I’ve been thinking a bit about targeting, and how we in the web analytics industry have just a ton of visitor or segment-level data that can be used for targeting ads or content, but most tools don’t let you use the data or easily feed it to other systems to do any targeting.  It’s rather odd, don’t you think?   Even Omniture Test and Target isn’t using, as far as I’ve learned, a single data model or the data collected from their behavioral tools, like HBX or SiteCatalyst, for targeting.  All their data models and thus, their data, are unique to the products in their platform.   So I decided to resussitate/revise a blogviation and offer it as food for thought on MediaPost.  When I reread this post, it’s more of an informational post for product managers on how I’d begin thinking about targeting with analytics data and what types of targeting are possible, so here it goes.   

Targeting refers to the process of delivering content or ads to segments or visitors based on their known attributes.  The goal of targeting is simple to understand: maximizing the performance of content or an ad by serving it to visitors at a time when they are most open to the receiving the message. 

For example, you may visit a site, and see some type of ad unit calling out at you to “meet singles in <insert_your_city>.”  When browsing a real estate site, you may see ad units for realtors and mortgage companies.  After entering a keyword such as “car insurance” and clicking through the search results, you may land on a site and see an ad for a car insurance company or land on a page that persuades you to begin the process for creating an insurance price quote.  That’s targeting in a nutshell.  It’s simple for a site owner to understand:

1. Visitor X has these attributes.  
2. We have content or an ad that we think will appeal to Visitor X’s attributes. 
3. Let’s show the relevant content or ad. 

In online media, targeting is associated with paid search campaigning, ad serving, and content optimization based on recognizing and responding to the following attributes:

• Category and sub-category.  Conceptual constructs like “categories” of topics on a media web site or products on an ecommerce site can be targeted to include certain types of ads or messages.   The idea is that if visitors are browsing your category for “hardware floors,” you could offer them an ad or content specific to “flooring installation services.” 
• Geography.  Country, region, city, state, DMA are all targetable constructs.  You may run a sports site and choose to target people surfing in from 02116 (Boston) an ad for Red Sox tickets or content about Manny Ramirez’s recent trade to the Dodgers.
• Browsing environment such as the connection speed, type of browser, operating system, user software, domain, and ISP.  An ad network could serve an ad for DSL to a modem-based surfer by detecting the visitor’s browsing environment.
• Time.  The idea of only showing content during specific periods of time is called “parting.”  Common types include day-parting and season-parting.  For example, a B2B site only choosing to show ads for a particular manufacturer’s product during business hours — the site’s busiest time of day — would be an example of day-parting.
• Keyword.  There are many different types of keyword targeting.  Search engines target ads based on keywords in queries.  Content Management Systems target content based on site search keywords or referring keywords.  “Keywords” may be associated as metadata with site sections or pages, similar to zone or category targeting on an ad server.  Once a page is associated with keyword metadata in an ad tag, you can tell your ad server to target ads to that keyword on whatever page or pages the tag was placed. 
• Language.  When a language can be detected or known in advance, you can target ads to visitors in their language.
• Demographics. If the ad server is aware of a segment’s demographics, such as age, gender, income, title, purchasing power, and so on, an ad can be targeted on that basis. 
• Context.  Think of AdSense and how it matches text ads based on the semantics in site content.  Or when, after adding a product to your cart, a site offers you “free shipping” if your total purchase exceeds a certain price.  This is content targeting based on context.
• Profile.  Targeting is possible based on conclusions drawn and rules created from attributes about an individual or segment (such as purchasing propensity or job title).
• Rules.  Serve an interstitial ad only to visitors who don’t have a cookie set for the site.
• Events.  Someone deposits a large sum of money into his bank account, so the online banking site offers him a CD product on his next login.

We’ve all heard, of course, about a very specific type of often-discussed targeting in online advertising: “behavioral targeting.”  Behavioral targeting refers to the technology and process in which an ad or content is shown to a visitor based on their past actions and reactions.

Behavioral targeting involves:

1. Collecting behavioral data about visitors.
2. Identifying when those visitors visit a site.
3. Determining the current context of visitors on the site.  
4. Detecting the visitor’s current behavior.
5. Serving relevant ads (or content) matched to the behavior.

The goal being to use past behavioral data to influence the customer buying cycle or marketing lifecycle, in order to more effectively and more quickly deliver on advertiser and site goals.

So where does Web analytics come in?  You would think Web analytics data from “Web analytics” technology would be used to enabling “targeting.”  After all the best Web analytics systems store detailed visitor level data about past behavior.  Web analytics data certainly can be used, but in most cases, targeting is a function provided by the ad server or network, perhaps the ISP, or another technology called the “behavioral targeting platform,” not from data collected by the Web analytics tool.

In order to make Web analytics data useful for targeting, you will need to use your data to:

1. Define segments to target or identify visitors to target.
2. Feed past behavioral data about segments or visitors to the targeting technology.
3. Analyze segment and visitor performance against site or advertiser goals after targeting.

Targeting has a proven ability and amazing potential to generate tremendous returns, especially when combined with the rich, detailed behavioral data available in Web analytics.  As a method for optimizing site content and advertising, targeting technologies that integrate with Web analytics data will only become more important and a necessary “must have” for innovative companies that want to maximize business opportunities on the Internet. 

