the search page too. Typically when we look at engagement with the search page, you see people scan the top four, three or four listings. If it’s that satisficing type of intent where they’re saying, “I just want to buy this thing,” you’ll see people scan those first three or four and pick what they feel is the path of least effort. They go down and say, “Okay. It’s a book. Amazon’s there. I know Amazon’s price. I’m just going to click through and order this,” but if it’s entertainment, then suddenly they start treating the search page more like a catalogue where they’re paying more attention to the brands and they’re using that as a navigational hub to branch off to three or four different sites. Again, it can really impact the nature of engagement with the web… or with the search page.

Jim:
Absolutely, and I really like your analogy of a catalogue. You know, there are some people that love just looking at a catalog – flipping through it, looking at the dresses and shirts or gadgets or sporting gear or whatever. And so that’s a much different engagement than flipping through the classified ads trying to find some practical thing you need. The whole level of engagement is at totally opposite ends of the spectrum, really.

Gord:
As an extreme example of that, we did some eye-tracking with Chinese search engines and we found that with Baidu in particular, people were using it to look for MP3 files to download. So when we first saw the heat maps – and of course it was all in Chinese, so I could understand what the content on the page was without having it translated – I saw these heat maps going way deeper and much longer than we ever saw in typical North American behaviour. We saw a level of engagement unlike anything we had ever seen before. And it was exactly it. It was a free task – They were looking for MP3 files to download and they were treating the search page like a catalogue of MP3 files. They were reading everything on the page.  I think that’s just one extreme example of this catalogue browsing behaviour that we were talking about.

Let’s go to one of the other findings on the buying funnel: that quite often the more general, broader categories from an ROI perspective can perform just as well as what traditional wisdom tells us is your higher return terms.  Those closer to the end of the funnel – the ones that are more specific, longer, more transactionally oriented. What’s behind that?

Jim:
Like a lot of these questions there’s no simple answer because there are plenty of exceptions to the rule you just described. There are some very broad terms that are very cheap, others that are very expensive. On the purchase side, there are some key phrases that are very cheap because they’re so focussed and others are expensive. But in this particular analysis – and again, this was 7 million transactions over 33 months, from mid-2005 to mid-2008 – the awareness terms were cheaper than the purchase terms and they generated just as much revenue.

I think a lot of it is that perhaps the items this particular retailer was selling fell into that sufficing behaviour: gifts, fairly low-cost items – there was just no need to progress all the way to that particular purchase phase.

To me it was really very unexpected. I really expected those purchase terms to actually be cheaper because they were more narrowly focussed and to generate more revenue, but it didn’t turn out that way.

Gord:
That brings up an interesting point we’ve seen with client behavior, especially given the current economic condition. We found is a lot of clients are tending to optimize down the funnel – they are tending to look at their keyword lists they’re bidding on and move further and further down to more and more specific phrases, because the theory is – and generally they do have analytics to back this up – that there’s greater ROI on that because these are usually people that are searching for a specific model or something which is a pretty good indicator that they’re close to purchase. But I think one of the by-products of that is as people optimize their campaigns, those long tail phrases are getting more and more expensive because there’s more and more competition around them, and as people move some of their keyword baskets away from those awareness terms, maybe the prices on that, it all being based on an auction model, are starting to drop. Do you think that could be one of the factors happening here?

Jim:
That very well could be. The whole online auction is designed around (the concept that) as competition increases, cost-per-clicks will increase also. It also may be that those particular customers don’t mind clicking on a few links to do some comparison-shopping and may end up going somewhere else. They may have a higher aspect of intent to purchase, but the competition among where they’re going to buy is more intense.

You know, compare that to this sufficing shopper: you just have to get that person’s attention first with a reasonably priced product and you will make the sale. That is the one issue with analytics in terms of transaction log analysis – we can analyze behaviours and we can make some conjectures about what happened, but you need lab studies and surveys to pan all data, to get the why part.

Gord:
That’s a great comment and obviously something that people have heard from me over and over again, because we do tend to focus more on the quantitative approach. I think this goes back to what we were talking about originally –online information gathering is a natural extension of where we are in our actual lives so it’s not like a distinct, contained activity. It’s not like we set aside an hour each day to go through all our online research. More and more, we always have an outlet to the internet close by and as we’re talking or as we’re thinking about something, it’s a natural reaction just to go and use a search engine to find out more information. And I think because it’s such a natural extension of what’s happening in our day-to-day lives, that the idea of this one linear progression through an online research session isn’t the way people act. I think it’s just an extension of whatever’s happening in our real world. So we may do a search, we may find something, it may be an awareness search, and then we may pursue other paths to the eventual purchase. It’s not like we keep going back and forth between a search engine with this nicely refined search funnel. It’s not that neat and simple, just like our lives aren’t that neat and simple.

