Evolution Technology and What It Gets You

Note: This post originally served as a marketing paper. Some things change, some things don’t. Most of what’s described in here is in NextStage OnSite, NextStage Experience Optimizer, NextStage Immediate Sentiment and NextStage Veritas Gauge

What is ‘Evolution Technology’?

Evolution Technology increases the effectiveness of website commerce by dynamically adapting presentation to a user’s personality. It makes using a website more comfortable and natural for users and promotes more frequent purchases by presenting opportunities that fit the user’s comfort level.

Evolution Technology’s ability to fine tune presentations allows it to perform targeted marketing and sales to members of different user populations visiting the same website. Other technologies recognize that user B behaves the same as user A and therefore would suggest policies and products to user B that user A was historically interested in or had purchased. Evolution Technology would be able to learn enough about the users by analyzing their usage profiles to determine which of the two was a better candidate for which service or product and tailor its presentation accordingly in real time.

How it Works

Regardless of culture or background, each of us has constructed over our lifetimes a kind of “map” that we use to guide our decisions. This map consists of the habits, perceptions, experiences, and beliefs we rely on to understand and deal with the world we live in every day.

Making a decision of any kind consists, first, of referring to this internal map and identifying various possible “routes,” then, second, applying our internal strategy — our set of unconscious “rules” — for making choices.

Behavior professionals — psychologists, neuroscientists and others — have standardized methods to “read” an individual’s map and identify the rules each individual uses to make decisions. These methods are easily codified.

Once a user’s map is properly understood and the rules are identified, it is possible to rearrange the “territory” of a web site’s presentation to match the individual’s map, making navigation easy and natural and guiding the user to the desired destination. This done, it is equally easy to present purchase choices in a way that conforms to the user’s “rules” for making a decision to purchase.

To date xCommerce and B2x systems rely on such methods as Bayesian Analysis (Autonomy), Syntactic Analysis (Sentient Systems), “Open Profiling” which is variations on ELIZA and HOMR analytic methods (FireFly) and similar tools to generate usage characteristics over time. All of these systems make use of questionnaires, response-analysis surveys, site-surveys and so on to create their demographic profiles.

Evolution Technology doesn’t interest itself with the ‘what’ of each web experience. In other words, Evolution doesn’t care that you bought a book or a sweater online, it is more concerned with the decision process that led you to make those purchases from that particular site at that particular point in time. This grouping of decisions to buy something when you did can be thought of as the ‘why’ of your purchase. Evolution Technology determines why purchases are made and then works to repeat the why experience whenever it finds you or someone who closely matches you online. In other words, once Evolution Technology determines why you made a particular purchase decision it works to recreate as much of the experience of a purchase decision as possible in order to encourage other purchase decisions.

The Result

Evolution Technology’s synthesis of knowledge about human behavior and advanced internet technology dramatically increases the effectiveness of web sites. With each mouseclick, Evolution Technology presents a site that more and more precisely matches a user’s personal “map” and internal “rules” for making decisions. The personalized experience for users encourages comfort, repeat visits and repeat purchases.

Active Selling, The Web’s Missing Link

When a master salesman talks with a prospect, he unconsciously notices and processes dozens of equally unconscious cues from his customer. With each cue, he adjusts his spiel to choose just the right emphasis that will close the sale.

For all the power that the internet has brought to doing business, eCommerce websites lack that master salesman’s talent. They remain essentially passive, waiting for the prospect to choose where the transaction will go — if anywhere.

Active — Not Passive — Listening

Evolution Technology blends all we have discovered about human behavior with the best in web usability studies and advanced design techniques to power websites more like a master salesman.

From the moment a visitor arrives, Evolution Technology is processing subtle cues about that visitor’s interests, choices and preferences. It customizes the presentation to that visitor’s personality before the first link is even followed.

The Advantage

eCommerce sites have an average of only five clicks to capture a transaction before new visitors drift away in boredom or frustration. Any distraction or click that takes a visitor down a blind alley risks losing that customer forever. Some studies show those lost customers represent four out of ten visitors for most sites.

Evolution Technology brings active listening to the website, taking users directly to the places they want and need to go and guiding the visit toward closing a sale that will satisfy the customer. By sensing what the customer wants to see and delivering presentation that meets that search exactly, Evolution Technology dramatically improves the chances for closing, as well as for opening new opportunities and building customer loyalty.

