Web Sense

Can Website Have an Effect on Call Centers? Yes They Can.

Merchant satisfaction with American Express as a credit card provider is essential. If merchants don't accept the card, cardholders can't use it and business suffers. There are multiple touch points for merchants who accept the Card. Two important ones are Call Centers and online support (Online Merchant Services - OMS). To stay ahead of the competition, American Express is continually looking how to improve customer service for improved customer satisfaction. Actions that can improve customer satisfaction and reduce costs are a tremendous win. Working with Joe Strickland, Director of OMS, we've just finished the first phase of doing just that.

I started working with Joe Strickland on measuring the activity of the website created for merchants to process their transactions online. In the beginning, we had just web data and any effect on Call Center usage was hard to prove, hard to measure, and hard to improve. We realized that to effectively use the website to reduce Call Center costs, we needed a complete customer experience view. We had to integrate all information on customer touch points - web, Call Center, and satisfaction survey data. To make a very long and difficult story short, Joe identified over half a dozen systems that contained the necessary data, arranged for data feeds, and established the appropriate access. We then analyzed the data and realized that there were inherent data anomalies that required business rules in order to make data integration meaningful. For example, there was a many-to-many relationship between user ids and account numbers which had no perfect solution. Together, we came up with a set of business rules to solve these and other issues. Finally after quite a bit of "blood, sweat, and tears", we had an integrated data source that had a very complete picture of how merchants interacted with American Express.

But that was not enough. When we looked at our new integrated database, there were no clear insights of what could be done to improve merchant service and thereby merchants' satisfaction. Averages hid more than they revealed. So we started to segment merchants based on their use of both the Call Center and online services (OMS). Combining statistics and an understanding of merchants, we discovered three very actionable segments. The first segment, the segment that produced most of the Call Center calls, consisted of merchants who never used OMS. Most of these merchants only called once and called to set-up their American Express account. Nothing that Joe did to OMS would or could have any effect on these merchants without an offline strategy to get them to use OMS to set-up their account. However, it was essential that before any effort was made to get them to use the web to set-up their account, there needed to be an easy to use online account set-up process. The question was whether such a process existed. Since we had integrated satisfaction survey data with Call Center and OMS data, we were able to find the answer. The answer was no. While not the answer we wanted to hear, it at least let Joe know that there was no point in having a campaign to get new merchants to set-up their account online until the online process was improved.

The next two segments were those of merchants who used both the Call Center and OMS. Interestingly, we found that merchants who used OMS prior to calling the Call Center made significantly less calls to the Call Center. In addition, we discovered merchants who used both Call Center and OMS could be divided very nicely into two very different segments. One segment had low usage of both the Call Center and OMS and the other had heavy usage of both. Each segment required a different strategy. With closer examination of their online behavior, we found that light users were often confused when they got to the OMS homepage and didn't know where to go were often going to more pages than they really needed. To solve this problem, Joe initiated a re-design of the homepage to better direct light users to where they need to go. His re-design not only provided better routing of light users, it provided information right on the homepage so that they some merchants didn't have to go anywhere else. This new, optimized, homepage has been in full production for just over a month and has been a meaningful initial success in changing merchant behavior. Landing page optimization, while usually thought of as a web only process, had a beneficial effect on the Call Center. We are now monitoring the behavior of this group both online and offline to see how this landing page optimization works not only in the short term but also over time and when it needs to be "re-optimized".

Heavy users of the Call Center and OMS, were not affected very much by the changes to the homepage. They didn't need better routing. They were heavy users and knew where they needed to go. A different strategy was required. By examining their online and offline behaviors, we were able to determine what concerned them the most. An initiative is now underway to address these issues.

This is just first phase. In analyzing the data we've found that different industries use the Call Center and OMS in different ways and that these industries fall into a few very definite groups. We are now doing a cluster analysis to determine more precisely what parts of OMS are used by which group so that a strategy can be developed to even further improve merchant satisfaction.

Looking back over this effort I am continually reminded that in order for an effort like this to work there are two essential elements. One, the web owner must be committed to seeing the effort through - there will be many obstacles to overcome. Two, the team doing the work must not only have strong customer centric analytic capabilities, but must also have an in-depth understanding of the customers whose behavior is being analyzed. Semphonic provided the analytic capabilities and Joe Strickland and his team provided the customer understanding. Together we made it work and we've only just begun. Can Website Have an Effect on Call Centers? Yes They Can. If you do it right.

