Greater Returns

I'm Blogging Over Here, Now...

2009-06-09T01:19:00.000-07:00

I've moved my blog to WordPress. Over here.

Sentiment Marketing is Coming - and it Looks More Like Direct Marketing than You Think

2008-08-05T07:22:00.000-07:00

This post is now located here.

X Change 2008 - Be There!

2008-06-11T22:28:00.000-07:00

I'm very happy to be able to say that I'll be attending the X Change 2008 conference in San Francisco this August. In my book it is the best web analytics conference running due to its intimate, participatory, and conversational format. If you did not attend the inaugural X Change conference last year in Napa, you really missed something special.

Special kudos to Eric T. Peterson and Web Analytics Demystified for sponsoring this year's event, too.

I'm really excited for this year's X Change. It's shaping up to be even better than last year, if that's possible. I'll blog more about it soon.

Eric T. Peterson Doubts the Importance of Twitter

2008-04-18T11:46:00.000-07:00

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.

2008-04-16T15:05:00.000-07:00

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

2008-03-12T12:37:00.000-07:00

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

2008-03-12T10:32:00.000-07:00

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

2008-03-11T11:30:00.000-07:00

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

2008-03-05T10:58:00.000-08:00

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

2008-02-29T11:11:00.000-08:00

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

2008-02-27T10:36:00.000-08:00

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.

--------------------------
Composed on my BlackBerry Wireless Handheld

Eddie Bauer Embraces its Inner Male

2008-02-25T08:32:00.000-08:00

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

2008-02-21T10:29:00.000-08:00

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

2008-02-21T10:21:00.000-08:00

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

2007-10-03T10:58:00.000-07:00

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

2007-09-27T21:58:00.000-07:00

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

2007-09-27T15:30:00.000-07:00

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

2007-09-21T08:51:00.000-07:00

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

Decentralized business units or entities with a unified measurement model
Decentralized business units of entities with a unique measurement model per bu
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

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)
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

2007-09-19T23:19:00.000-07:00

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

2007-09-19T22:43:00.000-07:00

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?

2007-09-19T22:22:00.000-07:00

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

2007-07-31T14:56:00.000-07:00

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?

2007-04-24T21:15:00.000-07:00

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

Join me for 5 Insights from Online Marketing Experts

2007-02-05T07:54:00.000-08:00

Join me on Thursday, February 8th at 11:00 AM PST when I'll be delivering the BtoB webcast 5 Insights from Online Marketing Experts.

In this webcast, you'll learn how to:

Profitably acquire new customers through search marketing automation
Develop a consistent marketing measurement framework
Leverage KPI dashboards to keep your finger on the pulse of your performance
Segment your customers and leverage cross channel data to target them effectively
Build profitable, long-lasting relationships with your customers

Update: 2/14/2007
The webinar went very well. Most exciting was the fact that there were lots of good questions from the audience. Many of the questions centered around KPI's. I came away from that with a very clear picture of the lack of clarity that still exists about what KPI's are, let alone which ones we should be looking at as marketers and business owners.

Here's what you need to know about KPI's:

They are KEY performance indicators, not just any-old-performance-indicators. Internalizing that distinction will help you weed out data that's good to have, but doesn't belong on a KPI scorecard or dashboard.
They should reflect performance of the drivers of your business that you can influence. As an e-commerce marketer or business owner, I can influence the number of people arriving at my site, the quality of people arriving at my site, the % of those arriving who buy or transact, the average value of a transaction, the % of buyers who become repeat buyers, how many visits it takes before a shopper becomes a buyer, etc. And all of these things roll up to impact one number - revenue - the ultimate KPI. If you're not tracking revenue associated with your financial services products, you should be.
If it measures something you can't influence, it isn't a KPI. For example, your business may be influenced by the weather. But you can' t influence the weather, so average daily temperature wouldn't be a KPI. It may be good supporting data that helps you make sense of of your business, but it isn't a KPI.
KPIs will vary based on the model of your business, and what drivers influence your business. There are no universal KPI's, though there are many similarities across consumer products retailers and banking/financial retailers.
KPIs shouldn't change unless your business model changes. Remember, they measure the drivers of your business. There aren't too many drivers when you boil it all down...we're talking 5 to 10 metrics.
Everyone across the company should be looking at the same KPIs. Everyone has the ability to influence these 5 or 10 drivers of the company's business. That doesn't mean that a site producer won't have a scorecard tuned especially for his needs and his area of influence...he will. But his scorecard is subordinate to the corporate scorecard with the highest-order KPIs.

Be sure to checkout the recorded version of the webinar, 5 Insights from Online Marketing Experts, and let me know if you found it useful.

Burby on Becoming an Analyst

2006-12-05T09:58:00.000-08:00

Jason Burby, ClickZ columnist, has written what could be considered a follow-up to my 3 part series on hiring an analyst. Where I focused on the analytics hiring manager, Burby's column offers a few tips for the individual contributor on how to become an analyst. His observations about backgrounds that lead to a good analyst jibe nicely with mine.