Alright, I had to have fun with the title. :) We’re about 4 weeks ago from the newest and most unique analytics conference on the scene: X Change, hosted this year by Semphonic and Web Analytics Demystified. 

If you missed the first year in Napa, you gotta head to San Fran this year!  Allow me to explain how X Change differentiates as I see it:

• Conversational. You don’t sit in a room and listen to people drone on in front of their powerpoints.  People sit in Socratic circles and talk about a topic of interest in “huddles.”  The huddle leader will bring up a topic, perhaps riff on some hard-learned experience or data point related to the topic, and ask for commentary from the participants.  The conversation then flows, like Jazz, until there’s a cadence, then the huddle leader phrases a few more notes and progression begins again…  Its atypical format depends on participants for success.  No one is going to sit there and read you slides and provide one-sided opinions.  You won’t just be sitting there listening (unless you want to).  The best huddles are interactive and encourage active participation in the pursuit of shared knowledge, not passive reception of an individual’s knowledge.
• Focused.  The huddle topics are highly specific and deeply relevant to the real world practice of web analytics today - from attribution to mobile measurement to integration to privacy to team structure, the huddle leaders selected topics that interest them to share with the participants. The focused conversational format should lead to symbiotic exchanges of information directly relevant to your job.
• Small.  100 people, 20 huddle leaders.  You get to make meet interesting people and build working relationships with them.  Cool folks like Bob Page, Rachel Scotto, Marshall Sponder, John Lovett, Jared Waxman, “Bob” Dylan Lewis will be leading huddles and hanging out.  The Web Analytics Tuesday event will probably be bigger than the whole X Change conference!
• Exclusive.  The huddle leaders were hand selected.  In attendance will be industry leaders, corporate executives, industry analysts.  All of the attendees work with analytics.  And for gosh sake, it is at the Ritz in one of America’s most beautiful and eccentric cities. 

I think X Change is a unique experience and a worthwhile event where you get to really connect, and well, exchange (!) expertise with your peers and go home with new knowledge.  At least I did last year.  I’ll be leading a couple of huddles, one of the web analytics team and one on knowing when you’ve outgrown you analytics tool, so say hello when you see me. 

Make sure you check out the official web site at Semphonic and sign up today.  The event will sell out soon.  15% discounts are available for Web Analytics Association members. 

The  well-researched answer is “no.”  The AVG LinkScanner Bot appears to prefetch the js and the gif (and pretty much everything else on the page), which for certain tools and their tag configurations generates false page views and visits (and the derivatives thereof), just like it’s “legitimate” traffic. 

If your tag configuration is set up with noscript tags, AVG will fetch the content in the tags, including the gif, which means that:

• The bot may be infesting the data of customers of web analytics vendor who configure page tag-based data collection in this way. 
• The bot may be inflating the data in such products/services offered by various web analytics companies.
• Customers may be paying for server calls generated by this bot.

Vendors, of course, could easily filter the user agent to protect their customers:

Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1;1813) 

But I haven’t heard a peep from any SaaS vendors about excluding the user agent, filtering already collected data, or refunding customers the cost of robotically generated server calls (regardless of AVG). Have you?

Think about this: many SaaS page tag vendors don’t provide detailed visitor-level data and user agent reporting.  That means that their customers have no ability to investigate this bot or detect it by filtering their reported data by the the true user agent.

I’ve been talking about JS executing bots screwing with web data for about a year now.  SEOMoz and the folks at SlickSurface confirmed it quite recently (quoting me no less in their fantastic analysis).  So they do exist…

Now let me tell you a little story.  Once upon a time I was at a conference called eMetrics when the CEO of a company came up to me and said “hey I read your blog about bot detection, and I looked in my web metrics tool for traffic with high page view to visit ratios.”  Then he narrated a story to me about how he found a bunch of traffic that had page view to visit ratios of 5,000 to 1.”  I said “do you use page tags” He said “that’s all my vendor provides, so yeah.”  And I said “you’ve found a javascript executing bot in your data.”  “I know” he said. “Well did you call your vendor and let them know?”  I said.  Now for the punch line:  he told me that the vendor (who shall remain nameless) told him “well, the traffic executed server calls”  And they wouldn’t give him a refund!

It’s worth mentioning that this bot definitely affects log file tools and packet sniffer tools.  Both must be configured to filter the AVG LinkScanner user agent.

Now here’s the rub for me.  I use AVG!!!  But I now find it increasingly difficult to support the company or continue using their products.  Why?  Because they are wearing a “bad hat” here:

• First, they are fully aware of the affect of this bot on web analytics systems. They just don’t seem to care (yet).  UPDATE:  They have set up a Google Group to discuss this issue.  They must understand how companies of all types in all sectors use web analytics data to optimize their sites, set their marketing budgets, determine expected server load, and much more.  What do their Internet Marketers think? 
• Second, the Link Scanner tool may have a short shelf life and may offer limited protection.  Malware creators will easily adjust. Check out what my friend Steve McInerney, a very smart security expert, said on the Web Analytics Association’s Yahoo Forum:

What strikes me about this particular solution by AVG is how
incredibly … stupid it is on several fronts.