Call Center Calls, Web Usage, and the Meaning of Other

In working with Call Center and web usage data, the meaning of "Other" (the call classification for calls that operators didn't know how to classify) became an important factor in understanding customer behavior and how to use that understanding to improve customer service. It turned out that customers with large number of "Other" classified calls were actually angry customers. Before getting into how we figured this out, a little background on the integration of Call Center and web data is in order.

For online processing sites, the integration of Call Center and web usage data is a powerful tool to improve customer satisfaction and reduce costs. Call Center support is much more expensive than web support, but there are some things that need the human touch of a live person. The goal is to maximize the use of the web for customer support without harming customer satisfaction or even worse losing a valued customer. By understanding how customers use both the Call Center and the web and the interaction between these two support channels customer support can be optimized - high satisfaction with low costs. Call Center data is heavily reliant on human judgment. Web usage data is reliant on effective implementation of technology. While there are technology issues in integrating the two sources, the issue of integrating human judgment with technology is even more difficult. The ability to use technology to improve human judgment is critical.

There are several challenges in integrating data from these two very different sources. Assuming that data is being collected for both in an electronic format that is able to identify the customer, there has to be a common key that connects a customer call with customer online usage. This can be an account number or a user id. In many companies, Call Centers and web sites use a different identifier. Call Centers may use an account number and the web uses a user id. If there is no table that ties account number to user id, then there is no way to integrate Call and web data. If there is a one-to-one correspondence between account number and user id or if both systems use the same identifier then there is no problem. Often reality is somewhere in between. For example, sometimes there is only a partial matching between Call Center and web identifiers. In other cases, there is a many-to-many relationship between the two identifiers. An account number is associated with multiple user ids, and a user id is associated with multiple account numbers. To solve these in between situations, companies must develop business rules that can be used handle ambiguous situations. These can range from ignoring ambiguous data and keeping track of how much data is ignored to grouping data together to eliminate the ambiguity. The grouping of data often happens in the financial industry where family members have multiple accounts and multiple user ids which can access these accounts. To solve this problem, accounts and user ids together that belong to single family are grouped. This technique is called "Householding", but it is not perfect. Sometimes it is difficult to determine who belongs to a single "household". Sometimes the difference between family member behaviors is significant and Householding hides important insights. Whatever the solution, the business rules must be well articulated and the consequences of their usage understood and accepted. As with all data integration projects compromises are essential. Don't let the perfect get in the way of the good.

Once a common key is established, the challenge of data compatibility must be addressed. When a call is made to the Call Center, the operator can record a wide variety of information ranging from call type to call resolution. Similarly on the web, a customer can view different content and perform different functions. For the integration of Call Center and web data to be effective, the information recorded by the Call Center must relate to the information collected on the web. For example, if a customer can change account information either through the Call Center or through the web, both systems must classify that action similarly. The closer the classification, the better.

Having a good (though not perfect common identifier) and matching classifications are the essential foundations of a good integration of Call and web data. It is not enough. Good Call Center data is dependent on the input of the operators. If the operators are not properly trained, the data they input is bad. Call Center training, turnover, and skill level are a never ending challenge. It turns out that understanding how Call Center reps respond to customers can be critical.

This leads me to the meaning of "Other" and why it is so important. At first, we ignored calls classified as other. Then one day instead of looking at "Other" in total, we looked at "Other" calls on an individual customer basis and found a very interesting pattern. Most customers who called had a small percentage of "Other" classified calls. However, callers who had a sudden increase in the number of calls had most of their calls classified as "Other". Then when the number of calls dropped down to a normal level, the percentage of "Other" calls returned its lower level. We then combined satisfaction survey data to the Call Center data, we found that the customers who had a sudden increase in calls most of which were classified as "Other" were also very dissatisfied. Angry, dissatisfied, callers consistently had their call type classified as "Other". This was very useful information. It was as if we had a new call type: "Angry". We could track the number of customers who had a high number of "Other" calls and know how many angry customers there were. The only thing we didn't know was why they were angry. The integration with web data provided the answer. We looked at web usage for the customers during the period when they had a high number of "Other" classified calls. In almost every case, for each angry customer there was a corresponding increase in site usage for a particular area of the site. Keeping track of what site areas makes customers angry, is a very good way to prioritize web improvements. It also helps create a strategy for how to improve Call Center training.