I wonder if he's been reading my blog? ;-)

Words to Live By from Steve Jobs

2006-11-10T17:15:00.000-08:00

I was just cleaning some papers from my desk, trying to get organized for Monday morning, and I stumbled upon a printed transcript of the commencement speech Steve Jobs gave at Stanford in 2005. One paragraph stuck out, enough that I wanted to share it.

Your time is limited, so don't waste it living someone else's life. Don't be trapped by dogma — which is living with the results of other people's thinking. Don't let the noise of others' opinions drown out your own inner voice. And most important, have the courage to follow your heart and intuition. They somehow already know what you truly want to become. Everything else is secondary.

Period.

How to Hire a Web Analyst - Part 3: Backgrounds

2006-11-01T22:19:00.000-08:00

In this third -and last- post in this series, I look at the work and education backgrounds that I have found lead to a successful web analyst. My previous two posts looked and key skills and mindsets, as well as personalities you're likely to come across in an analyst.

Work Experience

So, what have these people been doing if they're not already web analysts? As noted previously, any job that requires crating a simple, digestible story from disparate, complex sources of information or data is good preparation for a web analyst career. I have found that individuals with experience in crafting or analyzing online user experiences bring powerful insight to the role. At the end of the day, the core function of the web analyst is to synthesize reams of complex data into succinct ideas and clearly actionable guidance to the business. Analysts with a background in usercenteredd design or usability bring a keen understanding of the user experience issues that underlie the data, and as such are rich sources of insight into how the issues uncovered in the data can be fixed.

The good analysts I have come across have work experience in the following roles:

Marketing Analyst
Database Marketing
Direct Response Marketing
User Experience Designer / Architect
Information Architect
Usability Specialist
Web Producer

Lastly, look for people who you think would also be good marketeers. Not marketers, but marketeers -- candidates who truly empathize with the people in the market, and are interested in how to win their loyalty.

Education

In my experience, it's not so much important what the education of the analyst is, but rather that they are educated. I'm a firm believer that a baccalaureate is required for an analyst, or almost any professional careePossessionsion of a degree illustrates a level of commitment and discipline that is required for success in any career. More than that, though, I've never come across a good writer without a bachelor's degree. College, it turns out, is good at developing core skills even when you end up working in areas seemingly unrelated to your studies. Of course, there are lots of baccalaureates who can't write, so don't equate the degree with writing skill.

That said, I have had particularly good experiences with analysts who have degrees in psychology or sociology. People who have studied people tend to have empathy for them, and as such make good web analysts. Other educational backgrounds I've come across in successful analysts include:

Business
Psychology
Sociology
Liberal Arts
Math / Statistics

Series Conclusion

You'll note a conspicuous absence of statistics as a skill set in what I've presented here. I personally believe that statistics is not required prior to becoming a web analyst. What is required is an ability to manipulate numbers and data to uncover the story and communicate it. But I believe it is more important that the analyst have an intuitive understanding of the people behind the data, because a single data set can tell many stories, not all of them valid. Uncovering the right story means having empathy, which allows you to fill in what the data can't tell you -- why people are behaving as they are. If you hire for the right mindset, any missing technical skills -- basic statistics, Excel, data mining, web analytics tools -- can be trained.

Of course it helps if the person doing the hiring is a skilled analyst who can mentor the up-and-comers. If the person doing the hiring is not a skilled analyst, consider sending the up-and-comers through the University of British Columbia's certificate program.

I hope this series has helped you think a little bit differently about how to hire a web analyst. If you've been looking for analysts, you know that they're hard to find. In the case of web analytics, it's a luxury when you can hire someone who has the experience you're looking for. In times like these, when the demand is high, and the supply short, you have to be willing to look at ways to groom smart people into the role.

If you've faced this challenge, let me know how you approached it, and what the outcomes have been. I'm eager to hear from you.

How to Hire a Web Analyst - Part 2: Personality

2006-10-19T22:44:00.000-07:00

In my previous post, I outlined what I have found to be the right mind set, and the right core skill set to look for in a web analyst, especially when you're looking to hire someone whom you plan to groom into the role.

Today's topic is personality. I've observed three personalities in the quality analysts I've known:

The Critic
The Explorer
The Expert

In reality, pieces of each personality are in everyone I've ever hired or recommended for hire as an analyst, and each is a critical component of a successful individual. I've found that, in a given individual, one personality tends to dominate.

The Critic

The Critic personality is someone who is generally driven to question what is presented as "truth", "fact", or "good". They find reward in uncovering "things that aren't right", creating an understanding of what they've uncovered, and receiving recognition that they've uncovered something valuable. Of course, there is a pitfall to this personality. As with all strengths, this personality taken too far can become a weakness. You don't really want your analysts to go to your marketers and tell them point-blank that their work is awful. Your management challenge with this personality will be to teach them to soften the message to the business; to teach them that it's just as important to show people what's working as it s to show them what isn't working.

