Welcome to mthink.com: marketing, mobile and more

Welcome to mthink.com, the new center for marketing thought-leadership. We have exciting plans for the future, bringing together several independent initiatives under one roof.

In the immediate future we will be seeing Social Media – The Marketing Summit taking shape before launching on October 1st and 2nd, 2008, and it will be followed by new initiatives focusing on social media, social networks, enterprise software, interactive marketing, CRM, mobile marketing and metrics.

Once again, welcome. We hope to see you here often.

Understanding Technology Evolution: The Fallacy Of The S-Curve

Understanding technological innovation is vital for marketers for several reasons. First, technological change is perhaps the most powerful engine of growth. It fuels the emergence of new brands, creates new markets and transforms small outsiders into market leaders.[1]

To date, the topic of technological evolution has been studied primarily in the technology management literature. A central premise of these studies is that performance of a new technology starts below that of an existing technology, crosses the performance of the older technology once and ends up at a higher plateau, tracing a single S-shaped curve (see Figure 1). There is scattered empirical support for the premise and limited theoretical support for various aspects of the S-shape curve.[2]

Nevertheless, belief in this premise is so strong it has become a law in the strategy literature. Numerous authors have derived strong managerial implications about this premise.[3] They have warned that even though managers might be able to squeeze out improvements in performance from a mature technology, the improvement is typically costly, short-lived and small. Thus, the primary recommendation is that managers quit a maturing technology and embrace a new one to stay competitive.

However, firms cannot gain from technological change if they do not understand it well. A central practical problem that faces managers is deciding when to shift investments from the old to the new technology. If the S-curve is indeed valid, then the appropriate time for the shift would be the inflection point of the S-curve. After this point, performance improves at a decreasing rate until maturity. New product development and major investments in research depend upon a proper understanding of technological evolution in general and of the S-shaped curve in particular. It is also important to know the dimensions of competition between technologies, the process of transition between old and new, and the source of innovations.

Currently the main sources of answers to all these questions are limited findings in technology management literature. [4] These sources promote a theory commonly known as the theory of S-curve. Our study tests this commonly accepted model of technological evolution.

PREVAILING THEORY

The technology literature has coalesced around two aspects of the evolution-of-technologies theory: a strong consensus has developed about the phenomenon of the S-curve itself, while a consensus is emerging about the major explanation or theory for this phenomenon. As stated, prior research suggests that technologies evolve through an initial period of slow growth, followed by one of fast growth culminating in a plateau. When plotted against time, the performance resembles an S-curve.

The technology management field does not enjoy a single, strong and unified theory of technological evolution. However, researchers theorize that technology evolves through three major stages of the S-curve of technological evolution: introduction, growth and maturity.

Introduction Stage

A new technological platform initially makes slow progress in performance during this early phase of its product life cycle. Two reasons may account for this situation. First, the technology is not well-known and may not attract the attention of researchers. Second, certain basic but important bottlenecks need to be overcome before any new technological platform can be translated into practical and meaningful improvements in product performance. For example, the laser beam was a new platform that required much time and effort to achieve the safety and miniaturization required for a surgical tool.

Growth Stage

With continued research, the new technological platform crosses a threshold, after which it makes rapid progress. Three factors may account for this change: a dominant standard has emerged; product characteristics and consumer preferences coalesce around the new standard, and a larger number of researchers are attracted by the publicity of the standardization; and an increase in sales of products translates into greater support for research.[5]

Maturity Stage

After a period of rapid improvement in performance, research suggests that the new technology reaches a period of maturity when progress occurs very slowly or reaches a ceiling for various reasons: innate characteristics of a technology, changing focus of innovation as markets saturate, fears of obsolescence or cannibalization, and limits of scale or system complexity.[6]

DEFINITIONS

The theory in this area has been partly confounded by the use of circular definitions. So this section starts by defining various types of technological innovations independently of their effects.

Beginning with an early study researchers have used a wide variety of terms to describe innovations. Many terms such as revolutionary, disruptive, discontinuous or breakthrough are intrinsically problematic, because they define an innovation in terms of its effects rather than its attributes.[7][8] If the definitions are then used to predict market outcomes (new entrants displacing incumbents with disruptive technologies, for example), researchers run the risk of asserting premises that are true by definition. To avoid such circularity, we define technological change in terms of intrinsic characteristics of the technology. As such, we identify and define three types of technological change: platform, component and design.

We define a platform innovation as the emergence of an entirely new technology based on scientific principles distinctly different from those of the existing technologies. For example, the compact disk used a new platform (laser optics) to write and read data, whereas the prior technology used magnetism.

We define a component innovation as one that uses new parts or materials within the same technological platform. For example, magnetic tape, floppy disk and zip disk differ by use of components or materials, although all are based on the platform of magnetic recording.

We define a design innovation as a reconfiguration of the linkages and layout of components within the same technological platform – for example, the changes in floppy disks from 14 inches to 8 inches and then to 5.25, 3.5 and finally 2.5 inches, although all based on the platform of magnetic recording.[9]

Our study focused on the evolution of technologies. Within any platform innovation, performance improves due to innovations either in components or design or both.

METHOD

A ready-made database does not exist for the study of technological evolution. So we collected our own data using the historical method. The benefits of using an historical method include freedom from survival and self-report bias, ability to assess causality through longitudinal analysis and new insights from a fresh look at history.

We selected a portfolio of categories including some that had been investigated in past studies and others that had not been researched. This coverage allows us to compare our results with past studies and offer validation of our findings in new categories. However, the present study goes further than previous studies in one important aspect: within each category we selected a comprehensive set of technologies – and not only those that were successful. On the basis of these investigative criteria, we chose to examine data transfer, computer memory, desktop printers and display monitors.

The primary sources of data on product performance at different stages of its evolution were reports in technical journals, white papers and annual reports of industry associations, press releases and records in museums that profiled the development of industries.

RESULTS

We tested hypotheses about five aspects of technological evolution: shape, path and dynamics of technological change on a primary dimension; progress on secondary dimensions; source of innovations; and pace of technological change.

Shape of Technological Progress

We identified various technologies in each of the markets, each of which was initiated by a platform innovation, and plotted performance of technologies over time: four each in desktop printing (dot matrix, ink jet, laser and thermal printers) and display monitors (CRT, LCD, plasma and OLED) and three each in desktop memory (magnetic, optical and magneto-optical) and data transfer (copper-aluminum, fiber optics and wireless).

We found sparse support for the hypothesis that the path of technological evolution resembles an S-curve. In a majority of technologies, we found long periods of static performance interspersed with abrupt improvements in performance. These plots suggest a series of irregular step functions better approximated with multiple S-curves than a single S-curve. Across these step functions within a given technology, estimates of growth rate – especially performance at maturity – differ substantially.

What we learn from these results is that an analyst expecting an S-shape curve would wrongly conclude that the periods of static performance meet the S-curve hypothesis and that the technology has matured at the upper end of the curve. Substantial improvements in performance after the first plateau suggest a serious error in abandoning the old technology prematurely.

Technological Transition and Performance of Competing Technologies

Do the evolutionary paths of two technologies ever cross? If they do, how many times does it happen? Foster and Christensen postulate the following chain of events in the evolution of competing technologies.

Sometime in the life of an old technology a new technology emerges and makes slow progress on the primary dimension. Later it enters its growth phase and improves rapidly. In contrast, the old technology improves at a much slower rate. As a result, the new technology crosses the old technology in performance. This crossing of the old technology is a signal of the end of its efficient progress (see Figure 1).

On the contrary, we find that a majority of new technologies performed better than the old technology, right from the time they were introduced. Also, many new technologies never improved over the old technology, while others enjoyed brief spells of dominance over the old technology before the old technology regained dominance.

This unexpected pattern of evolution results in three distinct types of crossings between any pair of successive technologies: no crossing at all, multiple crossings and single crossing.

So the final status of each technology cannot be determined solely from the direction of the attack or timing of introduction. As such, it might be fatal for an incumbent to scan for competition only among technologies performing worse than its current technology. Moreover, managers expecting a single crossing are likely to be quite surprised and may make unwise decisions.