Don’t Use a Web Site that Does Not Cookie its Visitors

In his article Internet Says: "Me Want Cookie," WSJ 5/5/2008, L Gordon Crovitz points out that “Web sites do a poor job of explaining how and why this information [cookies] is used…” and that “Web sites and marketers have failed to explain why cookies are harmless…. So people don’t understand how the Web works, so fear they are being spied on and manipulated.” The consequence of which is more and more web users are deleting their cookies, and “Do-Gooders” are lobbying for and politicians are considering legislation to restrict cookies.

Crovitz’s primary justification for cookies is that they make advertising more relevant – visitors get ads for relevant products and services and “in exchange for seeing targeted advertising, we get access to Web sites, usually free.” Relevant advertising and free access are nice benefits from cookies but aren’t their most important benefit. The most important benefit of cookies and the reason I try to avoid Web sites that don’t cookie their visitors is that cookies enable Web sites to distinguish between visitors (not identify who they are just that they are different visitors). This is the foundation of the Web measurement necessary to improve users’ Web experience. Without cookies Web sites don’t have the information they need to improve their site. Sites that don’t cookie their visitors don’t care enough about their visitors to want to give them a better user experience.

Today most major sites use cookies to understand how their visitors use their sites. While companies such as DoubleClick specialize in the use of cookies for marketing purposes, the majority of cookie usage is for site improvement (most Web sites use cookies for both marketing and site improvement). Cookies provide the information necessary to answer questions such as:

Can a site’s visitors find the products they’re looking for? Is the check-out process confusing? How well does online support work? What features are useful and how often are they used? What kind of enhancements would best serve our customers? What types of capacity are needed? How can we improve the customer experience? Did the changes made to the site really improve the user experience?

Comparing the online experience with brick and mortar facilities, the absence of cookies would be like prohibiting companies from looking at and identifying their customers when they came to their facility. Today, banks observe customer behavior and use that information to do things such as have special windows for Merchants who come in with large volumes of cash, to have a single line for retail customers that is serviced by multiple windows, and to position customer service personnel. Retail establishments observe customer behavior to determine where and how to place and displace products, how to design traffic flows, as well as the placement of checkout stations. Grocery stores use membership cards to identify what products customers buy together to better place products making it easier for customers to find what they want. If done properly, it does improve profits, but it also improves the customer experience. No one would even think about prohibiting commercial establishments from observing their customers and using that information to improve their business. In my opinion, Web sites that don’t cookie their visitors don’t care enough about them to want to improve their site and should be avoided.

They only reason to prohibit online merchants from doing so is, as Mr. Crovitz says fear of the unknown – what cookies can and cannot do. Mr. Crovitz’s solution is to have better disclosure statements and uses as an example Walt Mossberg and Kara Swisher’s disclosure statement. Here's what is says:

“Some of the advertisers and Web analytics firms used on this site may place 'tracking cookies' on your computer. We are telling you about them right upfront, and we want you to know how to get rid of these tracking cookies if you like."

Read more »

Tracking cookies are small text files that can tell such companies what you are doing online, even though they usually don't record your name or other personably identifiable information. These cookies are used by these companies to try and match ads to a user's interests. They are used all over the Web, but in most cases, their presence is only disclosed deep inside privacy policies.

We want you to know how to get rid of these tracking cookies if you like. Here are links to pages where you can opt out of the cookies set by our ad-placement contractor and our analytics contractor:

• http://www.doubleclick.com/us/about_doubleclick/privacy/
• http://www.omniture.com/privacy/2o7

"We'd prefer a totally opt-in system, but, as far as we know, the ad industry doesn't have a practical one as of now.”

I enjoy reading Mossberg’s column and respect his judgment. However, in this case I think Mossberg and Swisher’s approach is wrong. It’s great that they tell people upfront about cookies. However, their whole emphasis is on what to do if you don’t like cookies and their explanation of the benefits of cookies is tepid at best. They subtlety pander to the fear of the unknown while pretending that they are objective. They should explain how valuable cookies are and that they enable Web sites to get better. Perhaps they don’t truly appreciate the importance of cookies in Web site improvement. Perhaps they are only aware of cookies as a marketing tool. They should advise their readers to keep their cookies and to avoid sites that don’t cookie their visitors.