Jim:
Yes, all models get rid of all the noise that reflect reality. So the neater they are, the less accurate they are, and the buying funnel is obviously very neat and so I think it’s reasonable that it represents a very small number of searches that actually progress exactly like that. We’re very nonlinear in things we do and so I assume our purchase behaviors are too.

Gord:
I want to move on to the question of branding a little bit, because you mentioned that that was one of the areas you were looking at. And at Enquiro, we’ve done our own lab-based studies on branding, so I’d be fascinated to hear what came out as far as the impact of branded search.

Jim:
This year, I’ve really got into this whole idea of branding in terms of information seeking. That’s really my background, web searching and how people find and assemble information. One of my first studies was to look at the comparison of what a search engine brand would do to how searchers interpreted the results. So I ran a little experiment where I switched the labels from Google, Yahoo, and MSN, and the results were the same. Certainly the search engine brand has a major lift to it.
In this particular study using the search engine marketing data, we did multiple comparisons of brand or product name and the keyword in the title, in the snippet, in the URL to see if there was a correlation with higher sales. And without a doubt the correlation between a query with a brand term and an advertisement with a brand term is extremely, extremely positive. That particular tightness seems to resonate with online consumers.

Gord:
So just to repeat, so if somebody’s using a branded query and they see that brand appear in the advertising, there’s obviously a statistical correlation between the success of that, right?

Jim:
Yes. In that particular case, one, that the click will happen, and two, that the click will result in a sale was yes, very positive. It really relates to the whole idea of dynamic keyword insertion in advertisements…

Gord:
So to follow that thread a little bit further, obviously if people have a brand in mind and they see that brand appear, then that’s an immediate reinforcement of relevancy. But what happens if the query is generic in nature, it’s for a product category, but a brand appears that people recognize as being a recognized and trusted brand within that product category? Did you do any analysis on that side of things?

Jim:
Not specifically. No, I did not. That’s a real good question though, but no, I did not do that type of correlation.

Gord:
The last thing I want to ask you about today, Jim, is this idea of personalization by gender. I believe from our initial discussions that you’re just in the process of looking at the data from this portion. Is that right?

Jim:
Well, we finished the analysis. Now we’re just writing it up.

Gord:
So is there anything that you can share with us at this point?

Jim:
Again, the results to me were counterintuitive from what I expected. Usually, the idea of personalization is that the more personalized you get, the higher the payoff, the efficiency and effectiveness is. We took queries from this particular search engine marketing campaign and classified them based on gender probability using Microsoft’s demographic tool, which will classify a query by it’s probability of being male or female. We looked at it this way: now whether the searcher was male or female but did the particular query fit a gender stereotype – did it have a kind of a male, for example, feel to it or stereotype implications.

Gord:
So more women would search for “Oprah,” and more men would search for “NASCAR”?

Jim:
Exactly.

Gord:
What did you find?

Jim:
In terms of sales, far and away the most profitable were the set of queries that were totally gender-neutral. We took the queries and divided them into seven categories: “very strongly male,” “generally male,” “slightly male,” “gender neutral,” “slightly female,” “strongly female,” “very female.” By two orders of magnitude, the most profitable were the ones that were totally gender-neutral.

Gord:
Fascinating.

Jim:
Yes, as a researcher who does personalization research, my guess would be “Ah, the more targeted they are, the more profitable.” But no, the means were two orders of magnitude different.

Gord:
So give us an example of a gender-neutral query.

Jim:
We defined gender-neutral to be were queries that the Microsoft tool classified somewhere between-  exactly gender-neutral is zero – up to like 59% either side. So we had a fairly big spread here. And there was a trend that was somewhat expected –  that the queries that were more female-targeted generated higher sales than the corresponding male counterparts.
So here’s some examples of queries based off the Microsoft tool:  “Electronic chess,” 100%. You know, the Microsoft tool classified that 100% male. For a gender-neutral query, I’ll just randomly pick up a couple here: “Atomic desk clock.” “Water purifier.”

Gord:
I know you’re just writing this up now, but any ideas as to why that might be?

Jim:
One thing that is coming out in the personalization research is that at a certain level, we have totally unique differences. You can personalize to a general category and to a certain level, but beyond that, it’s either not doing much good or may actually get in the way. And that may be something that is happening here – that these particular, very targeted gender keyword phrases are just not attracting the audience that the more gender-neutral queries and keywords are.