Dimensions of Technological Competition

Past research suggests that competition occurs systematically and sequentially along generic dimensions of inter-technological competition: functionality, reliability, convenience and cost. Progress occurs systematically along the first dimension, then moves to the second, then to the third and so on.

On the contrary, our results suggest a sequence of random, unpredictable secondary dimensions in each of the four categories. Each platform technology offered a completely new secondary dimension of competition while still competing on the primary dimension (for example, resolution, compactness, screen size and efficacy in desktop monitors).

We also found that technologies that excel in a particular dimension cater to particular market segments that value that dimension. When the mass market focuses on one old or new dimension, niches that are interested in the other dimensions might still survive. For example, thermal printers are still a popular choice in printing high-resolution pictures.

In summary, we find that although new technologies perform better than old technologies on secondary dimensions, competition evolves in new, unpredictable secondary dimensions instead of the standard four generic dimensions proposed by existing literature.

Pace of Technological Transition

There is evidence of both increasing pace and constant pace of technological change in prior literature. However, most of the studies employ indirect measures due to lack of data. Our rich data allows using three direct measures of the rate of technological change: the pace of introduction of new technologies, the pace of technological improvements within each platform and the annual rate of improvement for each technology. Tests of all three measures support an increasing pace of technological change.

Source of New Technologies

Among those who track technological innovation, the conventional wisdom is that the small outsider is more likely to introduce new technologies. Although these small firms are often ridiculed and ignored by incumbents in the beginning, they eventually become successful and end up as large incumbents with more opportunity and resources for innovations.

In contrast to the dominant view in the literature, we find that platform innovations come almost equally from small entrants and large incumbents. The probable reason is that in recent decades, innovation has gotten far more complex. The deeper pockets of large firms enable incumbents to maintain state-of-the-art facilities to conduct research, while incumbency provides them with opportunity and resources for developing and introducing platform innovations.

IMPLICATIONS

This study has several implications for managers:

Using the S-curve to predict the performance of a technology is quite risky and may be misleading for two reasons: most technologies studied do not even demonstrate an S-shape performance curve, and several technologies show multiple S-curves, suggesting that a technology can demonstrate fresh growth after a period of slow or no improvement.
The continuous emergence of new technologies and the steady growth of most technologies suggest that relying on the status quo is deadly for any firm. Moreover, technological progress is occurring at an ever-increasing pace. As such, paranoia rather than complacency is healthy.
The present findings indicate that the attack from below remains a viable threat. Many new technologies start by offering low performance but later threaten old technologies by improving at a much faster rate. On the other hand, new technologies can perform better than old technologies even at the time of introduction. This fact heightens the threat of competition.
Another threat to incumbents is the emergence of secondary dimensions of competition. Old technologies may be completely vulnerable to these dimensions.
First-mover advantages may not be lasting since entrants introduced even more innovations than incumbent firms. However, even if incumbents fail to introduce a particular new technology, all is not lost. They need not throw in the towel and divert all resources to the new technology. We found that old technologies demonstrated high levels of improvement even after being dormant and static for many decades, and in some cases regained dominance. In contrast, a misplaced belief in the theory of S-curves might have become a self-fulfilling prophecy and the premature demise of an old technology.

ENDNOTES

Richard Foster, Innovation: The Attacker’s Advantage, New York: Summit Books, 1986; Clayton M. Christensen, The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Boston: Harvard Business School Press, 1997; Rajesh K. Chandy and Gerard J. Tellis, “Organizing for Radical Product Innovation: The Overlooked Role of Willingness to Cannibalize,” Journal of Marketing Research 35, no 4. (1998): 474-87.
Foster, 1986; James M. Utterback, Mastering the Dynamics of Innovation, Boston: Harvard Business School Press, 1994; Christensen, 1997.
Foster, 1986; Christensen, 1997.
Utterback, Dynamics of Innovation.
James M. Utterback, “Innovation and the Diffusion of Technology,” Science 183, no. 4125 (1974): 620-26; Utterback, Dynamics of Innovation; James M. Utterback, “Radical Innovation and Corporate Regeneration,” Research Technology Management 37, no. 4 (1994): 10.
Foster, 1986; Rick Brown, “Managing the ‘S’ Curves of Innovation,” Journal of Consumer Marketing 9, no. 1 (1992): 61-73; Utterback, “Radical Innovation”; Chandy and Tellis, 1998.
Joseph A. Schumpeter, Business Cycles: A Theoretical, Historical and Statistical Analysis of the Capitalist Process, New York: McGraw-Hill, 1939.
Christopher Freeman, The Economics of Industrial Innovation, 2d ed., London: Frances Pinter, 1982; Michael L. Tushman and Philip Anderson, “Technological Discontinuities and Organizational Environments,” Administrative Science Quarterly 31, no. 3 (1986), 439-65; Rosanna Garcia and Roger Calantone, “A Critical Look at Technological Innovation Typology and Innovativeness Terminology: A Literature Review,” Journal of Product Innovation Management 19, no. 2 (2002): 10-32.
Clayton M. Christensen, “The Rigid Disk-Drive Industry – A History of Commercial and Technological Turbulence,” Business History Review 67, no. 4 (1993), 531-88.

A Manifesto for Integrating Social Media Into Marketing

You’re capturing recency, frequency and monetary data about your customers. You’re recording customer service contacts. You’re doing your best to capture point-of-sale information and correlate it with direct mail and telemarketing touch-point data.You’re trying to integrate your salesforce automation systems to keep everybody up to speed on customer contacts and customer desires.

Then along comes the World WideWeb, bringing with it something called Web analytics.

Web analytics is the art and science of tracking what individuals actually do on your website and how they respond to different stimuli (advertising, marketing and customer service). Web analytics allows you to get more granular in your knowledge of each customer. You are moving from the age of demographics,through the age of segmentation and into the age of behavioral analysis. The effect on the bottom line and on customer satisfaction is significant.

At the start, Web analytics consisted of log-file analysis: sifting through log files that Web servers created as a matter of course (see sidebar). These were never meant to be a business tool, just a transactional record of every file sent out to 0.

Marketing departments around the world have grown in intelligence in the past few years. They’ve started using Web analytics to measure advertising and marketing, rather than just sales results.The persuasion process has been instrumented and diagnosed. Small changes were made to see how they impacted a prospect’s ability to get from awareness, to interest, to intent and, finally, to purchase.

We’ve long played with shopping-cart analysis to upsell and cross-sell, but today’s eye-in-the-sky, over-the-shoulder surveillance gives you an edge you didn’t have before: the ability to classify your customers based on their behavior.

CUSTOMER SEGMENTATION

Sign up for a newsletter at any maternity or baby-focused website, and you’ll be asked when the baby is due or how old your infant is. The needs of a pregnant woman or a new mother change almost weekly. This industry knows that every woman will go through the same stages, so segmenting those women by month is simple.

It’s a bit more complex to segment your customers when they are buying wrenches. But Snap-on, Inc., purveyor of high-end automotive repair paraphernalia,knows it can be done. Sending the same sales rep to talk to the same automotive service technicians month after month made it clear that these customers move through an occupational arc, choosing their specialties along the way. Each specialty requires different mechanical and electronic implements to help them get the job done.

Detailed information on tools and their applications in the Snap-on online catalog coupled with online training turn those sales reps in the field into career counselors. By recommending an educational path to a technician and following his progress through the courses, a unique bond is formed. CRM? Sure, if you help your customers advance their skills and track their progress, you’re ready to fulfill their needs as those needs arise.

THE TECHNICAL EXPLANATION

The CMO heads over to the CIO and says, “Tell me what’s happening on my website.”

CIO: “What do you want to know?”
CMO: “Well, what have you got?”
CIO: “Well, what do you need?!”
CMO: “Whatever you can tell me!”

