Eric T. Peterson Doubts the Importance of Twitter

Eric Peterson spoke at Web Analytics Wednesday last night at WebTrends HQ in Portland. As usual, he was engaging and animated. I'd say there were about 30 people in attendance, and Eric kept the attention of every one of them. The question and answer session went on for 20 to 30 minutes.

Afterwards, a smaller group of us, including Eric, went to Dragonfish for beer and sushi (Eric's treat -- thanks Eric!). Eventually the conversation turned to Twitter. I found myself in the unexpected position of being the only one in the room who a) uses Twitter; and b) actually understood what Twitter is, how it is used, and it's potential value to the marketing organization.

Eric actually went on record with this statement (paraphrasing here): "Twitter has no value. You can't measure it. It's just a bunch of people talking." (Cue uproarious laughter.) Eric's a friend of mine, so I'm poking fun at him here. But seriously, I think he's missing the boat.

I can think of a way that Twitter is immediately measurable with web analytics, and some ways that it can be measured or support future measurement outside of traditional web analytics.

Use it as a viral or direct marketing tool. Use a URL minimizer (or smallerizer, as I like to call them) such as Twurl for all embedded links. Twurl has built in measurement, allowing you to see click-throughs on all your links. It's just an experimental tool at this point, but there are a lot of things it's creator, Rick Turoczy, could do with it. Of course, you could put a web analytics campaign tracking code on the redirect URL to track response and subsequent site behavior, too. Seems pretty measurable.

Use it to mine past or monitor for present conversations occurring about your brand. Track those conversations across the social mediasphere as they start on blogs, move to Twitter, and then end up back on the blog again. Use this as a component of buzz measurement. Go a step further and score sentiment. Are people talking positively about your brand or negatively about your brand. Identify the influencers and model the conversations. Are you trending in a negative sentiment direction? Does a negative comment from an influencer change the sentiment of those in their sphere of influence? Twitter's APIs provide access to a massively rich source of data about conversations about your brand, and even provide the FULL TEXT of the conversation. We're not too much engineering effort away from being able to mine that data, follow the conversations to other social platforms, map out who's influencing who, and get notified who you who you should be engaging and why.

As I write this Chris Grant and John Hawbaker are having a conversation on Twitter about the the engagement model Eric Peterson has proposed.

Regardless of measurement, though. Twitter is important for the same reason that blogs you don't write are important. Your brand has an online community whether you choose to participate in it or not. (I read that somewhere, but I don't remember who said it. Citation, anyone?) Participating allows you to impact the conversation.

Update: Forgot to mention, Eric did create a twitter account from his iPhone last night while he was arguing its unimportance. Welcome aboard, Eric. ;-)

Web Analytics Wednesday (as in Thursday) at WebTrends HQ tomorrow.

Web Analytics Wednesday in Portland will be held tomorrow (Thursday) at WebTrends HQ. Eric Peterson will be presenting on The Future of Web Analytics. If you are in Portland, please plan to attend.

More info and RSVP here: http://twurl.cc/t2

Measuring Web 2.0 Technologoes - Panel Discussion

I'll be a panelist on the Web Analytics Association's upcoming webcast Measuring Web 2.0 Technologies on Thursday, March 20, 2008 @ 12:00 PM ET / 9:00 AM PT. Other panelists include Brett Crosby of Google Analytics, Brian Tomz of Coremetrics, and Wes Funk of Omniture.

If you want to hear some lively discussion, I recommend that you register and attend.

Narrowing the GAP

Here's another example of a languishing brand attempting a turn-around. The GAP hasn't stood for anything in particular in years (except bland, I guess). I'm not sure they've actually narrowed the focus to a point where they will be successful.

Laura Ries has some thoughts on what happened and where they should go. It's an interesting read, and I recommend it.

This will be another one to watch.

Semphonic X Change 2008

The 2nd annual Semphonic X Change is now on the calendar. Eric Peterson has some good thoughts about last year's conference.

I was a huddle leader (there are no presenters) at X Change 2007, and it was an awesome experience. X Change is different because we are all there to learn from each other in intimate, small group settings. As a huddle leader, what I witnessed was a group of people who realized that each of them held key pieces of knowledge that, if they opened up to the group, became incredibly valuable as a part of the whole body of knowledge and experience contained in the room. We all learned far more from each other through discussion than any of us would have learned just listening to me talk.