The Difference

Evolution Technology does not rely on cookies or on customers’ actively providing information through filling out forms. Because it is dynamic and not completely reliant on databases of customer information collected in the past, it offers a technology that is unique in the market today.

General Use Case and Discussion

Imagine yourself sitting at your web-browser. You sat down just twenty minutes ago to go through a credit approval process and you’d been putting it off for weeks because you knew you’d have to answer lots of questions, have to look through your files, not be sure you were answering the right questions the right way… In fact, you gave up your Saturday afternoon because you were sure it was going to take hours, probably most of the day, and most of the time you were going to spend had little to do with your connection speed.

But that was twenty minutes ago and now you’re done. Not only are you done, but you’re relaxed. You’re happy. You’re glad. You’re smiling and you’re wondering why the gods smiled upon you.

This was easy. So easy.

You even printed out the forms the website asked you to print out and checked them over to make sure you’d answered the questions correctly, and you did answer them correctly. First time! Amazing!

You’re so impressed at how easily you managed this session and how expertly you navigated the website that you jump up to go tell your mate and your kids.

The only problem is you sent them all to the mall so you’d have the day free and clear with no interruptions and no one to hear you when you cussed the site, the computer, credit card/mortgage companies in general and yours in particular.

Now you’re left scratching the dog’s ears, explaining to trusty Fido how easy and effortless this was.

What happened?

Well, you’re not exactly sure, but you know darn well that you’re going to tell your friends at work and probably your in-laws when you see them tomorrow for Sunday dinner just how easy this was and what a genius you are for being able to get through this so quickly.

As you run your fingers through Fido’s fur, you tell that gloriously good mutt exactly what you’re going to tell your sister and brother-in-law. “How long does it normally take you to get your credit approved? Yeah? Well I did it in less than twenty minutes. No, I’m not! Where’s your computer? You got it hooked to the ‘net? Here. Let me show you.”

You finish by giving Fido a dog-biscuit and then you relax in front of the TV with a good book.

Yeah, this is the way doing business is suppose to be.

But what did happen? To answer that question we need to back up those twenty minutes and invite you to now imagine you’re the credit/mortgage company’s computer. There are lights blinking on and off on your faceplate like eyes waking to the bright morning sun, disk drives are whirring and spinning like arms and legs stretching from a welcome nap, somewhere deep inside your silicon heart electrons are pumping information through hardwired arteries and programmatic veins.

It’s time to go to work, you know. Someone has just browsed onto your company’s website. You also know you’re serving up an Evolution Technology enhanced website. You’re designed to help whoever’s browsing get where they’re going. Because you’re Evolution Technology enhanced, you know that people don’t truly “browse” and don’t truly “surf” the net; they perform what are called directed searches. You know you will benefit them the most in two ways; One, you can quickly help them decide what they’re searching for is something you can’t provide and they should move on. Two, you can quickly decide if this individual is someone you want to do business with (such as recognizing an individual’s a bad risk and encouraging them to go elsewhere for their needs).

But here’s the big one; Because your site is an Evolution Technology enhanced website you can dynamically alter your company’s website presentation to maximize the chances this individual will complete their transaction before quitting, finish what they came to do before moving on, or become so exasperated they decide to call customer service anyway.


What does it mean, “dynamically alter a website’s presentation”, and how do you do that? Are you somehow modifying the basic content of each presentation for individual users?


So you mean what you send to Charlie is subtly different from what you send to Gladys and that the two of those are subtly different from what you send to Pat?


And you’re doing this in real time, click by click, so that what this individual is doing while they’re browsing is influencing your dialogue, tailoring your presentation to a specific, individual audience of one?


That’s kind of what a master salesperson’s does, isn’t it?


Wow. That’s impressive. But I’ve seen and heard all that before. You use some kind of marketing models, right?


Okay. Then you have some kind of personal history database you purchase or tie into, right, so you get a profile of this individual the minute they sign on?


How about this, then; You look at their address and income level and a few other things and run some numbers or something like that, right?


Okay. I give up. What do you do, some kind of magic mumbo-jumbo?

Well…yes…and no.
First off, Evolution Technology enhanced websites begin gathering data on individual users the instant they enter a site. If a person comes to a site from another site via a referral, Evolution Technology uses that referral as part of its identity information. If a person comes to a Evolution Technology enhanced site from another Evolution Technology enhanced site, Evolution Technology will alter and sometimes dramatically individualize the new website’s homepage during the referral process.