The good news is that I've found that this personality is generally well educated, well spoken, and able to distill complex ideas into simple truths, as that is the nature of the Critic. They also tend to be good writers and communicators.

The Explorer

The Explorer personality is curious and driven to understand, but doesn't have the potentially negative "critical" outlook of the Critic personality. They find reward simply from the process of exploring the depths of possibility in the data, and also from "driving good results" for the business. This personality will tend get frustrated if the business doesn't know how to put him or her to good use, but is an extremely valuable contributor when they are used appropriately. As with all personalities, there is a pitfall. The urge to explore has to be put aside at some point in order to finish the analysis, create the story, and drive the actions necessary to create positive impact on the business. Your management challenge with this personality will be to let them explore to the extent required for the business, and to help them develop the discipline required to have an end in sight and work toward that end.

This personality doesn't have the strong correlation to the simplifying mind set that I've found in the Critic. You'll need to watch for that.

The Expert

The Expert personality seeks to be seen as an expert in all that they chose to take on. They receive reward from recognition of their expertise in any number of subjects. This personality makes an excellent consultant, and you'll often find them in a consulting role. This is a confident personality, able to gain trust from their audience even when they don't have all the answers. It's a good personality to have around. Don't confuse this personality with the confident huckster. You still need to watch for the core mind sets (analytical, simplifying) and the core skills of communicating and writing succinctly. You're looking for someone who truly is and seeks to be expert in what they do, not just confident.

I've seen this personality in a wide range of education levels and with varying degrees of communication skill. Look for someone with excellent person to person communication ability, with reasonable writing ability. You may need to coach on the softer business skills such as protocol.

Backgrounds

In the next and final post in this series, How to Hire a Web Analyst, I'll look at some of the work experiences and educational backgrounds that I've seen in top notch analysts. Here's a teaser for you... Statistics isn't on my list.

How to Hire a Web Analyst - Part 1: Mindset and Key Skills

2006-10-17T23:09:00.000-07:00

Hiring a web analytics expert - a web analyst - can be quite a difficult task, especially if you're just starting the process of building the web analytics function at your company. Experienced analysts are in high demand, and are demanding high salaries as a result. By the same token, hiring inexperienced analysts, or even hiring people with no analytics experience at all, can be a risky bet.

What's the right way to solve this puzzle? Over the next week or so, starting with this post, I'll be posting a series on this very topic - how to build out the analytics function without hiring only highly experienced web analysts.

Recognizing a Good Web Analyst

Who will make a good web analyst is more a question of mindset and personality than it is of rote skills or past experience. Of course, hard skills and past experience make a difference, but you'll quickly find that experienced web analysts are in high demand, and are demanding increasingly higher salaries. As a result, the most efficient way to build your organization is to hire one solid analyst, if you can find one, then focus on building a team of people who, based on mindset, personality, and key non-analyst skills, can be quickly groomed to be solid web analysts. To do this, you have to look at candidates not for "what they've accomplished" but for "what they're capable of."

Mindset and Key Skills

A good analyst has an analytical, problem-solving mindset. They constantly seek to understand why things are the way they are, how seemingly unrelated things are connected, and to be able to explain that all to others. They think systemically, meaning that they have a fundamental belief that all things are connected (i.e. "if I push here, something will fall out over there"). A good analyst also has a simplifying mindset. They look for ways to distill complex ideas into simple, fundamental concepts that are understandable by everyone. This latter ability is crucial - in order to drive action from data, the data has to be turned into a story that is consumable by marketers and business people, and from which actions or "next steps" can be derived. The last thing you want is an analyst that simply overloads your marketers and managers with data.

The only hard skill I've been able to identify that has a connection to the mindset described above is writing. An individual who can clearly explain complex ideas in writing is demonstrating the ability to analyze and simplify. An individual who cannot write succinctly cannot be a good analyst. (They may actually understand what's happing in the data, but if they can't communicate it, what good does that do you?)

Personalities

In my next post, I'll cover the three main personalities I've observed that make quality web analysts: The Critic, The Explorer, and The Expert.

Decker (again): Only 3 ways to drive revenue

2006-08-23T11:04:00.000-07:00

Sorry if you're sick of Sam Decker. I think he's well worth your attention, though, so listen up. In number 5 of his Marketing Bullseye series at Decker Marketing, Sam reminds us of a fundamental truth for online merchants, be you selling widgets or financial products (we're all retailers, after all). And that truth is this -- there are only three ways to drive revenue:

Get more customers [acquisition]
Get more from each customer [increase size of average order]
Get customers to frequent {I would say purchase} more often [increase lifetime value of individual customers].