1. Noticeably impacting a users bandwidth is, technically, a security
breach in the first place, aka Denial of Service Attack.

2. Some of us live in countries that have rather severe bandwidth
charges/limits and the like, whom shall I send my excess bandwidth
bill to?

…(this) method is fundamentally
flawed. ie malware ignores any first request and only infects on a
second request - alternate cloaking. Whatever. This type of “solution”
only provides weak protection for a strictly limited period of time.

…not just “no security” but bad
security. Because folk feel they are being protected when they are
not, and hence will take greater risks and hence inflict greater harm
on themselves.  

Ignoring the balance of positive to harm that this problem inflicts on
the users who use this product.

• Third, AVG just doesn’t seem to “get it” yet.  They are potentially messing with the ability to drive commerce via data driven decision making, e-commerce analytics, site optimization, and online media measurement!  To quote The Register “chief of research Roger Thompson - who designed the AVG LinkScanner - indicated he may do away with that unique user agent. His chief concern is security, and he doesn’t want webmasters or malware writers gaming his scanner. “In order to detect the really tricky - and by association, the most important - malicious content, we need to look just like a browser driven by a human being,” he argues.

WebMasterWorld has some good stuff about to say here.  Read the Register’s first article here.  And check out the dude’s blog who broke the news first and responses from AVG here and here.

Interesting stuff. So what do you all think? Have you seen evidence of this bot in user agent data from your page tag solutions that use the noscript tag for the image? 

Back from another excellent eMetrics.  I’m a very big fan of the eMetrics Marketing Optimization Summit…  Props go to Jim Sterne for growing this event from a little seed into an incredible, blogworthy blossom.  How involved is Jim in eMetrics?  I’d say he’s completely immersed in every little piece - he even came up to me at the SF WAW (way to go June D!) to find out about the renegade AV work I did in one of the sessions, and to get my take on how it could have been avoided.  He’s that intimately connected to what’s going on.  Macro and micro, micro and macro.  And when you have one of the best Internet Marketers in the world, keeping a tight rein on the Clydesdale of conferences, you know you’re in for one heck of fun ride. 

And so it was for about 500+ of the top web analytics in the beautiful Palace hotel.  Props to consummate conference organizers Matt Finlay and his crew at Rising Media for keeping the road smooth as we all trotted on it as well.  Fanny, you are one helpful polyglot of a marketing manager!  I never knew German keyboards were so wild… Thanks.

The eMetrics sessions were informative and actionable.  The lobby bar and after-hours parties fun and enlightening.  You really can’t ask for more out of a conference.  As I flew home thinking back on it all, there was a lot to blog about, including:

• It’s all about attitude, dude – as in attitudinal data.  Like my father says “it’s all about your attitude.”  And so it is on the Internet in 2008.  From ForeSeeResults, to iPerceptions, to OpinionLab, to CRMMetrix, the often missing link in customer analytics is attitudinal data.  I’m talking here about Voice of Customer (VOC) technology that allows you to ask a question set to site visitors and then apply some sort of algorithm or model to express the meaningfulness of the data in quantifiable terms.  From the American Customer Satisfaction Index to 4Q.  VOC technology enables you to participate in a continuous, automated dialog with your customers in order to identify problem points on your web site and enable you to measure purpose and success of your most valuable segments.  Expect to see some of the big players gobble up these smaller companies.  Omniture, Unica, WebTrends, and CoreMetrics should be thinking about acquisition in this space to round out their offerings.
• Testing, 123… as in multivariate, MVT.  The rage is site optimization technologies beyond the simple A/B, champion challenger, test.  In this category you find folks like SiteSpect (the only non-intrusive multivariate testing solution!).  I’m a big fan of these guys (and was in 2006 long before they ever sponsored a WAW, thanks to a nice demo from Larry at my old job).  Eric Hansen and his crew have specialized software that you install in your data center.  No futzing with damned tags.  Swap out your variations, create different recipes, determine what’s statistically significant in giving you a lift to your macro or micro conversion goal, and you’re off to the races.  The good folks at Google are doing it and doing it well with Google Site Optimizer (thanks for the t-shirts!).  Interwoven is baking in Optimost to the CMS, and Omniture has their Test and Target integrated with the Business Optimization Suite.  Accenture has Memetrics.  Kefta too. And what ever happened to Verster?

In a nutshell, these technologies enable you to test variations of content themes, colors, creative, calls to action, points of resolution, buttons, navigational elements, –whatever you want to call the stuff on the screen—to determine what combination performs best against your goals.  But of course, this is all just software, so don’t get too excited.  The tests are about as good as the people creating them…  And complex tests that take a long time to execute may not finish.  Imagine 1-800-Flowers starting a test in January and not finishing until March, missing Valentine’s Day.  Or Intuit running a test beyond April 15th for a tax product.  Go humbly and carefully into this space, my friends, or you may end up optimizing for everyone and appealing to none.