In an attempt to halt this circular madness, we start with “What have you got?” and then move on to “How do we extract insights from that data?” There are a variety of ways to collect data about what people are doing on a website. Here they are in the briefest terms possible:

Performance Monitors
Is your server serving quickly? Is it overloaded? Are your e-commerce applications running smoothly? Is your server sending out “404, File Not Found” messages? Performance monitors watch the technical side of things and give you a holler if something goes bump in the site.

Server Logs
Every Web server makes a log entry of every page it sends out. By using log file analysis tools, you can glean such interesting things as number of visits and page views, entry and exit pages, hourly usage, browser and operating system used, and usage by country. All of which come with the caveat: sort of. Each of these measurements has some inherent irregularity, so take them all with a good-sized grain of salt.

Referring Data
If the visitor comes to your site via a link on another page, your Web server will also record the URL of that previous page. This is enormously informative if you’re buying banner ad space or tracking the success of a pay-per-click campaign. Did banner ad A outperform B? Did the press release cause a stir? Are people finding you while searching for a word you didn’t expect? Interesting stuff.

Tagged URLs
Server logs have trouble confidently revealing what an individual did during a single visit, so tagged URLs were designed for session or clickpath analysis. When a home page is served, all of the links on the page are tagged with a sequential ID number. A link that normally looks like this: www.company. com/page2.html, is tagged by the server on the way out the door to look like this: www.company.com/page2.html?127, indicating that I’m the 127th person to visit today. When I click on that link, the server records that page2.html was requested by visitor number 127 and tags the links on the requested page with 127 as well.

Cookies
Server logs can rarely recognize individuals from one day to the next, so someone came up with cookies. For our purposes, it’s enough to know that you can track an individual over time using a cookie, and you can correlate his traffic patterns with any personal information he may have divulged while on your site.

Packet Sniffing
Information moves online from here to there inside small data packets. Your home page is divided into capsules of about 1,000 bytes of data, and off they go, finding their way to your visitor’s screen. Should the visitor type something into a form and hit the Submit button, the entered data gets packetized and sent back to you. By sniffing the packet on the way back, you not only know which Submit button this person clicked (top of the page, middle or bottom) but you also capture the entered data. Now you have a record of the click as well as the information that would normally go straight into an application database and require a good deal of extract, transfer and load effort to match up with the server activity information.

Web Beacon (cleardot.gif)
Web pages are often stored in temporary cache files on the visitor’s computer and in cache farms of ISPs to minimize the time it takes to go back to a previously viewed page. This minimizes the overall traffic on the Internet and improves the customer experience on your site. It also means that your server doesn’t always know when a page is viewed. Embedding a transparent, 1-pixel-by-1-pixel image designated as “no-cache” can help identify when each page is viewed. If such a graphic is served from a third-party server, the aggregate information about cross-server and cross-site traffic can be useful.

Page Tagging
This works similarly to the Web beacon but takes the form of executable JavaScript code. It calls out to the server to make known that this page has been displayed again but can contain all sorts of information collected along the site path the individual has taken. It might contain laptop confi guration information, ZIP code data if the visitor has searched for a local store or even check-in and check-out dates if she researched hotel room availability.

Client-Side Surveillance
A small Java program watches every move you make. Every mouseover. Every keystroke. This method can collect the most complete picture of what an individual does on your site. The data can be used to play back a visit and can capture data entered into a form even if the form is not completed or the Clear button is used. Very powerful, somewhat spooky. Full disclosure and full opt-in are highly recommended.

Panel Observation
If you’d like to look over peoples’ shoulders and ask them personal questions at the same time, the panel research method is the way to go. Each panelist agrees to have client-side surveillance software on his computer and is willing to respond to the occasional pop-up asking them why he made certain click choices or how he feels about the color of the site’s background, etc. You can also learn how he feels about the competition.

Eye Tracking
If you want to get up close and personal, there are a number of firms measuring what individuals actually look at on individual pages of your site. You’d be surprised at what people simply do not see online.

Gross Traffic Patterns
A handful of companies are learning what people do online by watching from the vantage point of the ISP. Millions of people looking at millions of sites per day reveals which sites are the most popular. For the price of admission, you can learn where people (in general) were before they came to your site and where they went afterward.

All of the above explains why the CIO is so quick to respond with, “What do you need?” There is so much data available (granted, some of it is rather expensive to gather), that you must stop asking for anything and figure out what you want in particular.

WHAT THEY DO INSTEAD OF WHO THEY ARE

Overstock.com is a closeout retailer offering discount, brand-name liquidation merchandise to the tune of a couple of hundred million dollars per year. CEO Patrick Byrne is a big proponent of clustering. He wants to know which of his customers are the same and how they differ. But he’s not a fan of demographics.

“When you add up everything you know about your online customers, you can get rid of education, income, children and the rest of the demographics,” Byrne said at the Web Analytics Summit of the eTail 2004 conference. “Demographics are foggy data. You can only guess and surmise why people who live in the same postal code might or might not shop the same way, want the same stuff or be willing to pay the same price.

“But behavioral data is sharp,” Byrne continued. “Customers’ behavior is a signpost to their needs, so we don’t cluster people based on who they are or what car they drive but by their needs as expressed through their behavior.”

How an individual uses a retail site provides more insight into how he or she might be persuaded to buy than does martial status, age or income. “Men on a diabetes website will click on an electronics ad seven times more often than the same ad on all other sites. Why? You’ll never know – you can only surmise. And it doesn’t matter! Just take note and make use of that knowledge.”

Byrne offered another example: If somebody buys electronics on their first trip to the site, they always buy electronics during the second visit. If a first-time buyer does not buy again within 45 days of the first purchase, they are lost forever.So what can you do with that information?Make sure the electronics buyer isn’t given too much of a discount on his next visit and send a special offer on the 44th day if he doesn’t come back at all.

CRM From the Other End of the Telescope

Web analytics gives us yet another window through which to view the customer.But Dianne Binford, director of consumer direct marketing at Nine West, wants to turn CRM on its head. “A 360-degree view of the customer is all well and good. But we also need to give the customer a 360-degree view of the brand,” Binford said,also at the eTail 2004 conference.

Integrated marketing means ensuring that the direct mail piece, the television ad, the in-store displays and the website all look alike. Binford is adamant that customers see a united front when they look at Nine West, no matter what angle, no matter what method and no matter what medium.

When you combine Overstock’s behavioral clustering, Snap-on’s hands-on approach to customer care and NineWest’s desire to integrate its countenance,you move into the realm of microbranding.

Microbranding is the art of determining what type of company an individual customer is most likely to respond well to and presenting that face to that customer.Every time that customer sees the brand,in whatever channel, it looks cohesive and familiar and is tailored to them at that point in time.

Amazon was first to offer books based on collaborative filtering. If you and 500other people like the same 10 books,then the chances are pretty good that you’ll like additional books those other 500 like.

We have reached the end of the practical road when it comes to data capture.You can now collect more data about an individual during a single website visit than you can realistically use.

Web analytics systems have become sophisticated enough to track every mouse movement, every click and every keystroke. Rather than merely recording which links customers click,you can now see which links they considered clicking when they hovered over them with their mouse. You can see how long it takes them to absorb a page.You can tell when their hand leaves the mouse – a sure sign that they took a Websurfing break.

For purposes of measuring the effectiveness of an individual page, this is an absolute gold mine. Every mouse twitch and every nuance of a customer’s visit to your website can be trapped and played back. But for the purposes of building a profile of who she is and what her needs might be, there is simply too much data.You need a balance between what you can record and what you can use.

Let The Computer Decide

One approach to this info glut is to put the power of the computer to work on the problem.

Let’s say you bid on a keyword or create a banner ad. People who click can be directed to one of several landing pages. You can then track which page is convincing more people to buy. Better,however, is to implement a system that creates multiple permutations to see which landing element combination (headline,body copy, photo, call to action) has the most positive impact.

Several vendors are offering optimization systems to create a testing matrix. For example, well-known provider Optimost says it can “generate up to 1 million permutations of the creative execution. Through sophisticated experimental design techniques, Optimost will then test certain combinations of variables to arrive at the optimal values along each parameter.”