Sam goes on to detail steps you should take to execute on these sources of revenue, ending with this: 'Track progress against the goals.'

Ahh, the devil's in the details. How do you track progress against those goals? Online, this is where a robust web analytics package, coupled with a robust, well thought out online measurement strategy comes into play. A well implemented analytics package will make it easy for you to adopt the discipline of setting goals and measuring against them for each of the three sources of revenue.

It's been my experience, though, that banks and financial services companies struggle to see themselves as retailers, even though this is precisely what they need to do to be successful selling products online. If you're in this boat - you're hindering your own success.

So, how do you track progress against goals for each of the three sources of revenue?

First Things First
First of all, you need to have a way to track sales of individual products. This is a stumbling point for a lot of banks and financial services companies, as there is usually no revenue directly associated with an online sale. Even at the most advanced companies, it is rare that a financial product, such as a loan or credit card is approved, closed, and funded online, making the tracking of actual revenue a little less intuitive when implementing web analytics.

Most companies only get the customer as far as submitting an application online, taking the approval and closing process offline. Some may give an approval online, while others stop at simply allowing the customer to download an application so they can mail it or bring it to a branch. The point is, though, it doesn't matter. You can attribute revenue to any of these activities, and this is what you have to do.

In the case of a bank that accepts applications online, do an offline analysis that tells you what a submitted application is worth to the company. Use Sam's workback waterfall, which I 'borrowed' here, to figure out what what % of apps are approved, what % of approved are closed, and what the average value of a close is to the company in either total dollars or first year revenue. Then work backwards to figure out how much each submitted application is worth, and apply that value to each "sale" in your web analytics package. Do this at the product level, not at a global level. A mortgage is worth something wildly different than a credit card, and you don't want to blend those values or you'll end up with data that is a lot less actionable.

Treat the sale process the same way a retailer does: record key business events in the sale process. At the individual product level, record at least product views, application starts, product add-ons (you do cross-sell, don't you?), application submits, and product value ($$). A robust analytics package will allow you to roll individual product data up into multiple levels of product families/categories that map to your particular business.

Second Things Second
So now that you've got a strategy for reporting on product sales, including revenue, you need a strategy for reporting on your marketing efforts. Most of the top-tier analytics companies treat marketing programs in a similar way, allowing you to assign an identification code to each individual marketing piece so you can track the performance of the individual campaign or offer, as well as see rolled-up views of various groups of IDs. For example you can see all creative versions in a particular offer, all offers in a particular campaign, and all campaigns in a particular channel (such as email or banners).

So now you've got the fundamentals in place: marketing tracking, and product sales tracking. You are now armed to measure your execution on Sam's plan for driving revenue from the three sources available to you. So, how do you do that? Glad you asked -- this part is actually really easy.

Get More Customers
The key word here is customers. You don't want traffic, you want customers. How do you know if your marketing campaigns are delivering customers, not just traffic? Remember the 'business events' recorded during the sales process? Topline analytics packages will allow you to correlate those businesses events to your marketing IDs, making it possible for you to see not only which efforts drive the best response, but which efforts drive the most product sales. Analytics packages typically let you break out new buyers from returning buyers, too. New buyers=more new customers.

Get More from Each Customer
This is why it is important to calculate product revenue at the individual product level, not as a global average as we discussed above. Just as you can correlate product sales to individual marketing efforts, so too can you correlate revenue. Want more from each customer? Try increasing the average value of each sale. How do you do this?

Try cross-selling additional items in your product application process. "Want a credit card with that?" "How about signing up for Online Banking while you're at it?" Or try targeting higher value products (HELOCs vs. Credit Cards). Don't just drive new customers, driver new, higher value customers.

If you want more from each customer, you have to sell more. To sell more you have to think, act, and measure like a merchant.

Get Customers to Frequent/Purchase More Often
This is simply a matter of getting existing customers to buy again, see Get More Customers above, but look at repeat buyers instead of new buyers. Additionally, many analytics packages will allow you to see sales cycle data on individual products, or groups of products. If your goal is to increase purchase frequency, you would seek to see an increased number of buyers with a decreased number of days between purchases.

This is all pretty straight-forward, really. The hardest part is knowing how to set up your analytics package in such a way that your ongoing measurement and analysis is easy and intuitive. That's why it's important to find and work with an experienced analytics consultant during your implementation. That, perhaps, is the hardest task of all. Many vendors provide analytics consultants (strategic consultants, business consultants, whatever they call them), but not all consultants are created equal.

I'm eager to hear about your adventures in Analytics. Please send me your comments and stories.

Sharpening the Point

2006-08-01T10:54:00.000-07:00

I made this point at the bottom of a previous post, but I've been thinking about it more and more. It's a recurring theme in my work - people wondering why they aren't getting any value from web analytics when they don't even know what they're measuring. So I'm going to make the point again, in bold type.