If you have a chance to go this year, I highly recommend it. I hope to be there myself.

Tracking Your Reputation Online

Over the last several days I've been doing some research and experimentation with tracking reputation online. I'm a little surprised at the lack of tools to do what I think should be done. (I know, product opportunity.)

There are a lot of solutions that track "buzz". But buzz is one dimensional. It's fine and useful to know that 95 blog posts mentioned you last month, or that 35 forum discussions mentioned your brand. But what does that really tell you? If you believe that all PR is good PR (I do not believe this) then I guess that's all you need to know. Here are a few things that are missing in the solutions I've seen so far:

Qualitative Information: Were the mentions of my brand in a positive context or a negative context? Am I trending positive or trending negative? Is that spike in buzz last week due to that bad press about my brand, and is it fanning the flames? Do certain social media environments tend to favor my brand while other tend to disfavor? I don't expect the solution to know this, but I want a way to easily score or mark each mention, and then report on it.

Collaboration / Ability to operationalize acting on data: This esoteric sounding requirement is really just me saying "I need to be able to do something with this data, now. It's not good enough to just have it sitting there". In my vision of a healthy internal online reputation management program you've got people throughout your organization ready to engage and contribute to discussions throughout the social mediasphere. As you discover new discussions that warrant engagement, you need to be able to assign those discussions to people in your organization, allow them to update their progress on a particular assignment, and collect important information about the engagement such as details about key influencers (like other channels of engagement key influencers use). In other words, if I discover a conversation about my brand on Twitter, and that leads me to a blog post from that same person, and it turns out that person is a key influencer, I need to keep track of the channels that key influencer uses. If I later find out that this key influencer is a regular contributor to an online forum, I need to be able to keep track of that detail, too. Why? Because key influencers are people I need to develop a relationship with. To have a relationship with them, I need to know where to follow them. By the same token, I need to be able to treat some mentions as just aggregate noise. I don't care about the person, and I don't need anyone to engage, but I want to score it and report on it. Then, don't show it to me again.

Categorization & Reporting: Going back to my first want, I need to be able to categorize each mention for reporting and analysis purposes. Aside form the pos/neg score (which isn't a category), I want to tag each one for the products or topical references made that are important to me. Is it about one of my products? Is it about the company in general? Is it about the industry in general? All of this detail doesn't really do anything for me at the individual mention level, but when you aggregate mentions, and the start looking for correlations between various attributes and your positive/negative score, you are suddenly armed with real insight that can help you form or reform your strategy for reputation management.

Lastly, I want this tool to be a rich internet application (RIA). I'm already living in my web browser, I don't want another desktop app, even if it pretends to be a browser. My browser is highly personalized to my work style. A browser based app allows me to leverage my browser setup, rather than making me move back and forth.

For sure, I haven't see all the tools out there yet. So far my experience has been on the extremes: internet applications that are too simplistic; and desktop applications that aren't really built for what I'm trying to do.

If you have any experiences to share in this arena, I'd love to hear them.

Eisenberg's Hierarchy of Optimizaiton Needs

Bryan Eisenberg's article today on the hierarchy of optimization needs is a worthwhile read. In it, he layers the concept of prioritizing site optimization opportunities on top of Maslow's Hierarchy of Needs. An interesting concept, though I think his separating Usable and Intuitive onto two separate layers is a bit of a stretch, meant mostly to make a nice, marketable pyramid.



Still, very useful. You could take this same concept and apply it, with slightly different labels, to optimizing any business process. If you don't have the fundamentals (the bottom of the pyramid) in place (e.g. an operation that works) then driving more and more leads into to your operation is going to be of limited value.

Hooked on Pandora

Lately I've become completely hooked on Pandora. If you don't know about it, it's a free streaming music site based on the Music Genome Project. You create your own stations based on "seed" songs or artists. Pandora then uses the genome qualities of that song or artist to feed you other similar songs. You can "thumbs up" or "thumbs down" a song to tweak what it is that Pandora feeds you. You can also bookmark songs, which sends them to your profile page where other people can see what you like and you can link over to Amazon or iTunes to purchase the track.