In other words, it’s the computer’s job to figure out which variables matter, which variable values are improvements and which variables barely move the needle.The more people touching down on your landing page, the faster the system will show which combination of text, graphics and layouts is getting the most people to do what you want them to do.

A Web analytics system can chronicle how the majority of people are attracted to a website and feed results back to an advertising system so that only the most attractive promotions are reproduced. It’s Darwinism at the speed of light.

All The Way to Loyalty

More sophisticated systems can track how the majority of people are attracted o a website, how they wander through its pages and how they do or do not buy.This type of system can watch which promotions result in the most profitable sales. It can feed results back to an advertising system so that only the most profitable promotions are repeated. It can feed results back to the website design team for insights on how to improve navigation.It can help online merchandisers determine which website elements might have the largest positive impact on conversion rates.

It takes one more step, however, to turn this marketing machine into a customer relationship management engine.This near-perfect system needs to have a longer-term view of the outcome.Instead of being programmed to reproduce the promotions, navigation and merchandising with the most profitable sales, it would detect which generate the most profitable customers. It needs to look all the way downstream to lifetime value.There are some companies working on these solutions, but they aren’t quite ready for prime time.

Your customers are coming to your website for information, transactions and to get help. Are you making the most of the information they leave behind?

Gleaning Meaning – Asking the Next Question

You know the standard questions to ask: Why did we get a spike in traffic to this section of the site for a solid week? Why are people who click through from search engines dropping out on page three of a five-page process? How much impact can we have if we tweak this page? Where does our advertising spend start to experience diminishing returns? If I shorten the copy on a page by 20 percent, does that increase customer satisfaction? Do they buy more? How much less clutter can I publish and still make sales? What changes in process completion should have alarms and what should the threshold be?

There is no Web analytics magic here. The standard questions are good ones and they help with incremental, continuous improvement. That’s all well and good. But the best question is the next question. It’s all about intuition, correlation and curiosity.

A large retailer in the U.S. found only a small percentage of its site visitors were Macintosh users. It seemed silly to devote the necessary resources to redevelop the website for the express use of a group that made up less than 10 percent of visitors. As the discussion progressed about ceasing dual development to accommodate this small group, one of the technologists asked the next question: What percentage of Mac users are buyers and how does that compare to Windows users?

The answer was surprising. While Windows visitors exhibited a conversion rate around 2 percent, Mac users’ ratio was up around 20 percent. That represented a healthy chunk of overall revenue. The next question had been asked, and the dual development continued.

The popular British online betting company William Hill noticed that only a small percentage of site visitors were viewing special, additional content. This content was expensive to create and maintain and was on the chopping block for the new website rollout. Then somebody asked the next question: Was there something special about those visitors who did view the special content?

Yes, there was. They were responsible for an unusually high percentage of site revenue. They placed more and larger bets. Rather that trash the content, William Hill Emailed the rest of its customers to tell them about the value of that content. The result was increased revenue, higher customer satisfaction and no measurable increase in costs.

A Web analytics tool does not provide a wealth of answers. Instead, it is an unending source of questions. Every good analyst uses the tools to sift through the data, searching for patterns and asking the next question.

So what’s the next question for your website?

Stay curious.

Web Analytics: The Non-Scary, Non-Techie Version

You’re capturing recency, frequency and monetary data about your customers. You’re recording customer service contacts. You’re doing your best to capture point-of-sale information and correlate it with direct mail and telemarketing touch-point data. You’re trying to integrate your salesforce automation systems to keep everybody up to speed on customer contacts and customer desires.

Then along comes the World Wide Web, bringing with it something called Web analytics.

Web analytics is the art and science of tracking what individuals actually do on your website and how they respond to different stimuli (advertising, marketing and customer service). Web analytics allows you to get more granular in your knowledge of each customer. You are moving from the age of demographics, through the age of segmentation and into the age of behavioral analysis. The effect on the bottom line and on customer satisfaction is significant.

Marketing departments around the world have grown in intelligence in the past few years. They’ve started using Web analytics to measure advertising and marketing, rather than just sales results. The persuasion process has been instrumented and diagnosed. Small changes were made to see how they impacted a prospect’s ability to get from awareness, to interest, to intent and, finally, to purchase.

CUSTOMER SEGMENTATION

It’s a bit more complex to segment your customers when they are buying wrenches. But Snap-on, Inc., purveyor of high-end automotive repair paraphernalia, knows it can be done. Sending the same sales rep to talk to the same automotive service technicians month after month made it clear that these customers move through an occupational arc, choosing their specialties along the way. Each specialty requires different mechanical and electronic implements to help them get the job done.

THE TECHNICAL EXPLANATION

The CMO heads over to the CIO and says, “Tell me what’s happening on my website.”

CIO: “What do you want to know?”
CMO: “Well, what have you got?”
CIO: “Well, what do you need?!”
CMO: “Whatever you can tell me!”

Tagged URLs
Server logs have trouble confidently revealing what an individual did during a single visit, so tagged URLs were designed for session or clickpath analysis. When a home page is served, all of the links on the page are tagged with a sequential ID number. A link that normally looks like this: www.company.com/page2.html, is tagged by the server on the way out the door to look like this: www.company.com/page2.html?127, indicating that I’m the 127th person to visit today. When I click on that link, the server records that page2.html was requested by visitor number 127 and tags the links on the requested page with 127 as well.

WHAT THEY DO INSTEAD OF WHO THEY ARE

CRM From the Other End of the Telescope

When you combine Overstock’s behavioral clustering, Snap-on’s hands-on approach to customer care and NineWest’s desire to integrate its countenance,you move into the realm of microbranding.

We have reached the end of the practical road when it comes to data capture.You can now collect more data about an individual during a single website visit than you can realistically use.

Let The Computer Decide

One approach to this info glut is to put the power of the computer to work on the problem.

All The Way to Loyalty

Your customers are coming to your website for information, transactions and to get help. Are you making the most of the information they leave behind?

Gleaning Meaning – Asking the Next Question

So what’s the next question for your website?

Stay curious.

RESEARCH METHODOLOGY

For this research, we analyzed click log data for 120,000 unique users occurring between Nov. 1, 2006, and May 1, 2007. The click data we analyzed originated from paid search advertisements purchased through Yahoo Search Marketing, Google AdWords and Microsoft AdCenter. A total of 275,858 paid search clicks were recorded for the set of users during this period. Thirty advertisers were included in the study, each advertiser accounting for 4,000 unique users.

In the discussion that follows, we use the term conversions to describe the primary measurable events advertisers use to gauge the effectiveness of their advertising campaigns. Examples of conversions advertisers might track include order completions, “contact us” form submissions and page views.

CATEGORIES OF NAVIGATIONAL SEARCH

In our analysis, we categorized each sponsored search click according to two behavioral dimensions.

Repeat-visit behavior. If a user clicked on multiple ads leading to a given advertiser’s website, we considered each instance after the first to be a repeat visit. We considered repeat visits to be navigational because they imply prior knowledge of the advertiser.

Branded keyword search. A click was assigned to this segment if the key phrase associated with the click included the advertiser’s brand name or explicitly matched the advertiser’s website URL. For example, if a user clicked through to the ACME Corp. website, the following key phrases would be categorized as branded:

acme.com
www.acme.com
acme corporation
acme corporation website

WHAT WE LEARNED

The charts that follow summarize our findings. Figure 1 shows the results for each segment as a percentage of total clicks. The percentages given are an average for all advertisers in the study, which means each advertiser had an equal contribution to the overall averages.

Looking at the data, we notice that nearly half (48.3 percent) of clicks were from users who had been to the advertiser’s site before. Well over half (59.6 percent) of clicks also came from branded key phrases. Only 29 percent of clicks were attributed to nonbranded first visits. This relatively small segment is often how search marketing is characterized – as a means of attracting and acquiring new customers.

To quantify the impact of navigational search on overall search budgets, we also looked at the media cost by segment (Figure 2). The 59.6 percent of clicks attributed to branded key phrases represented 34.2 percent of total cost. This shift is to be expected, given the relationship between click-through rate and bid price. Ads with higher click-through rates require lower bids to maintain top positions. Since branded key phrases are directly related to the advertisers’ brand or URL, higher click-through rates and lower cost per click (CPC) rates are expected for these ads.