You can't manage what you don't measure.
You can't measure what you don't define.
Period.

Here's an excerpt from an email conversation I had with a colleague earlier today that illustrates the point more clearly (I think):

It's not just about more traffic. You need to start defining what VALUABLE traffic is. What do people who are valuable do? Do they come to the site more often? Do they stay longer? Do they click on ads? Do they buy things? Whatever it is, you need to be able to define what value is to you. Once you can define it then you can measure it and correlate valuable traffic to the sources of that traffic and start to optimize your marketing efforts to drive more of your valuable traffic, and less of your valueless traffic. The goal should be do drive more valuable traffic with less marketing money over time.

Chew on it. If you're not operating from this perspective, you're wasting your money on web analytics.

Decker Does it Again

2006-07-28T00:31:00.000-07:00

Decker Marketing: Marketing Bullseye 3: Hit Goals with Workback Waterfall

Decker's nailed it again. In the third in his series on hitting the "Marketing Bullseye" Sam Decker introduces what he calls a 'Workback Waterfall', which he devised to help people understand how to 'processize' marketing. Read and understand this concept. If you run a for-profit financial services web site (if you think you don't I'd be curious to know what you're doing), this is how you should be managing. But, instead of the workback progression Sam uses in his example, yours would look more like this:

Let's say your Workback Waterfall ends at sale approved and moves back through submit application, initiate application, view product, and arrive at site. If you have a goal of 1,000 account sales per month, and you know what % of each previous step in the funnel will move forward for a given marketing response channel then you know how much of that response channel you have to buy (key word CT, email units, etc.) to generate the results you need: 84,000 site arrivals. More importantly, you now know what other knobs, besides input volume, you can turn to get the end result you're after.

Let's say you don't want to or can't buy enough marketing response to achieve your goal. Well, look at where you're losing people in the response funnel -- er, I mean workback waterfall -- there's plenty of opportunity to optimize the funnel itself to achieve your goal. How about nudging the % of app starters who submit from 40% to 45%, a 12.5% improvement, by streamlining the application moderately. Your number of submitted applications jumps to almost 2270, and your approved sales to almost 1135. You'd have to drive more than 10,000 additional site arrivals to achieve the same improvement. That's a lot of wasted marketing money, and a lot of wasted infrastructure to support "dead beat" traffic. As I'm sure you see, improving the % moving forward at any given step in the process has a compounding effect for each of the steps that follows it.

That, my friends, is the art of conversion optimization using web analytics tools. Discovering what knobs you can turn to drive more sales, then analyzing which knobs will yield the highest ROI and taking action. And that's exactly what I did for #12 on the Fortune 500 -- a giant leap in conversion rate and volume with no increase in marketing spend or input volume.

As decker points out, it's not exactly rocket science, but it does require discipline.

Six Sigma Applied to Marketing

2006-07-25T13:00:00.000-07:00

Decker Marketing: Marketing Bullseye 2: Think Six Sigma

Sam Decker, VP and marketing guru at Bazaarvoice writes in his blog on the application of Six Sigma to marketing, specifically online marketing. This should be especially interesting to banks and financial services companies, where Six Sigma reigns supreme.

Read carefully. It's actually a nice blueprint for successful adoption of a web analytics within the organization. The core principal of Six Sigma (Define, Measure, Analyze, Improve, Control) is also the core principle behind successful use of Web Analytics to drive increasing ROI from your marketing dollars, although we usually shorten it to some variant of 'Measure, Analyze, Improve' for simplicity's sake -- Define and Control are implied.

If you can't measure it, you can't manage it. And if you can't define it, you can't measure it. 'Nuff said.

Call it a Persuasion Funnel?

2006-06-21T10:44:00.000-07:00

Bryan Eisenberg's article, Conversion versus Persuasion: What's Your Challenge?, offers more support and, perhaps, better illustration for the conversion funnel I described in my previous post, Funnel vs. Hub-and-Spoke Conversion Visualization, which itself was a counter point to Shane Atchison's Conversion Funnel 2.0.

As I stated in my previous post, a valuable conversion funnel

recognizes that there is a flow to the decision making process that consumers go through, and that your site needs to push people through that flow, whether it's literally a linear flow or not. If you think of the funnel as visitor based, not visit based, and you think of the funnel steps not as pages on the site, but qualification levels of the visitor (or how close they are to making a decision), you see that it is an extremely valuable visualization.

Have a look at Eisenberg's illustration of the funnel he describes. It offers a nice view of how non-linear the buying decision process (and hence, the conversion process) really is.

Perhaps my conversion funnel is better called a "Persuasion Funnel"?

Event-Based Analytics

2006-04-14T15:36:00.000-07:00

After my last post, I was thinking some more about the power of event-based analytics, as opposed to "path based" analytics. In the previous post I wrote about the value of event-driven measurement being in the ability to correlate events (things people do, like "look at a product, or apply for a product") with other events. It's all true, but I left out something even more important: event reporting opens the door to pulling your web analytics data into customer or business intelligence systems, giving you the power of true "customer behavior" analysis, not just "web site visitor behavior" analysis. Pretty powerful stuff.