You’re kidding.

No, I’m not.

So what are you doing, watching click-throughs and things like that?

Again, yes and no. Evolution Technology does pay attention to click-throughs but lots of stuff is going on before an individual clicks from one presentation to the next. In fact, it may take a few minutes or more for a person to get from a company’s homepage to the page they were looking for. But during that time the individual is actually quite busy and here’s where Evolution Technology comes into play.
Everyone, regardless of their background, their homelife, their job, their this-or-that, manifests what are called psychomotor behaviors. Psychomotor behaviors range from distinctive walks to ways of reading a newspaper. Evolution Technology pays attention to these distinctive behaviors to determine one individual browsing the site from another individual browsing the site.

Yeah, well. How does Evolution Technology know how somebody walks or how they read a newspaper?

That’s our secret, but walk with me a minute and maybe I can show you. Does that sound like something you’d be willing to do?

Okay. You’ve got a minute.

You ever been to a webpage?

Of course.

Ever use a mouse while you’re looking at that webpage?


Ever move the mouse to what you were looking at on that page, to maybe focus your attention on what you were reading? Kind of like using your finger to highlight one line in your DVD burner’s instructions from the rest so you’d get it right?


And if you haven’t done it, ever seen anybody else do it?

Oh, yeah, well, sure.

That’s what Evolution Technology does. It pays attention to little things like that, things that most people aren’t even aware they’re doing.

So Evolution Technology pays attention to where I move the mouse. Big Deal. How much can you learn from that?

You’d be impressed. But Evolution Technology doesn’t just watch where you move the mouse. It does much, much more, and it links what it watches to information that’s too detailed to get into right now, but it does all this so that it learns — even before you make your first click — what types of things work for you and what things don’t. When you click to the next page it’s already subtly changed the presentation so that it’s easier for you to use. It’s kind of like talking to an old friend. Evolution Technology can learn enough and do it quickly enough to finish your sentences for you, so to speak.


Right. And it keeps track of who’s who so it can change the presentation for you, Charlie, Gladys and Pat and deliver the correctly modified content to the right individual as they’re browsing the site. Evolution Technology is true 1-1 marketing, done over the net.

So you’re saying Evolution Technology can take a two hour web session and turn it into twenty minutes, and make me feel glad about it, because it watches me and works to help me?

You got it.

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Working with Prediction Markets via NextStage’s Evolution Technology

Note: This post was originally published as “An Evolution Technology Prediction Markets Case Study”

Seeking Definitions

Like most of you, I read a great deal. That’s where much of my learning and understandings come from. Recently, for example, I was reading about web, behavioral and similar groups analytics and discovered that not all analytics methods and packages work equally well for all companies. The analytics tools which are the best for company A might be the worst for company B because companies A and B have different business models, have different KPIs, define “standard” metrics differently but use the same terms in their definitions, … Companies need to determine what they really want to measure before they can decide the best way to measure it.

ore salt was tossed on the wound when I discovered that many analytics packages aren’t even true to themselves; results for a single metric on a single site can vary wildly, they might add or drop data points due to collection methods, and sometimes what is being reported might not even be what is or should be measured.

Later in that same day I was also reading a history of the use and abuse of the press during times of war. Specifically, I was reading about how the US Pentagon manipulated stories and analysis until it found a metric which military advisers thought both made the military look good and gave the public the sense the military was doing it’s job. The metric they came up with was the body count.

Reading how analytics companies are searching for common definitions and KPIs which make them and their methods look good, and reading only a few hours later about the evolution of “the body count” and how it was and is used, I couldn’t help but appreciate that the language used in both readings was so similar, so directed at arguing the same points for the same reasons, that the two authors could have swapped manuscripts and it wouldn’t have mattered much. Traditional analytics is using body counts, they’re just calling it something different.

History’s Directives

I do not hold any company in error for doing their job, part of which is to convince consumers that the company’s methods, products and services are the standards by which all others should be compared. Any individual or group proclaiming they have the lock on how something should be done always makes me nervous. History demonstrates that the only constant is change, and today’s lock is tomorrow’s open door.

The most basic metrics, the unique visitor and the conversion, are basically body counts. The former is of all troops on the field and the latter is of survivors. We count one and debrief the other. All metrics beyond those basics aren’t often considered — the wounded, MIAs, counts of others who can no longer tell us their story, can’t share what really happened, what really got them where they are.