• Tying it all back to the dollar for profit-generating sites and to the mission of non-profit generating sites…  It seems like a “no, duh” moment but metrics for the sake of metrics can be a big waste of time.  If you can’t tie metrics or visitor actions back to value on a revenue-producing site or to the betterment of a non-profit site’s core mission, then what’s really the point of the measurement…  That’s why I’m a big fan of the stuff ZaaZ does.  They totally get the fact of how actionable metrics turn the wheel of Internet commerce and ad-based models, and they can model it all to prove it out the ROI.  Folks like newly elected WAA Director Alex Langshur’s company Public InSite do similar stuff for content driven sites.  That is they know how to use metrics to optimize the channel to goals, not to just puke confusing data, like most web analytics tools do.  Again, it’s all about the people you hire, not the tools you use… My good friend Avinash, right again!
• The emergence and rise of deeply psychological and neuro-behavioral methods for automating persuasion and conversion.   Anyone who knows my good friend Joseph Carrabis, over at NextStage Evolution, knows that besides being one heck of giant kite flying, music master, he’s also got the models and the patents to help target and respond to human behavior across programmable devices.  We’re already seeing some companies, like Seven Billion Joe’s, er People, taking what he’s been saying for years and going to market with it.  The idea here being that if you can identify the affective, behavior, and motivational drivers of site visitors, you can maximize cognition in elements on the site (like pictures, text, informational flow) to appeal to target segments and persuade/provoke desired behavior.  It’s like a higher rung on the optimization ladder.  It’s not test what they see, it’s figure out how they think, then make the site better because of it.  Cool stuff.  Blows my mind.
• Integrated, multichannel marketing.  Just ask my good friend Akin Arikan, author of the newly released Multichannel Marketing.  (Disclaimer: I was a technical editor on the book.  It’s easy to do when you edit brilliance).  Make sure to check it out!  Marketing in general will become more Internet-centric, but will continue to clutch the roots of broadcast and print.  You will have the database marketer and statistical modelers working with a union of web channel and offline data.  What’s preventing it now?  A unified marketing database.  You see companies like Salford Systems circulating in this space.  And take a look at Unica’s blend of Enterprise Marketing Management…  I’d stay tuned to see what Unica has up their sleeve for bringing together online and offline.  When you can segment and target across online and offline campaigns, if I were pure web channel player only, like Omniture or CoreMetrics, I’d be a bit concerned that people are waking up to open systems, not closed black boxes.  WebTrends is already moving in this direction…  But they all remain far behind Unica when it comes to multichannel marketing.

And that’s just a few of the things the phenomenal eMetrics got me thinking about…  I hope to see you in Washington DC in October! 

Web Analytics Key Performance Indicators (KPI’s) are critical for breaking through the dataglut spewing forth from your web analytics tool.   I mean there’s a just a ton of data in web analytics, and the majority of it tends not to be very useful or applicable for improving your business performance.  While it’s wonderful to have a tool that lets you cut, cross, and slice loads of data every which way but loose, its can be a real challenge to frame the data or put it in context in a way that helps your business optimize the web site.   That’s why I like KPI’s - they identify meaningful, business-focused relationships in your analytics data.  By understanding KPI drivers, setting expectations for KPI performance, and analyzing your KPI’s toward defined goals for those KPI’s, you increase understanding of data, alleviate data confusion, and provide focus for the usage of your web analytics tool.

For those of you who don’t have a KPI strategy or who are just getting into analytics, an easy way to understand a KPI is to consider the example of when you are driving somewhere and trying to get there within a certain period of time.  If your goals is drive 60 miles (kilometers, my European friends) in exactly 60 minutes, you know that you need to drive 60 miles per hour (or KPH).  If you go faster, you will arrive early, if you go slower you won’t meet your goal and will arrive past your deadline.   So as you travel along the road, you measure the KPI of your speed. That’s what is important to measure on your trip.  Of course you may measure other KPI’s like the amount of fuel left or the miles you’ve traveled… those certainly may be KPI’s you measure.  But you definitely don’t need to measure you compression ratio or oil pressure even though it’s available data from your car.  In the same way, when you are looking at web analytics data, you don’t want to track everything, only those things that are important to your business performance toward goals. 

Several activities can assist the creation of KPI’s.  Here are a few of them:

• Determine the Business Strategy.  Why is the company funding and developing an online mission?  What is the strategy?  KPI’s can help you figure out if it’s working.  To find the KPI’s that will help, the web analyst should be asking the question how can web analytics be used to formulate, implement and evaluate cross-functional decisions that will enable an organization to achieve objectives? How will web analytics be used in the process of specifying the organization’s objectives, developing policies and plans to achieve these objectives, and allocating resources to implement the policies and plans to achieve the organization’s objectives?
• Define the Site’s Goals and why the Site Exists.  I covered this in a post a few months ago.  A understanding of why your site exists enables you to effectively use online metrics.  You need to define the purpose of your site in order to create effective KPI’s.  Once you’ve defined your site’s purpose, you are positioned to examine Web data in way that helps you determine whether your site delivers on its purpose — does it exist effectively?   Create your KPI’s, identify goals for your KPI’s, and track your performance against those goals.
• Recognize Value Drivers.  How does the business make money on the site? Monetization, in cases where profitability is important, influences what you should be measuring.  If you run a media site, you probably make money from content consumption (the recency and frequency of content consumption), conversation (social media, such as contributions or comments), and conversion (the rate at which people complete certain value driving actions, like signing up for newsletters, rss feed, webcasts, print subscriptions, or downloading certain content types, like white papers).  So you create goals for and measure KPI performance around those value drivers.
• Map Organizational Roles.  Classify your organization into audiences for your KPI’s based what they do on your web site.  You may create KPI’s around function or action of the actors who receive your KPI reports.  Function defines the group that KPI’s are focused for, such as product development or editorial.  Action defines what those people do on the site to make it successful.  By understanding function and action of key actors on your sites, you gain insight into the type of data needed in KPI’s and the number of different KPI reports you may need to roll out.
• Understand the Customer.  KPI’s purely focused on internal function and actions are important, they need to be customer focused.   If you think measuring conversion is important, while your customers tend to come to your site for informational or non-transactional purposes and then go elsewhere to convert, you may be disconnected from the reality of why your site exists.   Learn customer goals from VOC (voice of customer) data and by examining historic behavioral data of key segments.  Make sure you don’t create KPI’s that are vain or inane.  Instead create KPI’s that help you guide action internally so that your business meets the needs of your customers.

Framing your KPI development around the five bullet points I listed above will help you create KPI’s that assist your team in guiding business performance toward goals - while not forgetting to consider some of the core elements of online business: business strategy, site performance goals, value drivers, the human organization, and the customer. 

Now segment, segment, segment your KPI’s!

Next Sunday afternoon I am moderating a panel at eMetrics San Fran.  The panel is called ”Web Analytics -vs- Audience Measurement.”  Andrea Hadley at NetSetGo was the brainchild of this panel idea (and yes that is her picture on her site :).  In fact, I was a panelist on the same panel at eMetrics Toronto, filling in for my friend Marshall Sponder.  Since he’s going to be in San Fran, I yielded my seat 0n the panel and decided to stand up at the podium.   Other panelists include Jodi McDermott, Director of Product Management, at ClearSpring, and some other surprise guests (from comScore and IAB maybe)… You’ll have to show up and find out…

The panel description is as follows:

Are you confused about the number of customers visiting your website? Are the metrics reported by your web analytics tool different from the metrics reported by your online media, or by audience measurement organizations? The WAA invites eMetrics Marketing Optimization Summit attendees and the local San Francisco business community of web marketers, publishers and agencies to attend this community meeting. A panel of experts will discuss the value of the metrics, methods and tools used by web analytics practitioners, online advertising media and audience measurement organizations. Find out how-to use these metrics and tools to better understand your customers, your website’s competitive standing and overall website value.

The goals for this panel include:

• Adding clarity around the tools and data associated with each set of technology and metrics - web analytics technologies and website data, ad servers and ad data, and audience measurement tools and data.
• Learning how each data source can be used to expand our understanding of customers, how effective our website is as a business channel, the website’s competitive standing and value, and so on.
• Providing insight into the role of the web analytics practitioner and how this role is growing in importance and influence over business, marketing, product, and strategic decisions.
• Discussing the role of the Web Analytics Association (WAA) and how the WAA serves the practitioner.  That the WAA is an unbiased organization that doesn’t serve advertisers, publishers, or technology vendors, rather that the WAA serves and exists for the benefit and betterment of the the practitioner and the web marketer/strategist.
• Articulating the announcement made at eMetrics Toronto on the important collaboration between the IAB and the WAA for standards review.

My goal as the moderator is not to critique, demean, or criticize audience measurement, Internet advertising technologies, or to embellish or hype up web analytics tools.  Rather I hope to clarify the differences between the technologies and speak about the value they hold together - like I did in my article for MediaPost called the Yin and Yang of Online Metrics.

So why am I telling you all of this on my blog???  Well it’s because I really want your help, whether you are going to eMetrics or not…  Since I’m the moderator, I get to ask the questions, and I don’t want to just ask “my” questions, I want to know what questions YOU would ask if you had the chance to ask.  Of course, those of you reading this and attending the panel will be given the microphone if you raise your hand.

Please help my crowdsource by telling me in comments or via email to judah (at) webanalyticsdemystified.com:

What questions would you ask to clarify the differences and value between web analytics and audience measurement tools?

Any questions you think worth asking from “why don’t the numbers match?” to complexly “what are the differences between audience measurement and web analytics systems in terms of data collection?” would be awesome and appreciated.  Thanks in advance for your help!  I’m eager to see if this social media experiment in blog-based crowdsourcing actually works!

Wow!  It’s been a few weeks since I’ve had any time to blogviate. 

What other things do web analysts do?  Besides blog and do WAA stuff… And ensure tool configuration/administration, date collection, data verification/validation, reporting, KPI generation, conversion optimization, deep site analysis, stakeholder guidance, outcomes evaluation and so on… Well the fun answer is “it depends” on a things like your boss, the organization you work and the holy org chart, your recognized skill set, and what you want to do.   But as I talk to my colleagues in the industry, I’ve noticed some web analysts do a lot of different things.  Here’s a few beyond the norms (or in some case maybe part of the norm, but not often discussed):

• Write business requirements.  You may be writing biz reqs for the extension and maintenance of your own tool, or you may be asked to participate in the definition of the metrics strategy for product or site features.  The analyst may define the attributes, capability, and characteristics that are necessary to accomplish given business objectives.  Generally these biz reqs will be functional (the system must do this in this way and look like this) and not technical (but every so often you may need to justify why you keep saying “ah, page tags, not logs” or vice-versa or packet sniffers or hybrid).  Fun!  And time consuming! 