I strongly agree with Mr. Corvitz’s position that there is quite a bit of misunderstanding and ignorance about cookies and their value. I propose that those of us who understand cookies and their benefits do something about it to combat the “real risk that someday soon we’ll find the untested hands of regulators in the cookie jar.” Web sites should have an information page explaining the benefits of cookies in access through a “cookie link” that only talks about cookies and their benefits in clear, easily understandable language (no legalize). Measurement companies like Omniture, digital Agencies like Digitas, and associations like the Web Analytics Association should take out ads in major publications explaining the value of cookies (if they don’t they may be out of business). Web professionals of all kinds should write their elected representatives explaining the value of cookies and asking them to refrain from misguided restrictions of their use. Let’s not be intimidated by fear-mongers and the ignorant.

Let’s standup for what we know to be true.

Data Integrators at X Change 2008

Data Integrators, are you ready for X Change 2008?

I'm looking forward to X Change 2008 for two reasons: Food & Conversations.

Conversations.

Last year we were just starting to integrate online and offline data. To be perfectly honest, all I could talk about were the "challenges" involved in data integration. Much has happened since then. We've actually done it. For me, the most interesting integration is that of Online Support and Call Center data.

To get a good picture of what's happening, we use a scatter plot with Online Support on one axis and Call Center usage on the other. We then divide the graph into four quadrants and look at different user segments such as online tenure and customer value. Wow do the patterns differ depending on the segment. Differ is interesting, but they differ in ways that are actionable for both the Call Center and Online Support.

That is valuable because we can use those differences to improve service and reduce costs. For example in many cases, in the first month or so after enrollment, clients are light users of both the Call Center and Online Support. Very quickly, however, there is a group that uses the Call Center over and over with very little use of Online Support. After about a year, the majority of this group is in the low callers and high online user group. By comparing their call types and online behavior, we are developing training and support programs that promise to reduce Call Center volume -- eliminate or at least substantially reduce the large number of calls made by customers with two to twelve months of experience. Because we can actually monitor the customer behavior based on the training and support they have received, we will be able to tell quite accurately what works and what doesn't.

We also look at repeat Call Center usage. Pilot programs have been started in which special training is given to a sample of Call Center Callers and their subsequent behavior monitored both online and offline. Without a doubt some things work (dramatically reduce Call Center volume) and some don't. Some work with certain segments but not others. What's great is that we have facts instead of guesses to support our conclusions based on our actions.

So what has this got to do with X Change 2008?

Well last year there was a group of hardy souls who were just starting data integration projects. In the X Change 2008 sessions, I'd like to compare notes and share insights with these pioneers. Then in the evening (we were all staying at the same hotel and didn't have to drive anywhere - at least if you reserve early enough) over drinks complain, vent, and get the relief that is only possible by sharing your pain with someone who has had the same experience.

So all you data integrators who have suffered the pain of data integration (How many user ids don't match? What do you do when you get records that show a single caller called 40,000 times in a single month?) come to X Change 2008. We'll share insights, swap stories, and get revitalized.

The Food.

I've met the chef at the Ritz and tasted his food. Each Ritz Carlton has a specialty and the San Francisco Ritz's specialty is food. It really is special. I've also seen all the rooms (dinning, conference, and bedrooms). Very, very nice.

Web Analytics -- An Employment Guide -- Where do you excel - Politics or Analytics?

To meet the growing demand for our web consulting services, we are recruiting newly graduated college students as well experienced analysts. As the use of the web becomes a requirement rather than an option, web analytics is becoming an increasingly popular high-paid career. (In the early days of electricity, there were electric companies - companies that used electricity - and non-electric companies. Today every company uses electricity and the distinction between an electric and non-electric company is meaningless. Similarly the distinction between a web company and a non-web company is rapidly disappearing.) In this environment, we've met some very good candidates. Many of whom have a choice between us (while we're the largest independent web analytics consultancy, we're still less than 20 people) and a large agency or general purpose consulting firm. Even though our starting salaries are equal to or greater than the large firm's offer, the candidates often choose the larger organization.

Is this a good decision or not? For those who know me, you know that one of my favorite saying is: "Know yourself and know others: in one hundred battles you will win one hundred times." Well what does that have to do with choosing an employer? Very simply, before you make the decision you need to know what you like, what your strengths are, and what the opportunities and success requirements of your future employer are. If you really like analysis and are good at it, you will do best at Semphonic. On the other hand if analysis is something you don't mind doing, and you have very good political skills you will do best at a large firm (agency or consulting).