THE IMPACT OF NAVIGATIONAL SEARCH ON CONVERSION ATTRIBUTION

Navigational search raises some concerns regarding how advertisers measure the performance of their campaigns. Current reporting standards attribute conversions to the last ad click or impression prior to the conversion event. Thus, virtually all campaign reports ignore the fact that consumers are being reached by multiple ads, on multiple sites and across many channels. Since navigational search behavior typically occurs in a user’s immediate path to conversion, navigational search ads often appear to be the source of high volumes of conversions. Put simply, navigational search behavior implies that the user already knows the advertiser. That prior knowledge may have come from a variety of other marketing touch points and interactions, and in many cases, from existing customers who are returning to the site to buy again.

To accurately measure performance, an advertiser should consider all ad exposures prior to a conversion. In support of this point, there is mounting evidence that crediting the last ad or click with the entire conversion is shortsighted. A recent study from the Atlas Institute found that two-thirds of converters were exposed to ads from multiple sites.[2] A separate study found that sponsored search clickers were 22 percent more likely to convert if they were exposed to display ads from the same advertiser.[3] If we take a holistic view of all tracked ad exposures, a conversion should not be attributed to the last ad clicked, but rather shared among all interactions that lead to a conversion. This means that advertisers currently have an inflated view of the value of navigational clicks, and are likely undervaluing non-navigational search clicks and other media types.

CONCLUSION: WHAT THIS MEANS FOR MARKETERS

Billions of dollars are being spent every year on navigational search clicks, and in all likelihood a significant portion of your search spend counts toward this number. The phenomenon of navigational search isn’t bad for search marketers. It is in fact an indication of the growing reach of search engines. But navigational search behavior should factor in to how you manage your search marketing campaigns. Below are a few tactics to consider when managing paid search.

Separate out your branded keywords when looking at clicks, cost and performance. This will help you understand how paid search is contributing to your overall advertising efforts. If branded keywords are driving a lot of sales, it’s likely that other marketing channels are generating interest in your brand. In addition, analyzing repeat-visit behavior will help you optimize your search campaigns. A high incidence of repeat visits is an indicator that a keyword is being used navigationally. This information can be useful in planning natural search optimization and could change how keyword performance is being valued.
Test what happens if branded key phrases are bid down or removed altogether. Several of the advertisers in this study were not bidding on any branded key phrases. In most cases, those advertisers ranked at the top of the natural listings for brand-related key phrases, which is often true for advertisers. A well-placed natural listing may be all the navigational searcher needs to click through and convert.
Consider all touch points that led to a conversion, not just the last ad. As discussed above, navigational search can mask the impact of other advertising media due to last-click attribution of conversions. To gain an accurate understanding of how different channels contribute to conversions, use one tracking mechanism to measure the performance of all ad types and look beyond the last ad when attributing value.

ENDNOTES

Danny Sullivan, “Browser-Based Searching,” The ClickZ Network. April 10, 2002. www.clickz.com/1006191
Jed Fowler, Analyst, The Atlas Institute, “The Impact of Overlap on Reach, Frequency &Conversions.” www.atlassolutions.com/uploadedFiles/Atlas/Atlas_ Institute/Published_Content/IODMI.pdf
Esco Strong, Sr. Analyst, The Atlas Institute, “The Combined Impact of Search and Display Advertising. www.atlassolutions.com/uploadedFiles/ Atlas/Atlas_Institute/Published_Content/ crosschanneldmi.pdf

B-to-B Online and Interactive Marketing: Cutting Through The Hype

Online advertising, social networking, search engine marketing, Internet broadcasting, wikis, Web 2.0… What do these terms mean for your B-to-B marketing strategy? How do you harness the power of these new channels and Internet strategies without derailing your current strategy? Who in your organization is responsible for this emerging area of marketing? How can you leverage your online and interactive marketing activities to improve marketing’s performance measurement strategy? The new and constantly changing digital marketplace represents great opportunity for your marketing organization and your company, and these are just a few of the questions that you should be asking yourself. However, many tech marketers are off to some operational false starts in this area.

Keeping on Course: 2008 Guidance for CMOs

You may expect that the first place to start reviewing this topic would be to describe the latest and greatest application available on the Web. However, to prevent losing focus on your overall marketing strategy and to keep the digital marketing hype in check, it’s important to begin with an understanding of your CMO’s overall priorities.

During 2008, many technology marketing leaders will maintain the focus from last year of improving their internal alignment, within marketing as well as within the organization as a whole. This includes improving alignment with field marketing, business unit marketing and sales and product management, as well as improving key processes such as lead management, marketing performance measurement, sales enablement and centralization/decentralization (see Figure 1). Only the more advanced organizations will be capable of turning their attention to include a greater focus on the needs of the market, better leverage online and interactive marketing, improve ROI of channel marketing and work internally to develop a single view of the customer to enable end-to-end marketing.

Online and interactive marketers should focus on three key efforts:

Think about tech marketing more from the “outside in.”
In the IT vendor community, the traditional marketing approach is becoming outdated. Tech marketers typically come into the marketplace with a trumpeting of products, features and benefits. The marketing mission is to climb to the highest point on the “noise pile” and plant the company flag – until that flag is supplanted by another. This is “inside-out” marketing: from “us” (the vendor) to “them” (the customer) in an asynchronous torrent of communications. This mind-set has deep roots in the traditional power centers of the tech vendor organization – sales and engineering – and in the traditional go-to-market process, where the marketing function serves primarily as the mouthpiece for those groups.

If the following statements sound familiar, your organization is likely more inside-out than outside-in:
- “We think a lot about messaging.”
- “We position ourselves.”
- “We ‘go to market’ (and just so they know we are serious, we use military jargon).”
- “We launch campaigns.”
- “We blast emails.”
- “We work in theaters of operation.”
- “We provide air cover for sales.”
- “We use a shotgun approach when we target our markets!”
This inside-out orientation will return less on the investment over time. Buyers indicate that they are less interested in the traditional messaging of product and feature attributes from vendors. Instead, they have a greater need to learn about the impact of new technologies on their existing business as a first step, followed by learning about products and how they can be leveraged within their existing environment. The other key shift is that vendors are no longer the main source of information. Since vendors have failed to provide a valuable learning environment, customers prefer to leverage relationships with independent third parties and interaction with other buyers. Marketers must take heed of this “voice of the customer” and design their company’s customer-creation process (i.e., marketing and sales) to better meet the full spectrum of customer needs. Online and interactive marketing provides a significant opportunity for differentiation in meeting these market needs.
Embrace online and interactive marketing.
IDC defines online and interactive marketing as follows:

The people, processes and marketing activities that are specifically designed to engage the market (including customers, prospects, partners and influencers) in an exchange of information with the marketer/ vendor by leveraging digital marketing. This includes the following types of marketing activities/technologies: websites, banner advertising, search engine marketing (SEM), Email, blogs, wikis, podcasts, webinars, online demos, RSS feeds, social networking communities, etc.

Tech marketers allocate about 9.6 percent of their marketing program’s budget (i.e., not including staff and IT infrastructure) to online and interactive marketing. Of this overall allocation, 17.2 percent is allocated to SEM, 29.1 percent to banner advertising/sponsorships, 27.8 percent to webcasts and podcasts, and 24.4 percent to Email marketing/ electronic outreach (see Figure 2). Growth in these areas is expected to significantly out-pace overall marketing investment by at least 2-to-1 in 2008. But marketers need to get ahead of the curve and address some potentially problematic operational issues related to online and interactive marketing.
Make further progress on end-to-end marketing.
Marketers tend to know their role at the beginning of the customer-creation process – to build awareness, expose new products and services and create initial demand. Marketers also tend to know their role toward the end of the customer-creation process – to provide sales support, resources and tools for revenue generation. It is in the middle of the customer-creation process that capabilities need to be improved.