Again, it’s a “why” thing.  We spend a lot of time in web search trying to personalize to the individual level and really haven’t got very far. But now people are trying to do things like personalize to the task rather than the individual person, and there’s some interesting things happening there. Spell checks and query reformulations and things like that are very task-oriented rather than individual searcher oriented.

Gord:
I remember Marissa Mayer from Google saying that when Google was looking at personalization, they found by far the best signal to look at was what’s the string, what immediately preceded the search or a series of search iterations. They found that a much better signal to follow than trying to do any person-level personalization, which is what you’re saying. If you can look at the context of the tasks they’re engaged in and get some kind of idea of what they’re doing or trying to accomplish in that task, that’s probably a better application of personalization than trying to get to know me as an individual and to try to anticipate what I might say or query for any given objective.

Jim:
Yes, It’s just so hard to do. You know, Gord is different than Jim, and Gord today is different than Gord was five years ago. Personalizing at the individual level is just very difficult and may not even be a fruitful area to pursue.

Gord:
I remember when Google first came out with talking about personalization there was this flurry around personalization in search. That was probably two, two and a half years ago and it really seems to have died down. You just don’t hear about it as much. And at the time I remember saying that personalization is a great thing to think of in ideal terms – you know, it certainly would make the search experience better if you could get it right or even half-ways right, but the challenge is doing just that. It’s a tough problem to tackle.

Jim:
Yes, and as you mentioned earlier, we’re nonlinear creatures, we’re changing all the time. I can’t even keep up with all my changes and I can’t imagine some technology trying to do it. It just seems an unbelievably challenging, hard task to do.

Gord:
I think the other thing is – and certainly in my writings and readings this becomes clearer and clearer – that we don’t even know what we’re doing most of the time. We think we have one intent but there’s much that’s hidden below the rational surface that’s actually driving us. And for an algorithm to try to read something that we can’t even read ourselves is a task of large magnitude to take on.

Jim:
That’s a really good way of looking at it. I’ve commented on that before in terms of recommending a movie or book to me. I don’t even know what books and movies I like until I see them. Sometimes I pick up a book and say, “Oh, I’m going to really love this,” only to get a chapter into it and realize “Okay, this is horrible.” And I think you see that in the NetFlix challenge –  So many organizations have laboured for a decade now, and finally it looks like perhaps this year someone may win by combing 30 different approaches simultaneously to the very simple problem of “Recommend a movie. It’s just amazing the computational variations that are going on.

Gord:
Amazon has obviously been trying to do this. They were one of the first to look at collaborative filtering and personalization engines, and they probably do it about as well as anyone. But even then, when I log on to Amazon, it’s not that they’re that far off base in their recommendations to me, but given what I buy on Amazon, it’s like they’re dealing with this weird fragmented personality because one time I’m ordering a psychology textbook because it has to do with the research I’m doing for something and the next time I’m turning around and ordering a DVD box set of The Office or even worse, the British version of The Office which really throws it for a loop.

Jim:    [laughs]

Gord:
Then I’m ordering a book for my daughter like Twilight.  Amazon is going, “I don’t know who this Gord Hotchkiss is, but he’s one strange individual.”

Jim:
From my interaction with Amazon, the recommendations I have found most effective are “You bought this book. Other people that bought this book bought these books” which I view as a very task-oriented personalization. And the other is a very broad, contextual one, “Here’s what other people in your area are buying,” which fascinates me. It’s almost like a Twitter, Facebook, social networking thing: “Oh, wow. I like that book,” you know? These task-oriented context personalizations, at least in my interactions, have been the most effective.

Gord:
You obviously bring up that intersection between social and search, which is getting a lot of buzz with the explosion of Twitter and the fact that there’s now real-time search that allows you to identify patterns within the complexity of the real-time searches. We’ve known in the past in other areas that generally those patterns as they emerge can be pretty accurate, so that opens up a whole new area for improving the relevancy of search.

Jim, one last question while we’re talking about personalization. This is something I wrote about in an article a little while ago and I’d love to get your take on it as the last word of this interview. We were talking about personalization and getting it right more often, and the fact is the way we search now, engines can be somewhat lax in getting it right. There’s a lot of real estate there, we scroll up and down. The average search page has something between 18 and 20 links on it when you include the sponsored ones. It’s more like a buffet: “We’re hoping one of these things might prove interesting to you or whet your appetite.” But when we move to a mobile device, the real estate becomes a lot more restrictive and it becomes incumbent on the engines to get it right more often. We can’t afford a buffet anymore, we just need that waiter who knows what it is we like and can recommend it. What happens with personalization as the searches we’re launching are coming from a mobile device?