Things Visitors Do, Not Places They Go

2006-04-11T00:57:00.000-07:00

Many of the banks I've worked with come to web analytics with the assumption that the value of web analytics is in tracking visit paths all over their site. While pathing is a powerful tool in the right circumstances, it isn't the most powerful thing web analytics can do for you as a bank. Instead of thinking about "seeing how people move around", which is what path analysis reports give you, think a little bit more abstractly...think about understanding what "things people do".

Do they:

Respond to a campaign I'm running? Which one?
View financial tools and calculators?
Read detailed product information? Which product(s)?
Log in to Online Banking?
Begin a product application?
Make on online payment?
Ask to be contacted?
Complete a product application? Which product?
Close on an approved application?
Respond to a cross-sell offer?
Save an application to complete later?
Come back and complete a saved application?

You could certainly ascertain if your visitors did these things and more by relying on path analysis, but gaining any level of aggregate understanding of visitor behavior would be practically impossible. The level of sheer 'noise' in the data would be astounding, and actionability near zero.

If, instead, you focus on collecting data about the things people do as they do them (events), you'll find that you've armed yourself with a stream of customer data that is extremely powerful and highly actionable. The power of tracking events lies in the fact that events can be correlated with other events to answer questions like:

Which campaigns drove the most application submits?
Which products are benefiting most from my campaign efforts? Which campaign efforts?
Which products had the most successful cross-sells?
Do financial tools and calculators have a measurable impact on a visitors propensity to complete an application?
Which products sell best with existing customers?
Which prospect segments need a little extra catering to in order to make a sale?
Who are my most valuable customers, and how can I target them for additional sales?

These are the kinds of questions you need to be able to answer with web analytics, and they're not questions that can be answered easily if you focus on "where people go" (path analysis) instead of "what people do" (events). If this isn't what you're focused on, you're missing the boat.

Of course, I'm not suggesting that path analysis reports don't have their place. They are a key tool for understanding visitor movement in the context of analyzing and optimizing site design, content placement, and navigation design. But, in order to know where to focus your investigations with path analysis and other similar tools, you must have a solid event-driven measurement strategy that can answer aggregate visitor behavior questions.

Funnel vs. Hub-and-Spoke Conversion Visualization

2006-04-06T13:51:00.000-07:00

Shane Atchison of ZAAZ proposed a new way of thinking about conversion today, called the "hub-and-spoke model." He describes it this way:

The hub-and-spoke model places the product page at the hub, with multiple inbound spokes to products and outbound spokes to desired conversion paths and points. When you shift to this model, you get a more sophisticated view of your customers' interaction with your online business.

I think this is an interesting concept, but it is valuable as an additional view of visit or visitor conversion behavior, instead of as replacement to a funnel view. The funnel concept is still valuable in that it recognizes that there is a flow to the decision making process that consumers go through, and that your site needs to push people through that flow, whether it's literally a linear flow or not. If you think of the funnel as visitor based, not visit based, and you think of the funnel steps not as pages on the site, but qualification levels of the visitor (or how close they are to making a decision), you see that it is an extremely valuable visualization.

For example, your qualification levels might be:

Visitor (just the state of being a visitor - this isn't tied to a specific page of the site)
Browser (visitors who get to the category level or product level of the site -- or visitors who exhibit some other behavior indicative of a higher degree of engagement)
Shopper (visitors who add something to the cart, or who begin an application process)
Buyer (visitors who finally make a purchase, or who complete an application)
Repeat Buyer (buyers who buy again)

Although this looks linear, it isn't entirely linear in nature, as some consumers may enter the "qualification" funnel much more qualified (further down in the funnel) than others. There is no need to assume that a visitor must progress through each level, starting with the top. A visitor may become both a visitor and browser with just one page view, depending on where they land in the site.

And this is where the hub-and-spoke model that Shane proposes would seem to provide additional insight -- where do visitors enter the site, and how do they interact with the tools, features, and content that exist ultimately to drive purchase conversion (this is where revenue comes from, after all).

At the end of the day, each visualization is answering different questions and enabling a different kind of decision making. The visitor funnel answers macro-level questions about the level of engagement of prospects, and efficiency of the site at pushing prospects toward making a purchase decision. The hub-and-spoke answers micro-level questions about exactly how prospects arrive at the hub-level and move away from it. Together, the two views give marketing and site strategists the data needed to understand both raw visitor behavior, and the impact of visitor behavior on the conversion (and, by extension, revenue) performance of the site.