With only one basic kind of service, web analytics, Semphonic must provide outstanding, cost effective consulting with every engagement. A large firm provides a wide range of services. Services that can range from web design, IT operations, media buying, to consulting not even associated with the web. Since their relationship is based on a wide range of services, each one does not have to be excellent, just good enough. Consequently, after a certain point, increased analytic capability is irrelevant. When that point is reached, politics becomes the critical success factor in one's career. Being a powerful, skillful member of the compensation committee, being able to smooze with other senior partners as well as client executives is more important than insightful analysis. The super stars of a large firm are those with exception political skills, and they make the really big bucks, more than a successful analyst at Semphonic. However, as with super stardom in any profession there aren't very many super stars and the competition is intense. The high salaries of these super stars requires that non-star employees (everyone else) work long and hard as they have to generate the billable hours that generate the revenue needed to pay the super stars super salaries.

Semphonic on the other hand has very little politics, a flat organization, and low overhead so that a much greater proportion of its revenue can go directly to the analysts doing the work. Its critical success factor is excellence of service. "Good enough" is not good enough. Consequently, increased analytic capability is very relevant. Semphonic gives its analysts more responsibility, more opportunity for different types of analysis, less stress, and more money than any large firm.

So what's the bottom line? If you're good at politics and like the trappings of a big firm and want a chance for super stardom (remember most people don't make star status) go for a big firm. If you like web analytics go for Semphonic. Choosing an employer is an important decision. You spend a large portion of you waking hours working. Make sure it's something that fits who you are.

If Semphonic sounds like a place for you, e-mail [email protected] with your resume and a letter telling us why you like web analytics.

Why Ask Semphonic?; Web Analytics -- The T'ai Chi Solution

Why "Ask Semphonic"? Because the questions are often more valuable than the answers.

In T'ai Chi (a "soft" marshal art that uses the soft to overcome the hard and the mind to overcome physical strength), there is a saying that I think applies very well to web analytics. "Know yourself and know others: in one hundred battles you will win one hundred times." The question is how best to know yourself and others from a web analytics perspective.

Just when you think you've gotten your web analytics under control, things change. Changes can be from any of three major perspectives: business, web site technology, or analytic tools. A marketing channel is no longer as effective as it once was. Your customer base is changing. You have a new product. Competition changes. Then there is always web site technology. You may redo your site in Flash or some other rich media with capabilities you never had before. Clients may be accessing your site through their cell phones, or RSS feeds may all of a sudden take off. Web 2.0 is here and Web 3.0 is on the way. Finally, there is your analytic tool. Pricing, capabilities, or even availability may change. What do you do?

So how do you know your web-analytic-self as well as web-analytic-others so that you can "in one hundred battles win one hundred times" with all this change going on? Start by asking questions. Start with some overview questions such as does your web analytics support your business objectives and how does it do it? Then get into the details of how. What site KPI's do you measure? How? Do you use segmentation? How? Do you track online campaigns? How? Do you track links? How? Do you measure any online processes? How? Do you do longitudinal analysis? How? What kind of web reporting do you do? How do you do it? Keep on going.

Put together a comprehensive list of questions that covers your web site from all three perspectives: business, web site technology, and web analytic tool. As your experience and expertise increase, keep adding to your list of questions and periodically re-ask them. You'll find that the questions are more important than the answers. Why, because the answers are continually changing while the questions don't change very much. If you have a good set of questions, any time there is a change in your environment all you have to do go to your question list and ask. On the other hand, if you just had a list of answers, how would you handle change?

If questions are the answer to how "in one hundred battles you will win one hundred times," what's the best way to take advantage of Ask Semphonic? Prepare your questions. To make sure you're not missing any, categorize them by the three perspectives, business, web site technology, web analytic tools. Select a few you think are the most important and submit them. Then during Ask Semphonic listen to the questions as much as you do to the answers.

When listening to the questions, remember that there are four different types of questions:

1. Questions you know the answers to.
2. Questions you understand but don't know the answers.
3. Questions you know but don't understand.
4. Questions you don't even know.

All four are important, but the last two, questions you don't understand and questions you don't even know about can be the most important. You may not need them today, but write them down. They could very well be the questions that give you the winning edge sometime in the future.