Jim:
That’s a great question. I think it’s one of those areas that have got a lot of talk – everybody is saying (again) “This is the year mobile searching’s going take off.” It’s been going on for four or five years now, and really, I mean at least here in the US, it hasn’t really happened yet. But what I think is going to make it hit the mainstream is this combination of localized search.
When you have a mobile device, the technology has so much more information about you: it’s got your location to within a couple feet, the context that you’re in can really start entering the picture and information gets pushed to you –I’m thinking tagged buildings and restaurants and cultural events and on and on. And so with my mobile device, where I can talk into it, I don’t even have to type anything. I want “what’s going on in the area?” and it automatically knows my location and the time and perhaps something about me and the things that I’ve searched on before. “Oh, you like coffee shops where there’s some music playing. Guess what? Boom. There’s five right near, in your area that have live entertainment right then.” So I think in that respect it’ll be a little more narrowed search, but the technology will have so much more information about us that in a way it makes the job easier. The problem’s going to be the interface and the presentation of the results.

Gord:
We’re talking about, you know, subvocalization commands and heads-up display. You start looking at that and say, “Wow, that would be pretty cool,” but…

Jim:
Yes. Imagine being able to walk through a town … I live in Charlottesville, Virginia. Tons of history here from 400 years ago when Europeans first settled here, Thomas Jefferson, James Madison, etc., etc. Being able just to walk down Main Street and have tagged buildings interface with my mobile device… I’m a big history buff and so getting that particular information, one, pushed to me or at least available to push when I ask for it is a wonderful, wonderful area of personalization. This idea of localized search and mobile devices and mobile search may be the thing that brings it all together and makes mobile search happen.

Gord:
It’s fascinating to contemplate. And I know I promised that was going to be my last question, but I’m going to cheat and squeak one more in, and it’s really a continuation. You remember the old days of Longhorn with Microsoft, when they were working what eventually became Vista. They were talking about building search more integrally into everything they did and they had this whole idea of Implicit Query – which really excited me because if anyone knows what you’re working on at any given time, it should be Microsoft, at least on the desktop. They control your e-mail, they control your word processing, they control your calendar. If you could combine all this… all those as signals – the document you’re writing and the next appointment you’ve got coming up and the trip you’re taking tomorrow – imagine how that could intersect with search and really turn into a powerful, powerful thing. I remember saying…this was years ago… “That could kill Google. If Microsoft can pull this off, that could be the Google killer.” Of course we know now that that never happened. But if we take all that integration and all that knowledge about what you’re doing and what you’re doing next and where you are and move that to a mobile device, that’s really interesting. In looking at where Google is going, introducing more and more things that compete directly against Microsoft… is that where Google’s heading, to become our big brother that sits in our pocket and continually tells us what we might be interested in?

Jim:
You know, the “Big Brother” idea label has certain negative connotations, so I don’t want to say that they are Big Brother-ish in that regard. But certainly I think with their movement into free voice and free directory assistance, they will soon have a voice data archive that will allow them to do some amazing things with voice search, which would be an awesome feature for mobile devices. Being able to talk into a mobile device, have it recognize you nearly 100% of the time and execute the search.
Google of course is the one that knows what they’re doing, but certainly I think it would be naive not to be exploring that particular area. And I think the contrast from what you said about Microsoft and the desktop, the desktop is just so busy. You’re getting so many different signals in terms of business, personal things, my kids use my computer sometimes. And so the context is so large on the desktop, but the mobile device, it’s narrower. You know, you have some telephone calls, you can do some GPS things, so the context is narrower but very, very rich in that very narrow domain. I think it’s a really hot area of search.

Print or Screen: The Zen of Reading

A very interesting post landed in my in-box yesterday. It came from The Chronicle of Higher Education and it looked at a recent paper by Anne Mangen in the journal of Research in Reading (2008, pp. 404 – 419), titled “Hypertext fiction reading: haptics and immersion.” (I know..absolutely gripping title)

Mangen touches on a fascinating aspect of reading, specifically, the tangibility of reading. The look, feel, heft and smell of a book vs. the disembodied experience of reading from an electronic screen: “Unlike print texts, digital texts are ontologically intangible and detached from the physical and mechanical dimension of their material support, namely, their computer or e-book (or other devices, such as the PDA, the iPod or the mobile phone”

I’ve always disliked reading from a screen. Often, I even print off documents so I can review the old fashioned way. And I love books. If you want to want me to crack like a cheap plastic wine glass at a family reunion, put me in a room for an hour with no reading materials. I’ll be pacing in a cold sweat in a matter of minutes. I have multiple screens I can read from, and have read a few e-books, but the experience for me is a mere shadow of that feeling of turning a physical page (this, by the way, is what Mangen means by “haptics”).