One note for banks and other financial services companies: Buyers in the example funnel above should be analogous to the revenue generating event you want your prospects to accomplish, or the closest thing to it on your site. For banks with online application processes that do not provide an approval decision online, "Appliers" is a good final step. For those that do provide an approval online, "Closers" would be a more appropriate final step of the funnel, and it should represent not only those that are approved, but those who actually accept the product and close the deal. Appliers, then, would be a good second-to-last step in the funnel, and this would give you insight into not only the efficiency with which your site encourages people to apply, but the quality of those people who do apply. It won't do you any good drive more people to apply if they're not credit-worthy.

I'm back...

2006-04-06T12:55:00.000-07:00

I've been pretty head's down at work for the last 6 months, and haven't had time to write. Things are a bit more sane now, and I'm hoping to take some time at least once per week to write here. I'll still be focused primarily on financial services, but may occasionally stray to a broader set of topics within analytics.

Don't hesitate to send me your questions or comments.

-Aaron

Banking as Retail

2005-11-28T12:34:00.000-08:00

Recently, while working the audience at an online retail event where the company I work for was presenting, I came across an individual who was actually in the financial services space. After brief introductions, he spent the next 5 minutes telling me about how he had virtually no professional resources available to help him do his job better the way online retailers do. So, he decided to come to an online retail event and see what he could glean.

I was ecstatic that he was there because, in fact, the sales side of Financial Services IS retail! Retail banks and consumer products retailers face many of the same challenges online, and retail banks can learn much from looking at the successes (and failures!) of their compatriots in the products space. To be successful, retail banks will have to start thinking of themselves, at least partly, as retailers. And from my experience, most retail banks are along ways away from this.

One of the best ways to start learning from products retailers is to look at the web analytics reporting that successful retailers have armed themselves with. Many of these powerful reports are applicable directly to retail banks and other financial services outfits. Some that immediately come to mind are:

Products reporting with revenue (yes, you can do this even if you don't transact money online!)
Products attributed to campaigns (which campaigns yield the most applications? the most revenue? the most valuable traffic?)
Cross sell reporting (how effective are you at getting applicants to add products to the "sale"?)
Product affinity reporting (what products are likely to be purchased by the same customer?)
Segmented conversion reporting (what types of visitors to your site are most likely to apply for specific types of products? to apply for multiple products over time?)
Campaigns reporting (onsite and offsite; which are successful, which should be scrapped)

The above list focuses on the public side of retail bank websites - the truly retail side. Of course, there is also the authenticated side, which is part self-service and part retail. In many cases, it makes sense to incorporate transactions and product sales from the authenticated side into the products reporting described above.

Also, you may have noticed that I left out "scenario analysis" reports from the list above. It's not that I don't think they're important -- they are crucial -- but I've left them out because scenario analysis reports are best used as part of a program of application conversion improvement (i.e. figuring out why applicants drop out of the process and fixing the problems causing them to drop out). They're not well suited to provide overall products reporting, though many banks continue to focus their reporting efforts on scenario analysis. In doing so, they're missing the huge opportunities that become apparent when the right reports provide the right insight.

Over the next few posts, I'll be focusing on how each of the above types of reports can help retail banks be successful online. I'd like to hear about your experiences with web analytics, too, from either a retail or financial services perspective.

Defining KPI's - Update

2005-10-19T12:04:00.000-07:00

I thought a little bit more about how I described the process for defining KPIs - and I came to this realization...

While it is true that you have to know what your business objectives are in order to tie your web measurements into group-, division-, or company-wide goals, often times it's easier to start at number 3, Describe desired visitor behaviors, and work your way up (toward connection to management objectives), and down (toward KPIs and contextual data) from there. The end result is still the same - the ability to illustrate to management how what's happening on the web site is directly connected to the larger goals that management cares about.

Here's what that looks like applied to the top down approach described by Schiff in his post on KPIs.

Optimization Tip - The order of states in an address form

2005-10-14T10:10:00.000-07:00

Checkout Jared Spool's post on this topic in his Brain Sparks blog. This is the type of minute detail that you have to focus on when you're optimizing business performance on your web site. This is especially relevant to retail (billing and shipping addresses) and retail banking and financial services (account applications).

If you want to achieve the greatest possible return from your investment in doing business online, leave no stone unturned when it comes to performance optimization. Seemingly small changes can add up to millions of incremental dollars annually. I know. I've seen it happen.

Measuring the Right Things [part 2] - Defining your KPIs

2005-10-11T23:11:00.000-07:00

I've been thinking about this post for a few days now, trying to figure out just the right way to approach it. What's got me thinking about it is that I'm getting ready to engage with a new client to help them define a Key Performance Indicator framework they can use to enforce a more disciplined approach to site management within the organization. Additionally, they want a framework with which they can document the business value of the site to executive management.

Conceptually, defining KPIs is extremely simple...