• Participate in product development and usability discussions.  A rich topic here for sure.  As web analysis sort of fractures into those who study how the site routes visitors, navigational elements, information architecture, and into those who prepare AB and MV tests and report the results, it’s not uncommon for analysts to be called into to determine what should go where and what functionality should or should not exist on the site in order to drive business or conversion goals.

• Contribute to the keyword set.  As I explained in my last post, web analytics is morphing into multichannel analytics.  Analysts are increasing leveraged to participate in and analyze the outcomes of SEO and SEM.  Based on keyword data, I have a few friends who spend a ton of time selecting and managing the keyword portfolio and even the bids! 

• Have a say in “strategy”.  Analysis informs tactical decision making, which is guided by strategy (and analysis and decision making and strategy again).  When fully leveraged, a web analyst has much to offer the strategic decision making process.  Think about something as simple as using referrers to establish content syndication and affiliate partnerships…  Cool.

• Guide the content agenda.  For those who work in what my buddy, Alex Langshur (who runs a boutique consultancy in the public sector), calls “content-rich” and “mission driven” sites, the web analytics tool has utility as an editorial or content research tool.  From understanding what keywords/phrases are driving traffic to determining whether the editorial plan is actually mapped to the information demands of site visitors, web analysts can have a lot to say, if asked.  But be weary, the last thing an editor wants is some hot shot web jockey telling them what to write. That’s not what I’m saying to do, rather, some analysts work with content and editorial teams to ensure frequently demanded content topics are rounded out on the site, expanded on/developed, put on the content plan, or simply just known about, so the content folks can do what they do… 

• Code. Yeah, some of us know how to do it, and many of us just don’t tell anybody.  Because “that’s not what I want to do anymore” as my friend who works at a local agency told me the other night.  My personal opinion is that code is better left to the coders, but any web analyst who can throw down with web development and talk about things like X-Forwarded From headers will only make themselves more valuable to the organization.  Then again, some analysts would rather analyze data than futz around with overly esoteric tags and variables and the plumbing of web pages.  Then again some of us love that.

• Direct IT.  Those of us fortunate enough to have control over our web analytics technology already know they’ll be spending perhaps inordinate amounts of time with our good buddies in IT.  They may be the audience for your business requirements, or you just may need to connect with them to ensure your technology is factored into the larger plan for next generation integrated, service oriented architectures.

• Due diligence on acquisitions.   A fun one for you MBA’ers is when you get drafted into the acquisition or merger process, having to examine the target’s web traffic.  You gain real insight into the core of their web business, and may even find things, I’ve heard, like page view inflation from not filtering bots on including things like favicon.ico to inflate page views.  Heh!

And more!  So yeah, it’s not all about spending all day just thinking about who comes to the site, why, what do they do, and do they complete their purpose according to specific goals.  While that is all a big and important part of it, the role of web analyst can go far beyond tradition, if you are capable and you work for the right business that lets you excel!

Hello good readers!  Every month I write a column for MediaPost’s Metrics Insider.  Here’s my most recent one:

Companies that derive revenue from multiple channels often have two analyst teams: the “database marketing team” and the “Web analysis team.”  These groups tend not to communicate.  In some companies, however, these teams are merging to form the “multichannel analytics team.”  This specialized team analyzes, reports, and evaluates both Web data and offline data — often in coordination with the “business intelligence team.”  The emergence of this new team structure makes sense for companies that are shifting their offline business models to become more online-centric, and thus want to understand value-generating connections among channels. 

Several macro-level catalysts are necessitating the shift to a multichannel approach to data collection and analysis.  The ongoing mainstreaming of the Internet channel for enabling commerce, conversation, and relationship marketing is certainly pushing this movement.  The burgeoning set of analytics tools that integrate with other technologies to enable event detection and trigger a customer-specific response is also promoting change in the way companies think about connecting offline and online data to improve overall business performance.

If database marketers and Web analysts are evolving into a new type of team, then what roles are necessary on this new multichannel team?  Here are a few:

• Web Analyst.  The overall Web analytics professional has a deep understanding of the Web channel.  This person uses a Web analytics tool to understand the performance of site traffic, online marketing campaigns, and to segment Web data in order to understand how visitors referred from certain channels navigate (or don’t) through the site.  They understand, measure, and report whether the site is fulfilling its purpose for conversion, task completion, and other KPIs when compared to business goals.  
• Site Optimizer.  A niche type of Web analytics professional, the site optimizer is in charge of determining the right approach for configuring and reporting the results for AB (champion/challenger) and multivariate tests.  This person is all about testing components of site and page design to yield the best combination of elements that provides a lift in a particular metric against a goal, such as conversion rate.  Content targeting may also fall under this person.
• Social Metrician.  Another niche type of Web analytics professional, the social media measurer is concerned about the performance of customer touchpoints outside of the main Web site.  He or she collects, monitors, and analyzes data related to things that happen “out there, on the Internet,” such as syndicated video, mobile, widgets, blogs, social networks, and other social media.
• Database Marketer.  The traditional offline analyst and database miner.  This role analyzes data from channels that are not online but may reference and promote online interaction, such as television, radio, print, catalogs, and direct mail.  Of course, these analytics skills can be applied to online data as well!
• Search Analyst.  The analytics professional in charge of keyword identification/selection, keyword management, bidding, and analyzing the outcomes of search.  He or she may be in charge of analyzing site performance against known SEO goals too, not just SEM.
• Market Researcher.  The traditional market researcher gathers, analyzes, and reports data about the overall market, key competitors, and customers. 
• Qualitative Analyst.  Part market researcher and part analyst, this individual is in charge of online customer and visitor surveying, relating customer feedback and visitor opinions to the context of on-site behavior to help deduce “why” people did something on your site.
• Ad Analyst.  Solely dedicated to assessing the performance of advertising campaigns, the ad analyst assesses and educates clients on ad campaign performance both online and offline.
• Audience Measurer.  The wielder of an audience measurement tool informs competitive decisions, influences media plans, and provides benchmarking and competitive data to give context to other data analysis activities, such as keyword bidding or media buying. 

How would these professionals all work together?  The market researcher’s data is used to help craft a customer-focused and competitively differentiated campaign strategy.  The audience measurer provides data that focuses the strategy on the right online demographics and sites, while the database marketer mines historic data to figure out the best-performing offline tactics for the identified demographics. 

Let’s say a mix of search, social media, and online and offline display ads are selected as part of the campaign.  The search analyst concentrates on SEO/SEM, while the ad analyst tracks the performance of display ads.  The social metrician examines the social media ecosystem’s response to the campaign.  The Web analyst analyzes how campaign-referred visitors behave and navigate through the site, taking into account the context of the qualitative analyst’s voice-of-customer data.  Meanwhile, the site optimizer tests landing pages and funnels to ensure they effectively convert visitors and fulfill business goals. 

For many companies, it would be unrealistic and perhaps impossible to find and hire people to fill each of the roles I’ve presented above.  In fact, in most companies these roles and activities are completed by only a few people, if at all.  An option for companies that seek to expand or combine teams is to look at consultants, contract workers, and full-time equivalents allocated across multiple people.

That said, companies that are unable to bridge together online and offline analytics teams will miss important data points.  In the digital future, we’ll see different types of analytics professionals working together across channels to yield profitable insights that support campaign and business goals.

The infoglut in web analytics is enormous.  So much data.  Companies report that 69% of all people who consume the data don’t understand it.  How does a business go about making sense of it all?  Formulating a comprehensive KPI (Key Performance Indicator) strategy is a big part of differentiating signal from noise and directing appropriate tool usage.  We’ve all heard about KPI’s before.  They are ratios or derivatives of metrics that pinpoint critical, business relevant web performance.   My good friend, Eric, even wrote a book (a BIG one) about it. 

The process of moving an organization through KPI Change Management starts with a well formulated plan for doing so.  Here are some tips for formulating your KPI plan: 

