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.

--------------------------
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.

Join me for 5 Insights from Online Marketing Experts

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:

1. 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.
   
2. 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.
   
3. 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.
   
4. 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.
5. 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.
   
6. 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

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

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

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

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:

1. The Critic
   
2. The Explorer
   
3. 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

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.