What I like about Ask Semphonic is that it gives you the best of both questions and answers. In short run the answers may be most valuable, but in the long run it's the questions. Semphonic consultants are a great resource for answers. Participants, and at this writing there are over 50, are a fantastic resource for questions.

The first Ask Semphonic takes place on December 11 at 11:00AM PST, 2:00PM EST (check out http://www.semphonic.com/analytics/asksem.asp) and will be about the Omniture acquisition of Visual Sciences. This will not only affect Visual Sciences and Omniture customers, but also has the potential of affecting others in so far as it changes the market dynamics of web analytic tools. The answers given today, may or may not be relevant a year from now. However, I'm sure most of the questions will be relevant. If you're forearmed with the right questions, you will be able to "Know yourself and know others: in one hundred battles you will win one hundred times."

Will Omniture Learn From Google?

What's Google doing that Omniture could benefit from? As Jessica Vascellaro writes in the Wall Street Journal, November 5, 2007, "[Google] hopes to entice others to develop features to exploit the mobile web.... If Google succeeds at rallying developers ... it could open the way for consumers to start doing more easily on their web phones what they can already do on the Web." Why is Google doing this? It's not because they are a philanthropic organization. It's because they want to own the market and they realize that they cannot provide all the features that consumers want as fast as they want them. They can, however, own the platform.

Omniture is in a similar position. With Web 2.0, technology is changing too fast for any one company to provide all the functionality that customers of web analytics software will need. The scope and complexities of rich media are such that Omniture will always be in a catch-up mode if it tries to do everything itself. Take Flash for example, Omniture is finally getting it's act together, but it's taken awhile.

During this catch-up period, what did customers do? Some suffered in silence. However, others wrote their own code. Since Omniture did not provide a robust API, these customers wrote code and placed it below the line line in the Omniture js file that says "Do not modify below this line". It usually worked until a new version of the js file came out. Then the customer had the choice of staying with their modified js file or figuring out how to modify the new js file so that they could continue using the capabilities they had developed. Let me tell you it wasn't always a very prettry picture. Another popular capability to add "below the line" is enhanced link tracking. The list goes on.

There are also features that customers would like, but even going "below the line" won't help. In particular, enhancements to the Excel interface. The existing Omniture Excel interface has a very nice GUI and is fine for new users or users with limited Excel expertise. However, there is a large group of web analysts who are not only experienced Omniture users but also very proficient at Excel. These users would love a robust Excel API. With a robust Excel API, Omniture could take credit for the power of Excel in reporting and analyzing the web data it collects and make lots of analyst very happy.

With Omniture's purchase of Visual Sciences, does it have any incentive to become a platform for web analytics and provide robust APIs so that others can develop Omniture features? In the short run probably not. However, who knows how short the short run will be. As Web 2.0 continues to take over, a smart competitor may take the software platform route and entice developers to develop enhanced features for their platform and eventually take over the market. Look at Apple. It had a better user interface, but didn't open it up and didn't capture the market. If they had, Windows may have been an also ran operating system.

In the meantime, what's a web analyst to do. You don't want to go below the line, but yet you need features that Omniture does not easily provide. Well, we can help. Our Omniture implementation guide (http://www.semphonic.com/analytics/impguides.asp) provides all sorts of tips on how to get the most out of Omniture without going below the line. We also provide an implementation review that provides solutions that don't require going below the line. In the longer run, let's hope that Omniture will learn from Google and start thinking of itself as a web analytics platform and not as a provider of all things to all people -- an impossible task.

Any features you'd like to see in Omniture that a 3rd party developer could add if there was a robust API. Do you have any horror stories related to modifications to the js file?

Omniture and Web 2.0

Now that Omniture is on the verge of swallowing Visual Sciences, the question is how well will Omniture move from Web 1.0 to Web 2.0. Will the Visual Sciences acquisition help or will it distract? Another important question is what will Web 2.0 measurement look like? Will it be supported by a powerful new application or will it be supported by a platform that accepts components from a wide range of third-party developers? My guess - and it's just guess - is that Web 2.0 will eventually go the way of a te platform with components from others.

Why, because there are too many possibilities in Web 2.0. Web 2.0 measurement will have address a wide range of challenges including mobile device support, qualitative in addition to quantitative analysis, integration of multiple data sources, rich media, as well as address issues of visitor identification. Making Web 2.0 measurement even more complicated, most of these challenges will not have just one solution. One size solution fits all solutions won't cut it in Web 2.0 and beyond. I don't think anyone vendor will be able to be all things to all web sites. If they try, they won't succeed. Rather the vendor that develops a te platform that accepts a wide range of third-party add-ons will be enormously profitable.