For instance, one problem is that after a prospect’s record is created in a company’s lead management database, multiple records of that customer are subsequently created by different individuals in marketing and sales groups. This makes it difficult to “tag” the activities related to that prospect on an end-to-end basis. Many IT vendors recognize this problem and are in the process of consolidating customer databases, so that they can maintain a single view of the customer that includes general industry information, prior purchase history, and marketing and sales touch points. As this consolidation takes place, marketers have an opportunity to improve performance monitoring and measurement, lead qualification and nurturing processes, the quality of the sales pipeline, and eventual share of wallet and customer advocacy. And all of these areas should be inextricably linked to your online and interactive marketing strategy.

CORRECTING OPERATIONAL FALSE STARTS

Even the best marketers face challenges in responding to their organization’s and the market’s needs for leveraging online and interactive opportunities. As a start, marketers should reflect upon the following questions:

Who in your organization is responsible for online and interactive marketing?
How are you leveraging online and interactive marketing to advance your marketing strategy and improve the organization’s return on marketing investments?
How should these new marketing channels impact your strategy for meeting both internal and external customer needs?
What is your performance measurement strategy in this relatively new area, and how does it tie in to your overall measurement strategy?

Establishing Accountability Within Marketing

One problem is that the personnel and processes for supporting interactive marketing are often not located in the marketing area. For example, it may be that engineers from each product line are starting their own separate community sites to monitor product feedback from customers, or the company webmaster does his best to manage a new blog initiative. If marketing does not govern these efforts, the company may miss out on the most valuable benefit – the ability to collect and process marketplace information in a codified fashion, not to mention the opportunity to ensure that consistent branding and messaging is deployed.

Marketing needs to manage and integrate the organization’s online and interactive marketing processes. This might include, as an important starting point, oversight and governance of policies of programs that are executed across multiple departments. It might also include evangelizing marketing’s availability as an internal service provider to other functions that are deploying interactive marketing tools. This marketing role will help ensure that online and interactive marketing is an extension of the overall marketing strategy, not a new, disconnected effort.

An Extension of Your Marketing Strategy

As new technologies and applications have become available, early adopters and innovators across your organization may be developing new methods and techniques for communicating with the market and with prospects/customers. This experimentation and innovation is highly valuable and should continue, but these new and quickly maturing ideas and activities should still be integrated into your overall marketing strategy and go-to-market plan. This ensures that the fundamentals of marketing are not lost, the needs of the market are met and return on these efforts is optimized.

Two examples provide more insight here: execution of a “more mature” activity, the webinar, and development of a “newer” interactive strategy, social networking.

Execution of a webinar. The ease of execution and reduced cost of webinars have enabled organizations to host more events that are attended by more people. Problems may arise, however, if these marketing-related activities are not managed according to the same process used by traditional event-planning professionals, such as aligning webinar schedules and content with existing marketing campaigns and events/ activities; identifying the most appropriate target audience; ensuring the content meets the needs of that target audience; establishing objectives and metrics to measure performance; collaborating with sales and lead generation teams to develop the list of prospects and customers to invite; and following up with participants.
Social networking. Customers continue to indicate that vendors’ selling processes are out of sync with their buying processes. They desire access to a greater amount of technology versus product-related information on a self-serve basis, and they want to get it from sources other than the salesperson (e.g., company engineers and third-party sources such as peers and industry analysts). Individuals across your organization may be setting up blogs and other varieties of social networks as resources for your customers, and these efforts should not be stifled. But they should also be structured as a part of your larger Internet strategy for interacting with customers, not as stand-alone initiatives without any sense of cohesion.

Working With IT: A Key Success Factor

Much discussion occurs regarding the alignment of marketing with the CEO, the CFO and sales. Much less attention is given to forging a stronger partnership with IT. Many marketers indicate that IT has historically been too slow to respond to their needs and that they feel relegated to the bottom of IT’s to-do list. To fulfill short-term needs, marketers have traditionally outsourced their application development, leveraged software-as-a-service models and/or deployed homegrown applications (e.g., campaign management, market resource management, content management and lead nurturing). To make further progress on end-to-end marketing and better meet the needs of customers, marketers must develop a more holistic approach to their IT strategy. This key success factor becomes especially apparent with the advent of more advanced online and interactive marketing strategies. For example, your organization should eventually gain the ability to track online and off -line interaction with your prospects and customers
to better target resources to meet their needs, and to better align the marketing and sales process to the buying process.

Performance Measurement: Focus on the ‘So What’ of Your Metrics

Tech marketers need to improve tracking and reporting of their online and interactive marketing activities (both investments and returns), just as they would with other elements of the marketing mix. But when working with the huge sea of data and metrics associated with online and interactive marketing, marketers must be careful to select and analyze the correct key performance indicators. As many marketers are unfamiliar with newer applications, there’s a real risk for misinterpreting the data and forming incorrect conclusions.

Additionally, although online and interactive marketing provides significant opportunities for better measurement, not every aspect of this strategy should be directly tied to a metric. For example, not every visitor to your website or landing page should be aggressively pursued as a lead. One of the great advantages of a comprehensive online and interactive strategy is the opportunity to develop and deepen a relationship with your prospects and customers. While taking a “hands-off” approach during the early stages of their education and awareness-building process may impede your data collection, it will improve the organization’s overall customer creation and retention process in the long term.

Lessons From Online Practice: New Advertising Models for All Media

The Online Advertising Playbook aggregates and synthesizes what has been learned about online advertising during its first 10 years.[1] The book answers a challenge posed to The Advertising Research Foundation (ARF) by a number of marketers and perhaps most clearly expressed by Gillette’s Pat McGraw: “I really don’t need another highly charged sales pitch on the power of Internet advertising. What I would like to know is how it works and why it works.”

The ARF reviewed, studied and learned from a collection of over 1,200 academic studies, industry research and professional articles and has developed strategic principles and guidelines for effective online advertising, each illustrated by case studies spanning the full spectrum of marketing objectives, from lead generation to loyalty. This paper includes quotes from participants in and contributors to the development of the Playbook. Looking forward is especially important now, as the industry is crossing an inflection point from the conventional mass media interrupt-and-repeat model for advertising to a family of advertising models centered on relevance.

Why now? The first reason is obvious: Consumers are spending more time online. Jupiter Research reports that online consumers spend roughly the same amount of time on the Internet as they do watching television – about 14 hours per week.[2] High-speed connections, of course, are a major reason why; nearly 80 percent of U.S. residential Web users went online with broadband connections, and those broadband users spent about one-third more time online than dial-up users.[3] Broadband is ubiquitous and always on. Faster speeds provide richer, more interactive consumer experiences as well as access to and use of more entertainment options, information and services – both commercial and social.

A second reason why advertising models are shifting is that broadband and new technologies encourage consumers to create, contribute and share their thoughts and experiences and engage with other people. Blog-tracking service Technorati claims there are more than 67 million blogs, with 175,000 created daily.[4] Today every PC or Mac ships with video-editing software that can burn discs or easily convert video to a variety of distribution formats. Entire multitrack recording studios rivaling the most professional operations fit onto a few discs. Image-, music- and videosharing sites like Flickr, MySpace and You- Tube abound. Movie studios, music labels, advertisers and conventional media no longer fully control content, nor do they have a lock on the means of production and distribution. The “disruption” of these industries and their economic models is daily news in the business section.

A final reason for the emergence of new advertising models is that broadband penetration and consumer adoption of new technologies have encouraged advertisers to experiment with and employ banners, search text advertisements, Email, interactive rich media and streaming audio and video, and consumers to learn about brands, participate with brands in new ways and create new brand meanings.