No one seems to want to count the liberated, the survivors, the wounded and evacuees, the escapees. No one wants to know their name or hear from them directly — they can’t provide actionable economic impact so ignore them.

Yet research shows that these people are the ones with the most interesting stories to tell and that they want to tell us their stories. That’s what people do, they tell stories to each other, some true, some not. It’s how we create communities; we share experience, we seek to touch each other with words if not our hands, and all people do it. Even people who push others away need something to push against, to touch, until the distance is a comfortable one.

These people — those who are liberated, who survive, who escape, who are wounded and rise again to tell of their experience with our websites, our marketing material, our leave-behinds and downloads — want to tell us their stories.

The current method of analysis — body counts and debriefing — is good at telling us what happened. It’s not good at telling us what could have happened and why it didn’t. In a field where the difference between 1% and 1.1% is the difference between closing the doors and being profitable, knowing the “could have”‘s and “why”‘s is as important if not more important than knowing what happened.

Making these types of prediction markets work requires sophisticated software, time and a willingness of lots of people to participate. The market needs to be defined, set up, advertised, a reasonable reward needs to be established and participants need to be solicited and selected. Once you have the participants you need to ask them questions then do some clever mathematics to normalize the results. Think of a focus group, albeit a very large one (prediction markets using this method vary in size from 1,500 to 31,000 active participants), and you begin to get the idea. Also, make the focus group a broad demographic. Everyone in your group should have some familiarity with the subject matter but beyond that anybody’s opinion is game. Prediction markets differ from the traditional focus group concept because people taking part in traditional focus groups know that they are being evaluated and that they’ll be rewarded for their time regardless of outcome, according to Rivier Business Professor Eric Drouart, Former VP of International Operations for Bristol-Myers Squibb. This prediction market method is more like the real world than a focus group in the sense that participants are rewarded when the markets become profitable.

Another prediction market methodology completely bypasses the problems inherent in focus groups, time, set up and development costs, active participation and rewards. This methodology makes use of some clever mathematics but not to normalize the polling process and results. This method makes use of mathematical tools called concept manifolds and solid probabilities to create virtual (or “synthetic”) cultures. A simple way to think of how synthetic cultures work is this; if you count up the little opinions of everybody in a group, you start to see a ‘group’ opinion emerging on the big things. Synthetic cultures are like personae on steroids. Traditional personae are useful and limiting — you can create a target profile but, unless your entire market matches that one target profile, you have to creating different personae for everyone in your market segment.

Synthetic cultures allow you to create a group personae or cultural identity that matches entire demographics. Instead of a single persona, Pat (a mid-30’s accountant transplant from the mid-West to Boston interested in good wines and personal fitness, no kids but in a good relationship) you get Pat, all of Pat’s friends, co-workers, people who shop at the same stores Pat shops at, have the same upbringing but go into different professions, and so on. Research In Motion has the synthetic cultures to establish itself in new markets, and Forrester Research’s Shar VanBoskirk used synthetic culture concepts in her 8 Nov 05 NEDMA presentation, Integrated Marketing Grows Up.

Prediction markets using synthetic cultures generate their predictions via a sophisticated knowledge of an audience’s beliefs and culture (it’s socio-anthropology). An added advantage of synthetic cultures is that they don’t require the markets to exist, virtually or otherwise. Synthetic cultures predict not only the outcomes of synthetic markets (“Will there be more police dramas on this Fall’s TV schedule?”); they predict the a target audience’s responses to changes in a market (“Will people be willing to watch more police dramas this Fall than are willing to watch them now?”). Synthetic culture prediction markets answer more than whether something will or won’t happen. They venture into the realm of whether or not what happens will make a difference.

The power of either prediction market method comes from the diversity of their participants, and they’ve accurately predicted election outcomes [[(as documented in Reading Virtual Minds Volume 1: Science and History and“Predicting Election Outcomes via NextStage’s TargetTrack” or “Why Dean Led, Kerry was Droll and Lieberman Foundered in 2004”]] and top economic performers among other things.

Learning if Yellow Cars Will Sell

Let’s do a little exercise to give you an idea of how the BMech and PA aspects of prediction markets gain their predictive power, and how knowing the opinions on little things determines the opinions on big things. Let’s start by asking ten people the question, “How would you rate the color yellow; good, bad or indifferent?” We find out that five people like yellow, three don’t like it and two people have no opinion. That equates to 50% good, 30% bad and 20% indifferent.