In their Wall Street Journal article, Strategies for Being a Platform Leader, September 27, 2007, Annabelle Gawer and Michael A. Cusumano write about what it takes to be a platform leader. Two of the qualities of a te platform include solving "an essential technological problem for many players in an industry" and "be[ing] easy to connect to or build upon." In addition, a successful platform leader must "create economic incentives that encourage other firms to develop complementary applications for the platform, and at the same time protect its own ability to profit from its innovations. This balancing act is perhaps the greatest challenge to platform leadership."

The question is can Omniture do this. So far, these qualities have not been their strengths. However, now that they are acquiring a competitor will they have the vision and the ability to move from a killer application to a te platform? Will the Visual Sciences acquisition go to their heads and prevent them taking the steps needed for success in Web 2.0 What do you think?

Omniture Acquires Visual Sciences: Don't Panic, But Don't Hide Your Head In The Sand

The announcement of Omniture's acquisition of Visual Sciences has created quite a stir. My advice is "Don't panic, but don't hide your head in the sand." Those of us immersed in web analytics are analysts, so let's analyze the situation.

For Visual Sciences clients, issues include moving to a new analytics platform with similar yet different features and capabilities, a different contract, different performance and a different support structure. While Omniture clients may assume that this won't affect them, they could be wrong. Omniture may be distracted by the effort to digest the Visual Sciences acquisition and performance and support may suffer. To aid the migration of Visual Sciences clients it may add features such as the HBX Report Builder which would be a very nice improvement.

With a larger customer base, Omniture may change its pricing structure. As Phil Kemelor points out in his Blog, Omniture's digestion of Visual Sciences is going to take some time and take some unexpected turns. (Omniture's digestion of Instadia's 200 clients is projected to take 18 months - how long will it take to digest Visual Sciences 2,000 clients).

Take advantage of the time it's going to take and take charge of your own fate - this advice is for both Visual Sciences and Omniture clients. What should you do?

1. Make sure your analytic house is in order (both Visual Sciences and Omniture clients);
2. Determine when and under what circumstances you want to migrate (Visual Sciences clients);
3. Keep abreast of changes in web analytics platforms, both technical and contractual (both Visual Sciences and Omniture clients).

#1 Make Sure Your Analytic House Is In Order

1. Using a structured perspective on your web metrics (business objectives to web KPIs to supporting statistics to application implementation) make sure that you are getting the information you need and you understand how your measurement application (Visual Sciences or Omniture) is providing that information;
2. Make sure you have meaningful standards and conventions for your web measurement. If you don't have any or if they are inadequate initiate an effort to remedy that;
3. Make sure that data collection is separated from data reporting and analysis. For example, if you are using an Excel interface, make sure that calculations and formatting for reporting and analysis are done in different worksheets than data collection.

#2 Determine When and Under What Circumstances You Want to Migrate

You got plenty of time, so take advantage of it and migrate when it makes sense for you. For example, if you are going from an HTML based web site to a Flash based web site, you are going to have to change your tagging for Flash whether you migrate or not so why not do the migration in conjunction with the move to Flash. If you don't have good web metrics standards and conventions, establish them and do their implementation as part of the migration. If you're not moving to a new web technology, don't need to improve your measurement standards and conventions, and don't need any new features, wait. "If it works, don't fix it." If you do migrate, consider out sourcing the migration, as it is not an expertise that you will need on an ongoing basis.

# 3 Keep Abreast of Changes in Web Analytics Platforms, Both Technical and Contractual.

Wait, watch, and listen. Monitor Omniture's digestion process of Visual Sciences for technical and contractual issues. Get your information not just from Omniture, but also from clients, analysts, and consultants. Also, keep abreast if what other vendors such as WebTrends are doing.

When migration makes sense for you -- technical, contractual, or support reasons -- make sure you know what you have, what you want and how your going to get there. Thus armed, migration may turn out to be a blessing in disguise. For Omniture clients, this may be a period of "interesting times" with lots of changes. Make sure you're set-up to take advantage of new features. Speak-up if performance or support suffers. Keep Omniture "honest" by monitoring industry developments.

You use your analytic skills to optimize your web site. Use them to optimize the Omniture acquisition of Visual Sciences for you.