Mangen says that the technology that enables digital reading actually gets in the way of a pure imaginative rendering of a fictional world. A print book has no distracting technology. A Kindle or iPhone does. These are some pretty heady concepts, but they touch on that vague feeling of dissatisfaction I have whenever I read something in digital form. I just don’t like it as much as a book, so while the rationality of keeping hundreds or thousands of books on my iPhone appeals to me, I still have several bookshelves and cardboard boxes full of books at home. Amazon loves me..a lot!

This whole topic becomes more material to me as I’m getting ready to self-publish my own book. Amazon will be producing the print version, but there will also be an electronic version. I wonder if my preference for paper is a generational thing. One of the topics I explore in the book is the difference between Digital Natives (people born after 1985 who grew up with digital technology) and Digital Immigrants (people born before 1985 who adopted digital technology as adults). Or is it deeper than that? Do we have some inherent bond with books? Do women feel differently than men?

I’ve launched a quick survey to explore this further. It’s only three questions long, so will take you about 40 seconds. I’ll share the results in a future post.

Marissa Mayer: Digital Promiscuity and Digital Loyalty

It was a one minute exchange (via the Valleywag) at the San Francisco Web Summit between Google’s Marissa Mayer and managing WSJ editor Robert Thomson..but it spoke volumes

Thomson accused Google of promoting “digital promiscuity” by devaluing “digital loyalty”. The bone of contention? Google’s font size for quote attributions. People get the info they’re looking for and may never see the contributing source. Moderator John Battelle quipped that he never thought he’d be moderating a panel where the debate was about font size – “Can we reach detente at 7 points?”

One might think that a quibble about font size seems inconsequential, but there’s a lot at play here. First of all, let’s explore this from the user side.

The user is looking for information and they go to Google, because that’s what they always do. They take the fastest and most reliable route to information. In the results, they see what they’re looking for. Now, one of two things is going to happen. Either they’re satisfied with the information they received on the Google results page, or they need more information and they’ll choose the best link. Thomson’s contention is that the font size is too small to allow users familiar and loyal to the WSJ brand to quickly identify the source and to weigh that in their decision. Fair enough, I guess. See for yourself. Here is a screen shot of Google News for the query “Sri Lanka”:

Screen shot 2009-10-23 at 3.09.07 PM

So, here’s where the digital promiscuity charge comes in. Each story has many potential paths to go down, most or all of them away from the original source. The user is free to choose where they go..and I suspect putting the attribution quote in 12 point type won’t really change that. I’ve looked at enough eye tracking to know that. The user is going to follow the strongest information scent, the link best aligned with what they were looking for. Google actually does the contributing source a big favor by putting that link top and in the most popular eye scan path. Mayer would know far more so than Thomson the significant advantage this gives the official source. We’re incredibly lazy when we make our online choices. A .5 inch move of the cursor is a wall too great for many users to bother climbing over.

Also, what is Google doing wrong here? Google’s job is to provide the best information source alternatives for the user. Period. Google is doing the WSJ or any other traditional publication a tremendous favor by indexing their content and introducing that content to the huge number of people that use Google every day. Yes, they get the content, but the WSJ gets the opportunity to grab the eyeballs. Obviously, traditional journalism hasn’t figured out how digital information seeking works in the 21st century.

Which brings me to why Thomson has his knickers in a knot. It’s a elephant sized case of not “Getting It”. This isn’t about digital loyalty. This is about looking for information. This is a transition of power into the hands of the user. The WSJ or any other paper no longer has sole control over a loyal readership, giving it license to push its editorial viewpoint as in days past. It’s not promiscuity..it’s freedom. Freedom to choose the path that suits the user best. Google is simply playing the role of the emancipator here. Here’s something else to ponder. Google would not be in the position to threaten anyone if we had not already made the decision that it is the place we will go for our information. And that includes all those “loyal” readers.

Thomson is in a snit because the WSJ’s revenue models are seriously out of sync with their readership’s preferences. That’s not Google’s fault. I’m guessing the blame lies in the failure of publishing to realize their day in the sun is over. And the only one to blame for that is the public. We’ve moved on. Get used to it.