At first, marketers quite naturally considered online media as extensions of space-and-time media: TV, radio and print. Advertisements during most of online advertising’s first 10 years filled measured spaces on Web pages with variously sized banners, rectangles, buttons or leaderboards. For a short while following the dot-com collapse, the Internet was nearly written off, due to the failure of many highly touted website businesses, many of which were based on advertising-supported revenue models or assumptions about consumers. We know now the problem was not the Internet but rather those Web companies’ business plans, management and unreasonable expectations for success. Post-collapse, as consumers and companies continued moving online, more practical business models emerged and started proving themselves, such as search advertising (now 40 percent of online ad spending) and e-commerce. Along with these came refinements in targeting advertising, understanding how websites build and hold audiences, and deeper insights into online consumers and their media and buying patterns. New technologies and broadband adoption enabled advertisers to make enormous creative leaps and develop landmark campaigns, such as that for BMW Films. These leaps are likely to continue, as marketing and advertising organizations are increasingly staffed by individuals who grew up with the Internet. Online properties have played some role in forming young marketers’ and advertisers’ world views, just as television, film, radio and print did for prior generations.

We can see that the sine qua non for interrupt-and-repeat-advertising – one-way communication from advertiser to consumer – is vanishing from online advertising. Marketers are moving to three new models of advertising. The first, the on-demand model, is based on consumers’ abilities to select and choose their content and interactions with brands. The second model is the permission-based (opt-in) model, centered on engagement, not exposure. The final model is one of advertising-as-service to consumers.

On-Demand Model

Central to this model is the consumer as content aggregator, filterer, scheduler, exposer and disposer. The era of consumers reading, watching or listening according to the media’s set schedules seems almost quaint; today, nearly every media organization is promoting its ability to be seen or heard whenever consumers want. TiVo and DVRs are emblematic of this trend. Even network television is experimenting with on-demand models. Episodes of some programs, even wildly popular ones, are sold on Apple’s iTunes or made available from a network’s own online distribution systems, such as CBS’ Innertube, or on a show’s official website. A regular train commuter might choose to spend her Monday morning ride watching video podcasts of business news programs that were originally broadcast over the weekend. In fact, many media have enjoyed a serendipitous benefit from the on-demand trend: Their archives have become hot properties as consumers seek to dig back into previously aired programming.

The broad adoption of Internet search tools supports the on-demand model. Before search engines and quality websites, consumers were at the mercy of manufacturers, retailers and distributors for brand information. If the store was closed or consumers missed an advertisement, they were out of luck. Today consumers routinely access, evaluate and act on brand information found via search engines and Web pages 24/7.

Another important aspect of the ondemand model is content personalization. Consumers want to leverage and harness the power of brands by customizing content to their interests, needs and tastes, often by managing site preferences such as “I want to see the weather in the 10016 and 90210 ZIP codes on my home page,” or “Update me only when there’s new information about Brand X.”

With choice comes responsibility. Jeffrey Cole, director of the University of Southern California’s Center for the Digital Future, writes in the Playbook that “people like choice, but not too much choice”.[5] Too much choice can be frustrating, overwhelming or immobilizing and counterproductive from a brand viewpoint. Furnishing consumers with tools to manage a reasonable number of choices is far better than giving them every possible option.[6]

For brand marketers today, it is not just about stimulating demand for their products and services but also about inspiring consumers to include those brands in the choices they make. Because consumers’ media consumption is becoming so individualized, there are many implications for brand advertising. Playbook contributor Rishad Tobaccowala, CEO of marketing strategy firm Denuo, pointed out that there is a need to revise widely held views on targeting. He argues, “In an on-demand world, you have audiences of one whom you need to re-aggregate into large enough audiences to target with both scale and relevance.”[7] This idea stands the traditional view of segmentation on its head and signifies that new types of thinking are needed to exploit the advertising opportunities inherent in the ondemand model.

Engagement Model

The engagement model centers on two key ideas: high relevance of brands to consumers and the development of an emotional connection between consumers and brands. Additionally, engagement occurs – as do all relationships – in a social context that can influence the quality and duration of the engagement.

“Consumers want to get involved with brands they care about and give brand marketers explicit permissions, through an opt-in program, to involve them with the brand,” writes Playbook co-author Joe Plummer. For these consumers, brands provide opportunities (not always taken) that go beyond typical transactional relationships to a hierarchy of privileged statuses and rewards. The “brand ambassador” is probably the highest status brands bestow on their best consumers. Ambassadors have insider access to marketers and gain recognition and social standing in the larger brand community. Microsoft’s Most Valuable Professional program, which numbers more than 2,600 members in 81 countries, is a classic example of the ambassador-type of engagement program. Ambassadors are not limited to high tech. Companies like Del Monte Foods also maintain small, very focused communities that give guidance and direction.

Because engagement hinges on emotions and relationships, marketers adopting this model conceive it differently from traditional advertising. The standard learning- and-persuasion measures commonly applied to 30-second TV spots or online banners (e.g., brand awareness, knowledge of brand attributes and purchase intention) are losing ground. Marketers are increasingly interested in understanding their brands’ social aspects. These include the ability to involve, inform and entertain and, in the longer term, co-evolve with consumers through the creation and ongoing development of brand meaning. Engagement is much more than “I know you.” In its ideal form, it is about bonding, shared meaning and identification. Harley- Davidson is perhaps the ultimate example.

Professionals writing about engagement view it as an opportunity because, once consumers have chosen to receive brand communications, the strategy is to make it worth their while by providing compelling brand experiences. Marketing Insight Corp. CEO Vincent Barabba says that consumer choice can “… lead to greater and more meaningful engagement between the consumer and the provider of products and services.”[8] A similar and more urgent thought is expressed by Digitas Chief Marketing Officer David Edelman: “… consumers are seizing control. Marketers have no choice but to reframe their perspectives and deliver engaging experiences that inform, educate or entertain. It is about defining an engaging concept … making it come to life … and enabling consumers to call it their own.”[9]

Engagement strategies are applicable both for B-to-B and B-to-C marketers. Visa USA, for example, created its Business Breakthrough program to target small businesses and dramatize the benefits of working with Visa to become more efficient and profitable. Visa held a competition to identify one- to five-person businesses that needed improvements in areas like marketing, organizational development, technology or accounting. After selecting finalists, they hooked the businesses up with appropriate consultants and created video case studies. Research shows that this target audience watches videos more than larger business customers and that they are more eager to participate in contests and related events. In just three months, the campaign generated more than 2 million visits to the Business Breakthrough site.[10]

In an example of consumer packaged goods, Nestle Purina PetCare’s family of websites includes informational sites as well as sites exploring the emotional connection between pet owners and their pets. The company furnishes customers with free picture-sharing tools, personalized podcasts, ringtones and desktop wallpaper – all designed to strengthen the three-way bond among brand, pet and consumer. Notably, Purina has gone even further, building engagement experiences off its proprietary websites; the company launched a page of Purina downloads on iTunes and maintains a presence on Yahoo’s pet portal, where it contributed the “Pet Weather” widget that, in addition to the forecast, provides owners with witty sayings from their dogs or cats and gives them the ability to personalize. Says Arc Worldwide account director Chris O’Brien, who handles Purina’s interactive, “If you bring them the right tools and the right information, you are going to build an affinity for your brand.”[11]

As these examples show, the engagement model is not mere diversion or mindless entertainment but a disciplined approach for achieving brand objectives. Engagement depends on leveraging consumer insights to focus the relationship and guide the experiences through which brand meaning is created, grows and endures. Solid engagement strategy is rooted in consumer data, drawing upon multiple sources that assist marketers in evaluating their engagement efforts, and takes place through multiple communication channels and touch points.

Advertising-as-a-Service Model

Advertising-as-a-service aims to provide consumers with information and capabilities that smooth transactions or enhance brand engagement. Playbook contributor David Kenny, Digitas chairman and CEO, aptly describes this approach as first identifying the services and information consumers need and then creating the messages and experiences relevant to those needs.[12] Planning campaigns begin with questions from the consumer’s viewpoint: What services does a consumer need? How does the service need to function? What is the best platform, or combinations of platforms, to deliver the service? These questions apply to almost every product category.

These messages and experiences occur across media and in both branded and third-party forms. One task for brand marketers and their agencies, therefore, is helping consumers manage the variety of sources brought to bear during brand learning and decision making.