Now ask a second question, “What do you think of this car, good, bad, indifferent?” The results with the same ten people are 20% good, 40% bad and 40% indifferent. Ask these two questions with a sufficiently large group of people and you never have to ask them “What would you think of this car if it was yellow?” because their likely answer will be the average of their previous two answers; 35% will like the car if it’s yellow, 35% won’t like it and 30% won’t care. Now share this result with a car manufacturer who commissioned this prediction market and they’re decision is

  • not to produce that car in yellow for the mass market because 65% of the market either won’t like it or won’t be interested,
  • but to market it aggressively to the 35% demographic which will respond favorably.

Wherein Lies the Power

The key to prediction markets’ power is nothing new. Whether you’re working with synthetic markets or synthetic cultures, you have to know

  • how to ask questions,
  • how to codify the answers and
  • how to find the best people to ask.

The caveat to all three of these is that you have to remove all bias from the questions, codification of the answers and from choosing people to answer the questions. That’s not easy to do.

One of the methods NextStage uses to remove bias is to go where people go and simply ask questions. See if you can match the following products to the venues where different synthetic cultures got their start:

1) Cellphone/PDA
2) MPEG/WAV Player
3) Cigars
4) Notebook Computer
5) Branded Website
6) Undergraduate College
7) Airline Frequent Flyer Program
8) Brick&Mortar Bookseller
9) Theatrical Movie

a) Airport
b) Fastfood Restaurant
c) Grocery Store
d) Gym
e) Hotel
f) Mall
g) Subway
h) Upscale Restaurant
i) Walking the Dog

Answers: 1(a,b,c,e,i)

If you looked at the correct answers and were surprised at how many different venues are used for traditional market testing, think back to removing biases. A cross section is best when it crosses several sections, not just one or two.

One of the tricks to making synthetic cultures work is to ask people to convince you, not ask them to let you convince them. For example, a test to determine if a particular PDA is going to be successful might start out by walking up to people with a PDA and politely saying, “Excuse me, I notice you have a such-and-such and I’m thinking about getting one. Would you recommend yours?” Two or three innocuous, curious and well structured questions later you have two books worth of data. Do that ten times, match the results to the socio-anthropologic norms of your target demographic and you have all the data you need to determine the entire demographic’s response to a given campaign, product or service.

Removing bias in questions means crafting two sets of questions. The first set of questions can be answered by “Yes”, “No” and “Maybe”. The second set of questions are numerical and grow out of the first. For example, the first question is “Do you like the color yellow?” The person answers, “Yes”. Now ask a second set question, “If you had to put a number, 1-100, on that, do you like the color yellow at 100? At 75? At 12?” These two questions together are a person’s soft and the hard experience, or what psycholinguists and semioticists call qualia. Essentially, the two questions combine to ask “How much of a ‘yes’ is that ‘yes’?” Someone’s 60% of “Yes” doesn’t mean there’s 40% of “No”, it means there’s 40% of “not quite ‘yes’ enough” or “not ‘yes’ enough to be 100%”. A slight variation is to replace the 1-100 scale with a time-based scale. The first question might be “Do you like this book?” and the second question might be “Would you read something else from the same author in a week? In a month? In a …?” Synthetic culture prediction markets used this way separate consumers’ intent from their wishful thinking.

Getting in the Game

NextStage’s prediction markets tools take two forms. The first form is NextStage’s award winning TargetTrack™ product. Unlike other prediction markets products, NextStage’s TargetTrack™ utilizes the combined experiences of over 25,000 individuals to determine how well material, products, candidates and businesses will fare in current and future situations, and in many cases results are available in less than 30 seconds. Marketers, advertisers, economists and politicians can determine how slight changes in product placement, design, statements or agendas will affect a very large population or a very small one — say all Americans versus all Hispanic-Americans or Asian-Americans, or all men versus all women — in a matter of moments and refine their messages to optimize the outcome of any or all markets they’re interested in.

The second form of NextStage’s prediction markets tools is embedded in its Intelligent Analytics™ products. Unlike traditional web analytics which provide body-counts, NextStage’s Intelligent Analytics™ determines both the “common thread” or consensus and the “usual story” or average response. The average response is the end product of traditional survey and focus group studies, the consensus response is the end product of prediction markets. Companies using NextStage’s Intelligent Analytics™ to monitor their website activity learn more than just how many people were on what page. They also learn what visitors really think about the site’s navigation, layout, content, and more.

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