• Educate senior management and get managerial buy-in.  Education and buy-in can take shape via a number of methods.  Maybe you publish and circulate an internal-only white paper about the importance of KPI’s measurement.  Maybe you leave Eric’s book on the chair of your C-level executives.  Perhaps you hold a meeting and present the web site optimization process and how measurement via KPI’s provides the foundational informational on which to make site optimization decisions.  Perhaps you take your boss out to lunch and explain that basic reporting and tool access is helpful, but “Web analytics is hard” and that KPI’s give context to the data to staff that’s otherwise somewhat confused about what they pull for the tool.  You explain that KPI’s provide a focal point for centering analysis around business goals.  Whatever the method, the goal is managerial approval that “yes, you can do KPI’s.”
• Determine the audience for the KPI’s and train them.The importance of KPI’s will vary by stakeholder, and your KPI strategy needs to take that into account. Different segments of stakeholders will be interested in specific KPI’s, and you must accommodate that need.  As an analyst, you should identify the functional roles and job responsibilities of the people who are going to receive KPI reports.   Everyone may not be the right choice (though it could be), and it may make sense to concentrate a KPI rollout on the needs of the few or it may make sense to “go broad.”  Follow up with comprehensive training about your KPI project and how KPI’s can most effectively be used.
• Start with simple, well-qualified, highly relevant KPI’s.  While some folks with want to throw a “kitchen sink” strategy at KPI’s.  That’s a mistake.  If you report more than 5 to 10 KPI’s (imho) per stakeholding group you may end up with a set of unworkable, confusing, and neglected reports.  It’s better to report just a few, well qualified, highly relevant KPI’s.  How do you qualify them? By mapping KPI’s to important business objectives.  How do you know they are highly-relevant? Because you’ve compelled management to buy-in and to agree that they are critical indicators of site success. 
• Elicit the business goals for the KPI’s, compare KPI’s to goals, and report associated variances (i.e. deviations). Make sure you have determined business performance goals for KPI’s.  Goals give context for performance. It’s that simple.  Without goals, you have no context for determining what’s good and what’s bad.  If your conversion rate KPI is 5%.  Great!  So what though?  If you know your goal is 3%.  Awesome job.  If you know your goal is 10%.  Stop reading now, and get back to work - you have much work cut out for you. 
• Identify the frequency and format for reporting.  You need to determine a frequency that is timely and sustainable, and the format in which you present KPI reports needs to common enough that people can easily examine the data. Perhaps you deliver the reporting in Excel, make it available directly in your tool, use Xcellius, or create reports using a BI tool. 
• Automate the delivery of the reporting.Without automation, you may put on the Report Monkey suit and enter Excel hell.  Critical to the successful rollout of any KPI reporting is an automation plan.  Do you email reports, put them in a shared directory, create a set of reports in the tool and provide access, or deliver them in weekly presentations?  The best choice is the option that gets people to use them, listen, and understand what you are trying to do with KPI’s.
• Following the reporting up with analysis and guidance.  Depending on the size and scale or your organization and the resources you have to work with, it may not be possible to provide every stakeholder with detailed analysis.  But you need to do your best to follow up KPI reporting with true analysis and guidance.  Why are KPI’s going up or down?  What are the drivers of the changes? 
• Segment, segment, segment. Site level KPI’s are helpful in understanding overall audience and customer behavior, but they hide important details.  When you slice a KPI by a specific segment, you will realize insights that help you conclude what action to take next.  Overall site repeat visit rate is 37%, but the repeat visit rate for customers who use your “product lookup tool” is 96%.  What does that data indicate about how you market the site, or about why people are coming to the site? 
• Test, test, test.  As you measure > report > analyze > guide based on KPI’s you will undoubtedly determine actions to take on the site.  You should be testing the hypothesis behind these actions via controlled experimentation.   

There’s obviously a lot more to talk about here - from what constitutes a good KPI, to what types of KPI’s different stakeholders should examine, to what are the best KPI’s for particular site types and more.  I guess there’s more blog posts for that, but in the meantime I hope you’ve found this blogviation useful.  Let me know if you have any thoughts to share.

eMetrics Toronto is about two weeks away, and Boston Web Analytics Wednesday is tomorrow night.   I’m pretty excited for both events.  

I think eMetrics is thee premier web analytics and marketing optimization conference.  I’ve been to a bunch of them, and I always walk away with new ideas with which I can hit the ground running when I get back to work.   The real world case studies, practitioner advice, vendor spiels, and the cadre of notable analytics and marketing professionals who attend and make themselves available to you, the attendee, is unmatched.  

Web analytics pals Jim Sterne (and Andrea Hadley in Toronto) in association with Rising Media ensure the content and tracks focus on the knowledge needed today to drive the real-world application and usage of analytics and marketing measurement technologies in way that enables your online competitive advantage tomorrow.  eMetrics is far beyond a beginners conference (though there’s always plenty of good stuff for beginners).  Gone are the days talking about simple definitions and whose tool can do what (though they’ll be plenty of that stuff covered in some sessions, at lunch, in the bar).   Today’s eMetrics is focused on the application of analytics in business context, especially in the context of marketing.  The conference, as I see it, is about what you should measure and how to take action from what you measure in order to improve business performance and increase top-line revenue and bottom line profits (while reducing middle-line expenses).

I’ll be there in two sessions.  The first session I’m in is on Monday afternoon and occurs in two parts.  The first part is where I’ll fill in for my buddy Marshall Sponder, Director of the WAA and Chair of the Social Media Committee, and give an update on Social Media Committee activities.  During the second part of session, I’ll participate on a panel moderated by Chris Williams, Managing Director, Media Contacts Canada, and panelists Brent Bernie, President, comScore Inc., Paula Gignac, President, IAB Canada, and Jodi McDermott, Director, Product Management Clearspring Technologies.  We’ll be talking about the importance of standards, collaboration between industry organizations, and the real-world application of all the measurement tools you can use to run an online business (and more).

In the second session, on Wednesday afternoon, I’ll be on another panel speaking about the analysis of audience behavior and engagement levels on media and content sites.  Sitting alongside me will be moderator Mitch Joel, President, Twist Image, Sibel Satiroglu, Interactive Marketing, Hewlett Packard, and Mike Sukmanowsky, Web Analytics Specialist, Rogers Media. 

Should be some good conversation.

For those people trying to gain insights from the data, to those actively working on taking action from the the data, and for those who are trying to manage it all, I highly recommend attending one of 2008’s eMetrics Summits.  If you’re in Canada or nearby or really anywhere on Earth, now’s the time to sign up for Toronto.   

And for those in the Boston area tomorrow night (3/19), please join me at the monthly Web Analytics Wednesday I host.  This month, Jonathan Mendez, Founder of RAMP Digital, will be presenting on the “Crawl, Walk, Run” approach to onsite targeting.   Omniture is sponsoring and providing free food and drinks for all attendees, so swing by and swing back a drink whilst enjoying some smart conversation.

See you at both events.