Advertising-as-a-service can also include personalized services. Like the good country doctor who treats patients from birth through old age, marketers are increasingly able to capture their consumers’ histories and use them to provide targeted services. Some online retail websites, for example, pop up a help window when shoppers have performed a certain number of searches in a short time. It may be that they are having difficulty finding an item or just are not sure what they want.

Land’s End is one retailer that furnishes shoppers with a service that answers the question “How will this look on me?” Consumers can customize virtual models with their sizes and proportions to see how a particular item of clothing is likely to fit. And service can get even more specific, based on behavior. These are but a few instances where a little guidance may be very helpful and tip the balance from browsing to buying and improving the brand experience.

The downside to the good country doctor is that, as personal as he is, he cannot provide service beyond a local area. Marketers do not have that problem; they can use technology to scale their services to large numbers and are not limited by geography or time. Advertising-as-a-service is perhaps the most personal of the three models discussed and, for this reason, might be considered the most altruistic. Brands are helping consumers make decisions in their enlightened self-interest. Marketers still need to make sure that they deliver a helpful service at the appropriate times and avoid the trap of substituting technology for consumer insight and connection.

Applying the Models

First, it seems clear that while each model may be used alone, there are interrelationships among the three and they can be used in whatever combinations marketers deem best for their brands. Second, the new models shift attention away from traditional one-way direction of advertising centered on reach, exposure, cost-per- -thousand and standard brand metrics to measures that evaluate the quality of the relationships among consumers and brands, of which there are many.[13] In Kenny’s words, “Engagement trumps awareness.”

Third, the new models emerge from new technologies, but they are not determined by technology. Technology is an instrument of strategy and execution. MSN Corporate Vice President Joanne Bradford points this out in her Playbook contribution: “Start with the consumer to understand what drives people’s passion for your products and services, and then determine how you can use technology to deepen those relationships.”[14] Fourth, deepening those relationships depends on collecting and aggregating data on individuals and combining those findings with additional sources of consumer information and insight.

These new models provide marketers with flexibility and a range of options they can apply as consumers and situations warrant. “The best thing,” Joe Plummer writes in the Playbook, “is for brands to experiment with the model, or combinations of models, that suit the brand best.”

This paper is adapted from The Online Advertising Playbook, co-authored with Joe Plummer, Taddy Hall and Robert Barocci.

ENDNOTES

Plummer, Joe, Steve Rappaport, Taddy Hall and Robert Barocci, The Online Advertising Playbook, New York: John Wiley &Sons, 2007 (in press).
Dawley, Heidi, “Timewise, Internet Is Now TV’s Equal,” MediaLife Magazine, February 1, 2006.
Nielsen//NetRatings. “Over Three-Fourths of U.S. Active Internet Users Connect via Broadband at Home in November,” December 12, 2006: [URL: http:// www.nielsen-netratings.com/pr/pr_061212.pdf].
Technorati, “About Technorati”: [URL: http://technorati. com/about/], 2007.
Cole, Jeff, “Changing Rules and the Rules of Change,” Joe Plummer, Steve Rappaport, et al, The Online Advertising Playbook, New York: John Wiley &Sons, 2007 (in press).
Wagner, Randy, Brandweek Interview, January 22, 2007: [URL: http://www.brandweek.com/bw/search/ article_display.jsp? vnu_content_id= 1003535335].
Tobaccowala, Rishad. “Learn as You Do,” Joe Plummer, Steve Rappaport, et al, The Online Advertising Playbook, New York: John Wiley &Sons, 2007 (in press).
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Finally, Advertisers Can Calculate Real ROI From Digital Advertising

Providing advertisers with a wealth of opportunities to reach their ever-splintering audiences, the Internet has earned a reputation as the most accountable marketing medium. But the Web’s accountability as a marketing medium still falls short of fulfilling advertisers’ needs. As a result, the vagaries and shortcomings of digital marketing measurement models have stunted the growth of digital ad budgets, stilted creativity and limited the adoption of new channels for reaching key audiences. Today, however, thanks to new technology and industry demands, these barriers are coming down. A new measurement standard is picking up steam, and the industry stands to undergo even more change as a result. Marketers will be able to take greater advantage of the vast creative possibilities digital media has to offer, and brand marketers will be able to better justify redirecting traditional advertising budgets in increasing numbers to the Web.

BIG CHANGE, BIG OPPORTUNITY

This fast-paced evolution is turning the art of digital advertising into more of a marketing science. Audiences continue to consume content through new channels like video and mobile at a notably increasing rate. And as advertisers attempt to reach audiences through the widening variety of touch points, they’re being forced to rethink the value of their old, one-dimensional return on investment (ROI) measures. Advertisers, as a result, have been demanding a new measurement model that effectively demonstrates the ways consumers engage with their brands across each channel, site and placement, and at each stage in the sales funnel.

These changes have led to the introduction of a new ROI model for advertisers that are looking to digital media to reach their fragmented audiences (whenever/ wherever they are) and that want to measure the value of every touch point with their audiences (whenever/wherever they engage).

THE OLD MODEL TELLS ONLY PART OF THE STORY

A few years ago, measuring click-throughs gave way to linking to the “last ad.” This model – known as the “last ad” standard – assigns 100 percent of the credit for a conversion to the last ad consumers saw or clicked before they converted. At the time, this was the best approach we had – and far superior to offline measurement. Still, it’s a model that’s seriously flawed – and now, thanks to new developments, outdated as well. Today, the industry has taken a large step forward, enabling us to see and evaluate virtually every touch point on the path to conversion. In light of this fuller, broader picture, we see that the “last ad” standard masks the complete consumer experience – from their first impression all the way through the funnel toward conversion. Thus, it’s vital that marketers adopt a model that enables them to explore, measure and leverage the entire interactive experience.

THE NEW MODEL MAKES SENSE OF DIGITAL MARKETING

With the “last ad” model, you know the last stop a user makes before purchasing, but what happened earlier in the process? Different media influence users in different places along the way. Some advertising is targeted at achieving awareness, whereas other advertising seeks to close the deal. The technology behind digital advertising has finally caught up with the big ideas of smart marketers who have for years envisioned an ROI measurement model that could calculate the success of digital marketing campaigns geared toward brand experiences that correlate with the concept of the buying “funnel.”

The new Engagement Mapping model enables advertisers to calculate the ROI on each interaction a consumer has with the marketer’s message, not just the last. By providing a complete conversion analysis, the model calculates which of those interactions are most effective before the conversion.

ENGAGEMENT MAPPING: BETTER ROI MEASUREMENT

Quantifying success today requires much more than an adherence to an outdated model that measures only what happened immediately before the conversion. Engagement mapping enables a better measurement of reach (and the quality of that reach) while qualifying (rather than just quantifying) frequency. It enables today’s savvy marketers to also consider the importance and influence of factors such as ad format, frequency, recency, ad size, interaction and order.

The new model can provide a mosaic of analytics, which taken in full can provide a clear, thorough analysis of engagement ROI. And even though it’s infinitely more flexible, the Engagement Mapping model neither costs more for digital advertisers nor requires additional effort from the marketer. It requires only two simple things: 1) a desire to calculate engagement ROI instead of the return on only the last ad clicked; and 2) for your ad-serving technology provider to have enabled digital advertising and engagement mapping across all the various digital channels.

DIGITAL MARKETING IS NO LONGER JUST FOR DIGITAL MARKETERS

Marketers typically tie their marketing activities to stages within the marketing funnel: awareness, interest, intent to purchase and so on. This has certainly been the case with marketers concerned with traditional media. Because the new model for measuring the engagement ROI from digital media closely adheres to those long-held marketing tenets, digital marketing is no longer just the business of digital marketers. Digital marketing is finally becoming the business of every marketer.

The adoption of new digital-media measurement methodologies that more closely resemble traditional marketing strategy but are superior to traditional marketing measurement is enabling marketers to see how every engagement works together to drive their business. Because it proves the effectiveness of online awareness techniques and channels, engagement mapping makes sense and fits into the strategic thinking of visionary marketers. And it can free up both creativity and ad dollars.