1) Understand your Root Goal or Overarching Business Objective
2) Document the efforts you'll undertake or approaches you'll use to try to achieve those goals
3) Document the desired visitor behavior to result from your efforts
4) Express the ratio or data-point that lends insight into the scrutinized visitor behavior (this is a KPI)
5) State the individual measures that create the ratio or provided needed context to understand the KPI

What end up on your scorecard or dashboard is nos. 4 and 5. Numbers 1 through 3 you use to provide the overall business context when you write up your analysis of overall website performance for management.

Where most client-side analysts or site managers tend to fall down when deciding what to measure is failing to explicitly state and understand the Root Goal that 'efforts' and 'behaviors' are derivative of. Most of the time when I ask a client what their goals are they tell me about desired behaviors or eff0rts to affect behaviors, but they don't talk about the high-order objectives -- the Root Goal. As is true with any business, you need to understand your goals before you can understand your performance, or even what you need to measure to understand performance.

Here's an example of a fully defined KPI for a retail banking site:

1) Root Goal: Grow new account revenue 20%
2) Effort (or Approach or Method): Improve attach rate (cross sell performance)
3) Desired Visitor Behavior: Complete application with accessory products
4) KPI: % applications with accessory products
5) Contextual Data: # of applications, # of applications with accessories, AVG Revenue/Application (without attached accessory), AVG Revenue/Application (with attached accessory)

A colleague forwarded me this post from Craig Schiff while I was working on this post. In it, Craig does two things nicely (aside from being a smart guy): he provides a nice graphic illustrating the top-down definition of KPIs; and he clearly demonstrated to me how web analytics is just a little slice of BPM (Business Performance Management). We're working on exactly the same challenges, just on a different scale. The wording in his process is slightly different from mine, but they both get you to the same place.

Here's Craig's illustration:

One other note about Schiff's process -- I liked step 5 so much I included it in mine. I had not explicitly called out the needed contextual data separately. Instead, I was just including the contextual data as part of Step 4. It's much clearer when you call those out separately.

Blog ROI

2005-07-07T14:31:00.000-07:00

Heidi Cohen on measuring blog ROI

Haven't had a lot of requests from clients to measure the impact of blogs, but it sure seems like a good idea. You can easily build a hard-dollar case for the value of a blog by treating it as another piece of online media. Include your blog (or blogs) in your campaign reports and correlate conversion metrics, such as product views, purchases and revenue to customer behavior on your blog.

Don't sell stuff? Correlate any conversion, like lead capture, and assign a dollar value to each conversion event. You don't need to sell online to understand the revenue impact of conversion and the media driving conversion.

Measuring the right things. [part 1]

2005-07-06T12:17:00.000-07:00

The thing I get asked to do the most, and the thing the most people seem to have trouble with, is identifying the right things to measure. It's not surprising that clients have so much trouble - the possibilities are crazy. You can measure anything (well, anything that's measurable).

It's actually an age old marketing problem - if you provide too many choices, the customer gets option paralysis. They can't make up their mind. In the classic marketing sense, option paralysis leads to a slowed or lost sale (I can't pick which one I want - it's too difficult). In the case of web analytics, it leads to data bloat (I want everything, just in case I might need it). Problem is, there tends to be an inverse relationship between the amount of data available and value derived. While it's true that we consumers want choices, we don't function very well if we have too many of them.

So in these cases, it's my job to help clients identify the right data - the key data points they should surface to understand, at a strategic level, the business performance of their web site. You may have heard of these data points...they're your Key Performance Indicators (KPI's). Of course, you need more than KPI's to manage a site. But the right KPI's will make using the rest of your data easy. They're like a road map in an unfamiliar city. Without them, you're completely lost.

Actually, come to think of it, they're more like the Neverlost GPS you get in your Hertz car. Well thought out KPI's actually tell you where to go.

Now, in my mind, KPI has become over used and under utilized. Lots of people talk about tracking KPI's, but very few people are tracking what I would call truly key performance indicators. Further, we run the same risks with KPIs as we do with data in general. Too many, or poorly organized, KPI's become just more data.

Stay tuned. In another post I'll talk about how I help my clients arrive at the right KPI's for their business.

What are we?

2005-07-06T11:52:00.000-07:00

What are we... Web Analysts? Customer Behavior Analysts? Site Optimizers? Design Analysts? Web Analytics Gurus? [fill in the blank] Experts? Online Business Analysts? If you take into account where we come from, how we got to be Web Analysts (or whatever), you could add Usability Engineers, Interaction Designers, Information Architects, User Experience Analysts & Designers, Interface Designers, and Direct Marketers to the list. We're quite a varied bunch.

I'm not sure what the best title for us is, and I'm not sure we know enough about what we do and where we're going to have the right title just yet. I suspect there may be some specialization in the field required before the titles start to settle in. I'd be interested to hear your thoughts on how the field will specialize (or is specializing already).

Whatever you call us or what we do, it appears that, according to Jason Burby, we have very satisfying jobs. I would have to concur.