I use Pandora primarily at work, but I love it so much that I've started using it at home, too, by connecting a laptop to the stereo we use most often - the one in the kitchen (my wife is also hooked). Sonos makes a home music distribution system that will connect to Pandora, but that seems like overkill to me.

Now I'm starting to want Pandora when I'm on the move. Some phones can be used to connect to Pandora, too, but not my BlackBerry Curve. Not even with the web browser. I know I can buy and download my bookmarked songs, but I bookmark songs from multiple stations, not all of which I'm interested in buying at a given time. It would be great if Pandora allowed me organize my bookmarked songs by station, and then buy all (or selected) bookmarked songs from a station in a single action. It should be as easy as possible (see below - I hate managing MP3's).

Really, though, I hate managing MP3's. I want Pandora to work on my phone so I don't have to manage files. It's a completely friction-free way of listening to music if you don't mind not being able to go directly to a particular song (you can skip ahead in the stream, but you don't have direct access to specific tracks). I don't have to manage anything to make it work. I like that.

Pandora, please work on my phone. Until then, I'm patiently waiting. And loving Pandora.

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Composed on my BlackBerry Wireless Handheld

Eddie Bauer Embraces its Inner Male

Eddie Bauer is another example of a brand that got big, then moved away from its position in an ill fated attempt to expand and paid the price in declining sales. In 1996, prior to the brand expansion efforts, Eddie Bauer had sales of $430 per square foot according the the Puget Sound Business Journal. That had declined to $250 by 2006. The expansion efforts included moving to dressier lines and more women's clothing, and abandoning the rugged outdoors position that made the brand so powerful in the first place. Stick to your position, or watch it erode and die.

As a clothing retailer, Eddie Bauer owns "outdoors" in the mind of the consumer. Straying from that proved disastrous. It appears that CEO Neil Fiske wants to return the Eddie Bauer brand to the rugged outdoors, where it came from.

Hooray for Neil! This will be another interesting turnaround to watch along with Starbucks. Interesting that both are taking place in Seattle. Don't know if that means anything, but it's nice to see this stuff happening in our own back yard here in the Pacific Northwest.

Prediction: $1.00 Starbucks Coffee = Bad Move

Quick Prediction: Starbucks attempt to move down market with $1.00 coffee will prove to be another in a recent string of brand mistakes. Starbucks stands for "expensive coffee" in the mind of the consumer. Adding a $1.00 cup of coffee to the menu, and attempting to compete with McDonalds and Dunkin' Donuts will dilute that perception, eroding the core perception of "expensive coffee", and revenue growth with it.

Another recent mistake was the hot sandwiches for breakfast. While I personally loved them at first, the quality seemed to wane after several months. Worst of all, the ovens made Starbucks smell like a fast-food joint, not like a coffee shop. Frankly, it was disgusting. In a business like coffee, smell is a huge part of brand perception...and the sandwiches were killing the coffee shop vibe.

It's funny [not so funny, I guess, more sad] to watch big companies like Starbucks start to mess with, and in some cases throw away, that which made them powerful brands in the first place. Starbucks is "expensive coffee", Dunkin' Donuts is "everyman coffee", and McDonalds "fast food and kids". Dunkin' is doing great job with embracing who they are, and presenting an alternative to Starbucks. Starbucks could stand to learn from them. Stick to your position, Starbucks, or watch it erode and die.

UPDATE (2/22/08): Looks like movement in the right direction. Of course, its very unfortunate to see layoffs, but previous management laid a course that was unsustainable, so the course has to be corrected. My hat's off to him for doing what needed to be done. Now, will he dump the $1.00 coffee, too? Time will tell.

UPDATE (2/25/08): I just heard from my wife that some stores are reporting that they won't be getting rid of the hot sandwiches due to so many people complaining about their disappearance. This raises another interesting question: how to weight the protests of a vocal minority when trying to pull a brand back to its position. I'm sure there are people who would love Starbucks to sell cheeseburgers, and if Starbucks had introduced cheeseburgers, they would complain when they were taken away. The instinct, of course, is to try to please all your customers. The problem is, you can never be all things to all people. When you try to, you lose your focus. When you lose your focus, customers stop coming because they don't know what you stand for. If I want a burger, I'll go to McDonalds. If I want coffee, and I don't want the fast-food burger experience with it, where do I go? Not Starbucks, I guess. We don't have Dunkin' Donuts here, so I'll go to my neighborhood coffee shop. The point is this...I don't have research on it, but I bet Starbucks is driving more people away with the fast-food experience than they are gaining by keeping the hot sandwiches. The counter-intuitive thing about positioning is that it, by definition, drives some people away, because your brand doesn't represent what they want. But it also strongly attracts those that want what you represent (assuming you're well differentiated from competitors). Those are the people you want to please, not the loud people tugging you away from your position.