Web 2.0 and the Opportunity for Web Measurement Standards

We depend upon standards and conventions all of the time. Often we don’t even realize that we do at least until they are not followed or understood. In the U.S., a raised hand, palm facing out means stop. In Iraq, it means “greetings,” “hi,” or “hello.” When a U.S. soldier wants a car with Iraqis to stop and raises his hand, the Iraqis think he is waving hello and keeps on driving, often to their detriment.

In accounting there are definite conventions regarding the classification of money and resources. Revenue and expense, asset and liability accounts are clearly differentiated. These conventions are essential for meaningful financial measurement and reporting. Executives that don’t follow these conventions can, as Enron executives found out, end up in jail. While not having or not following conventions and standards in web measurement won’t get you killed or land you in jail, it will make web measurement and analysis more difficult and prevent you from maximizing its benefits.

Except for some very general measures such as page views and sessions (even these are not always the same) there are generally no accepted web measurement standards and conventions across web sites. Even in a single web site there are more often than not no clear, well followed standards. Looking at URL names is frequently not unlike an archeological excavation. If directory “x” was used, it was when Joe was web master. If directory “y” was used, it was when Jane was web master. What’s wrong with that? It makes some of the most meaningful analyses difficult if not impossible.

For sites with large number of pages, most big sites, analysis on an individual page basis, except for pages like the home page, is not meaningful. There are just too many pages. What is meaningful, however, is analysis by content group. An online brokerage site wants to know whether information on fees is more effective than information on trading tools in getting prospect to sign-up. If all the “fee” pages are not in a single directory and all the “tool” pages in their own directory, it is difficult if not impossible to compare “fee” and “tool” performance, especially if measurement analysts are not informed when a new page is added that does not adhere to a standard.

And then there are links. If you don’t know how links are used, you haven’t a chance of knowing how well or how poorly your site’s navigation is working. More importantly, you don’t know how to improve it. I’ve seen sites where all of the links on a page were named “View Details,” impossible to differentiate, impossible to improve.

Because most major web metrics tools are based on actual names (URL, links, etc.) it is difficult to retrofit a measurement on a site without a naming convention. On the other hand, because web 1.0 sites do have names for their pages and links, there is at least something that can be measured even if it is not optimal.

With web 2.0 rich-internet-application (RIA) techniques such as Ajax, or Flash, if nothing is done to implement measurement, there will be no measurement. A site implementing a RIA solution is starting with a clean measurement slate that will be empty if nothing is done. So with web 2.0 you must take some action if you want measurement. There is no default, not even a bad one. If you have to do something, you might as well do it right.

What’s right? First of all follow the KISS (keep it simple s…..) principle. Establish simple, clear standards / conventions for naming and categorizing. If they’re not simple and clear, no one will follow them. Make sure they are flexible enough to measure what’s needed today, but also flexible enough to accommodate future requirements (future requirements that are not yet known). Make sure that everyone involved with your web site from designers to programmers to QA is aware of, buys into, and commits to the standards. Make sure that there is a process in place that supports their use.

While every site will have different requirements there are a few basic things that need to be tracked.

• Base pages. In web 1.0 almost everything a viewer saw was a page. In web 2.0. Pages are more like platforms on which events take place. So while there are potentially not as many pages, they are important. An event that takes place on one base page needs to be differentiated from an event that takes place on another base page;
• Events. Events nare actions that take place on a base page without going to another base page. Event names will have two parts. First, the name of base page on which it occurred. Second, a name that is descriptive and consistent across the entire site. For example, deleting a column in a report would have “delete” in the name as well as the column being deleted;
• Links. Links are actions that take viewers from one page to another (either on the site or off the site). The link name should consist of the from-page name (the page on which it originates), a to-page name (the page to which it takes a viewer), as well as link name that is descriptive and consistent across the entire site. The combination of these three elements should be unique across the site;
• Content Area. All pages should belong to a content area so that they can be meaningfully combined and compared and usage statistics correctly aggregated. Content areas can be either hierarchical or flat depending on site requirements. (For a more detailed discussion of content types checkout Functionalism at http://www.semphonic.com/functionalism).

I’m sure there are lots of things I’ve forgotten, overlooked, and omitted. I welcome all comments and suggestions. There is still a lot of thinking and work to be done to effectively measure and analyze web 2.0 sites.