Blog Remodel

We're undergoing a bit of a remodel here at Greater Returns. Shedding the stodgy look for something a little more dynamic and modern. Also, broadening the focus a bit, since I think about more than just Analytics and financial services.

I'm not entirely happy with Blogger's new templates. They're better, but they're still missing some things. For example, I don't seem to be able to have links to the previous and next post within a post. Seems obvious enough, but it doesn't seem to be there. If you know how to enable that in Blogger, let me know.

More on WA Standards

Judah Phillips makes an excellent argument for standardization of web analytics data that is more clear and concise than my own post on the topic. I still don't see people talking about industry-specific libraries of high-value events, though. Without these, practical interoperability between analytics products and peripheral products will be limited. A "purchase" event really isn't the same as a "flight reservation booked" event or a "credit card application submitted" event, and they shouldn't be treated or described the same. Without high-value business events, you're still just talking about the core measures and dimensions that are the same across all sites. Enterprise analytics solutions go well beyond these core dimensions and measures -- and so must any data definition standard.

I'm happy to see that there appears to be interest in this topic among the big thinkers. It won't be easy to accomplish, for sure. But I believe open standards will be beneficial to vendors in the long run.

Thoughts on WAA's Standards Committee's Web Analytics Definitions Document

I finally had the time today to start poring over this document, released by the Web Analytics Association (WAA) on August 16th. I haven't finished reading all of it in detail yet, but I have these thoughts (well, ok, they're rants) so far.

Let me start by saying that I'm excited about the publication of this document, as it represents a step toward the development of the set of standards for web analytics data collection and data definitions that will be required for true interoperability of web analytics products, and products peripheral to to web analytics that, together, create true business problem solutions. It's a small step, but a step nonetheless. In my dreamland, I see a standards-based library of vertical-specific business events that can be used as the basis for collecting, reporting, analyzing, and integrating analytics data. Web analytics has to move beyond simple counts and ratios of dimensions based on browser/client actions, toward standardized handling and reporting of high-value business events.

So, with that in mind, here are my unfiltered thoughts (rants).

Firstly, I'm left wondering what the purpose of the document is. Is it to put a stake in the ground as to what the standards should be, or is it to act as a sort of "meta user manual" that takes all the variant vendor behaviors into account, attempting to make any standard definition wide enough to include any vendor's product? In cases, it seems to be the latter. Consider this definition of Visit Duration:

The length of time in a session. Calculation is typically the timestamp of the last
activity in the session minus the timestamp of the first activity of the session.

Should not the purpose of a standards document be to declare the standard? Explaining typical behavior belongs in a book about web analytics, not in a standards document. That's not to say that you're going to get all the vendors to agree on the "right" way to calculate visit duration. But if there isn't a standard (or if you aren't declaring one) it doesn't belong in the document (IMHO).

Secondly, I'm a little disappointed that several of the definitions are self-referential (if you will) -- they use the word being defined as a core part of the definition. Sometimes the definitions are almost ethereal. Of course being a long-time practitioner, I understand what is meant, but I think this will make it difficult for new practitioners and managers to grasp the definition. Here's an example from the definition of Dimension:

A general source of data that can be used to define various
types of segments or counts and represents a fundamental dimension of
visitor behavior or site dynamics.

What? IMHO, I should be able to use a standards document to develop an entirely new web analytics product, based on the standards. This doesn't tell me what a dimension really is, so I can't develop the product based on a standard.

To be sure, there's lots that's good about this document, and I don't mean to minimize that. But I would love to see this pushed more toward true standards and have some of the core definitions crystallized even further.

That's all for now. More later (maybe).

X Change Wrap Up

Eric Peterson wrote a very nice, big picture summary post regarding the X Change conference (thanks for the kudos on my huddle, Eric!). I have to agree with him, it was a very positive experience primarily because it was so interactive. I tend to get bored at conferences (both as presenter and listener) because what I crave is impassioned discussion, not a one way dissertation. No matter how much you know, there is always more to learn, even if you're the so-called expert in the room. X Change created the opportunity to have these impassioned discussions, and I, for one, took advantage of that. I learned a ton. And I think the people in my huddles learned a ton, too. Not from me, but from each other.

Here's Eric's closing statement:

I’ll leave you with this parting shot about X Change, a comparison I’m shocked that nobody smarter than I has already made:

• Emetrics is the Web 1.0 conference for web analytics where you will learn a ton and be very happy
• X Change is the Web 2.0 conference for web analytics where you will contribute a ton and be very satisfied

Well said.

X Change Day 1

Day one at X Change was pretty enlightening. I liked the huddle format, where leaders and participants were encouraged to engage in an open discussion on a topic, rather than fall into a presenter-listener relationship. Some huddle leaders were better at facilitating a discussion than others (some really just presented), but overall each of the huddles I participated in involved a good healthy dose of discussion and debate.

Of particular interest to me was the session on "deploying measurement systems across the global enterprise" with Judah Phillips. I came away from this session having synthesized this key idea:

In any global enterprise execution of a web analytics solution there are two frameworks (for lack of a better term) at work. Each framework contains multiple potential models. There's a framework for solution design models, and a framework for solution deployment models. The models in each framework can be mixed-and-matched -- there isn't a correlation necessarily between model 1 for design and model 1 for deploy. The combination of models that works for you will depend largely on the political and structural ecosystem you work in.

Here are the models:

Models for Design

1. Decentralized business units or entities with a unified measurement model
2. Decentralized business units of entities with a unique measurement model per bu
3. Centralized business with a single measurement model

The benefit of model 1 is that you gain the ability to roll-up business events across the globe and compare business units on an "apples to apples" basis because each unit is measured in the same way, reporting business events according to the same model of possible events.

The benefit of model two is that everybody gets what they want.

Model 3 probably only applies if your businesses around the world are essentially identical, and managed from one HQ location. Can't think of where else this would apply.

Models for Deployment

1. Crawl, Walk, Run (i.e. roll out basic analytics, then, as Judah put it, roll out dimensions that have meaningfulness to the business, then integrate external data)
2. Deploy "meaningful" solution slowly across globe

Here, the benefit of model 1 is that you can introduce people to the solution over time, and slowly raise their level of confidence and competence without overwhelming them.

Model 2, in my experience, is necessary when you have a decentralized organization that can not handle a quickly paced series of small changes, but instead offers you only one window per year (or less) to deploy a solution, or where the decentralized nature means that you have different windows at different times across the different parts of the enterprise around the world, preventing you from orchestrating a carefully controlled series of phases.

Of course, I think there are hybrids, too. I've worked with companies employing multiple combinations of the models for design and deploy...this is what I've seen. What am I missing? What other models are there?

More OLAP Fun

I've taken on a new project in the last few days. I'll be working to help an enterprise-class company integrate existing customer data into their Visitor Intelligence solution, allowing them to segment existing reports or build new reports, on the fly, with any combination of customer attributes from outside data stores and web analytics data from the page tag.

The power of the reporting and ad-hoc segmentation is as I wrote about here, but this is even more interesting because rather than segmenting and constructing reports only from data collected through page tagging, we'll be leveraging the power of web services and OLAP style reporting to integrate data about a single visitor from multiple databases and 3rd party systems.

I'll post more as the project moves forward.

Adding to Eric T. Peterson's Commentary on Dainow

So I've been keeping quiet on the Dainow post re: Google displacing all other web analytics "products". Partly because this has been fun to watch, but mostly because I work for one of the other supposedly "dead" competitors. I wanted to see where this landed before I got in the mix.

Eric Peterson's thoughts on this are spot on. Here's Eric:

Dainow demonstrates a near complete lack of understanding of web analytics and the web analytics marketplace. Google Analytics already dominates the market in terms of total domains coded, but dominance isn’t defined by the breadth of your coding, it’s defined by the success your customers have using your application!

I'll go one further. What Dainow fails to see is the difference between a product and a solution, where a solution is a product and a set of services combined to solve a business problem. While the market well served by Google doesn't really require a "solution" as much as they simply need a tool to do a job, the customers served by the big players (my employer included) tend to need (and have the money for) services to ensure successful solution design, implementation, deployment, and adoption of the tool set and the business processes required to make good use of the tool set.

The farther you go up the market, out of mid-market and into true enterprise class solutions, the more this is true. In fact, I would argue that in true enterprise-class solution deployments (the area of consulting I specialize in) the services are more important than the tool set. The greatest tool in the world isn't worth anything if it can't be successfully deployed across a global enterprise with a standards-based approach. Google, neat tool that it is, is nowhere near displacing the few vendors who can play at this level.

See you at X Change?

I'll be at Semphonic's X Change conference in Napa, California on Thursday and Friday. I'm leading two "huddle" sessions on using web behavioral data to optimize customer experience and drive business result improvements.

I'm looking forward to some lively discussion, and I'm hoping to learn as much as I share. I'll post a summary of the discussion points, ah-ha moments, and key take-aways from each session.

Hope to see you there!

The Power of OLAP Reporting

With the announcement, today, of WebTrends new OLAP reporting solution (Visitor Intelligence) which adds reporting capability to the evolving suite of tools built on top of WebTrends warehouse architecture, I can finally talk about the power that is coming to the world of web analytics.

If you're not familiar with OLAP, or multi-dimensional reporting tools, the first page and a half of this article are worth a read. It's a good introduction to what's coming.

Essentially, OLAP tools, and WebTrends Visitor Intelligence is no exception, allow you to do deep, ad-hoc drilling and re-arranging of data, on the fly while maintaining the proper relationships and correlations between the dimensional data. While there are pre-configured reports, called Starting Points, in Visitor Intelligence that will meet the needs of "just give me the data" end-users, curious analysts will find themselves in a playground of possibilities.

Don't like like the order of the dimensions in the report you're looking at? Rearrange them, and the relationships stay in tact (just like in a pivot table). Don't like the measures that are in this report? Grab any available measure and drop it in the report. No longer are you confined to defining your report view, and being stuck with that. Nor are you working in a cumbersome environment where the relationships between data are not clearly represented and easily manipulated. The real power is that with OLAP reporting, all you need to know is which dimensions you want to report on, and which measures you want to report. From there, you can construct whatever report you want, on-the-fly, or you can set up starting points that are essentially pre-built reports. Also, the ability to create custom measures on-the-fly is absolutely awesome. No processing time, no analyzing. It's just there.

Here's a real-life example from a customer I've been working with to develop a robust reporting solution using Visitor Intelligence. This customer has a globally distributed and decentralized online business, which is organized roughly by regions of the world (each country is a division), brands operated by each division, and customer groups serviced on each site. Of particular importance to the customer is understanding how much of each division's business comes from a country other than where that division operates, and what services those "out-of-country" customers are consuming. This insight will help the business better understand who their customers are, and how to market to them.

In this case, the customer has tagged each of their web sites with a single, universal meta-data model that describes each and every web page in the world, and how it fits into the global organization. The model passes values for the region, country, and division, in addition to descriptive data about product lines and the divisional business units offering the product lines. The result is that we collect a rich set of data easily turned into dimensions in an OLAP environment. The icing on the cake is visit and visitor geo-location data built in to WebTrends that allows us to determine who is "out-of-country" in a particular visit, and who is not.

Upon launch the business will have both default report views tailored to their specific needs, and the flexibility build exactly the right views of the available data. User A, a global business manager who wants to see Unique Visitors by Country, Division, Brand, and Product can easily create that view. User B, a product manager, can build a view that shows Visits and Unique Visitors by Product and Brand. And User C, an analyst, can build a view showing Visitors, Visits, and Visits per Visitor for "out-of-country" visits only broken down by Division, then Country of Visitor, then Product usage broken down to Business Units offering that product.

I've never before worked with a web analytics tool that is this powerful, and opens up so many possibilities -- and I've worked at three different analytics vendors. It still comes down to business results, though, and what a full-featured OLAP solution brings to the table is the ability to easily explore and manipulate the data to discover the insight needed to make business improvements with measurable impact.

What is the Role of Marketing, Anyway?

This post has been moved to my new blog at WordPress...here.