Reach and frequency and the core concepts of traditional media planning and advertising.  For a given site, program, channel, radio station, billboard, newspaper section, a target audience (the reach) is exposed to a certain number of occurrences of the media (the frequency).  On the web, these concepts manifest themselves in metrics collected and reported from a number of recognizable services.  Audience measurement firms, like comScore and Nielsen, web analytics firms, like Omniture and Unica, to companies somewhere in between, like Quantcast and Google, all have reach and frequency data.  Many new media metrics can be used to proxy frequency- from time-based measures, espoused by audience measurement firms, to concepts like visitor retention or the repeat visitor rate cited by web analytics firms.  On the reach side, companies refer to concepts like “unique visitors.”

These data, of course, available in free tools or in for pay tools are certainly helpful for planning campaigns.  But reach measures can be dirty (cookies, unduplicated unique users, estimates from panels, coverage error).  Frequency measures can be just as dirty (problems recording time in single page visits or visits on the last page, do page views really matter with AJAX and rich media, cookies again, and so on).  We all are aware of the challenges.

Thus using basic reach and frequency measures for planning or evaluating a campaign does not suffice.   So advertisers and agencies target demographics, like gender, age, income, education, and job title.  It’s a given that advertising in the Robb Report reaches a different audience segment than advertising in Popular Mechanics. 

These brave new days we have “behavioral” tracking too.  By taking into account visitor activity across sessions, such as past actions taken on a site or a roster of previous purchases, we can attempt to deduce what a person or segment responds to or is interested in based on their behavior.

Even with reach, frequency, demographics, and behavioral data to help guide advertising and media buying, we are missing an important attribute for maximizing the potential success of our campaigns.  We do not have an available tool, whether free or paid, for advertising or buying media on or across sites according to measures of past performance.  Such measures include ad clickthrough rates, conversion rates, goal completion rates, delivered impressions, and perhaps even harder to quantify financial measures such as ROI, ROAS, and ROMI.

Sure, historic, tacit knowledge of campaign performance exists and is used by agencies or publishers.  However, there is no shared industry source that can help us answer “how has a site for display advertisement historically performed toward goals based on the reach, frequency, demographic and behavior of its audience segments?”  Interestingly, a company minting money right now, named Google, can masterfully demonstrate performance in paid search campaigning and help advertisers unify it with segmented reach, frequency, and demographics.

Outcomes based performance measurement unified with reach, frequency, demographics, and behavior is what is missing in audience measurement tools, not frequently reported externally by web analytics tools or ad serving tools, and not available in ad planning tools.  When advertisers can target display ads, or even video ads, to desired audience segments by reach, frequency, demographics, behavior in the context of known performance, media planning will be more effective.  

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. 

We have modified the Search-Shield component of the product to
only notify users of malicious sites.Search-Shield no longer
scans each search result online for new exploits, which was
causing the spikes that web masters addressed with us. However,
it is important to note that AVG still offers full protection
against potential exploits through the Active Surf-Shield
component of our product, which checks every page for malicious
content as it is visited, but before it is opened.

As you’ve just read in the quote above, AVG has stopped scanning each page that returns in a SERP for users of their free tool.  Instead pages will be scanned by proxy after a user clicks on the link. 

For paid users, it’s a little different.  SERP’s will still be scanned but via a pure database approach (not the DDOS approach :), which means the sites listed in SERP’s will be compared to a black list of known “bad” sites.  The blacklist is based on internal AVG research and from the real-time results reported by users who have opted-into AVG’s “prevalence reporting system” (a feature of AVG 8).  This means AVG is still scanning sites, but on a very limited basis, thus the detrimental effects on analytics should be very minimal and only caused by users who participate in prevelance reporting.  Still some data pollution will occur…  

AVG hasn’t confirmed that they’ve released a fix to the “noscript” issue I mentioned.  I do know they are working on it and have fixed the problem in internal builds.  Regardless, if the LinkScanner is working in the way they say it is, the problem will be negligible (but some data pollution will still occur ;).

Kudos to AVG Corporate, Roger Thompson, Pat Bitton, Greg Mosher, and all the other engineers who listened to the community on the web and worked quickly to fix the problem.  Now let’s hope the the build 138 update works as described. Time will tell.

Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)

In addition to the easily detectable user agents:

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

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

User Agent:Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)

This news is not good.  If you filter SV1 agent, you risk filtering legitimate traffic from the IE6 browser.  A few folks have commented to me that one should filter the user agent anyway, because 1) IE6 is in decline and 2) most IE6 users have .NET installed, which will show in the user agent.  Still filtering it makes me a little uneasy.

Is this the death toll for log file analysis and services provided by ABCe (since they can’t filter this user agent either)?  Maybe it is.  AVG is touting that agent lacks HTTP Accept-Encoding, which is just dandy, but that information isn’t normally captured in logs.

So the current situation is this:

1. AVG has two user agents.  Both are filterable, but the SV1 agent is problematic to filter because you risk filtering legitimate traffic.
2. Both agents in the current version request gifs in noscript tags, inflating counts in page tag implementations with noscript configurations.  AVG claims they will fix this issue.
3. The bot uses”mad” bandwidth.  I’ve heard stories of bandwidth increasing 100x normal levels.  Some webmasters are serving dummy files to the recognizable user agents, some aren’t serving content to IE 6 browsers (crazy), and some are redirecting the bot back to AVG (thus inflating AVG’s bandwidth, LOL!).
4. Evidence points to this bot NOT inflating clicks from paid search (i.e. PPC) and thus NOT committing click fraud.   But it doesn’t remain out of the realm of possibility that the scanner may be accessing an ad vendor click redirector and causing a click.  Not trying to spread FUD here, just making a point. 
5. AVG is looking at option of checking either an external db (hosted by AVG) or a local cache to verify sites in SERP’s have been “scanned by AVG,” instead of repeatedly scanning sites every time they are listed in SERP, to reduce the bandwidth issue and minimize fraudulent entries in log files.
6. AVG is thinking about enabling white listing of sites, so they are skipped by the scanner.
7. AVG is thinking about exposing a meta-tag that instructs the scanner to ignore the site.

Good luck with this nasty bot!  Interestingly, here’s how you smurf a site with the AVG LinkScanner. 

So why is the AVG user agent showing up in that data collected from certain page tag configurations?  The AVG LinkScanner currently requests gifs in noscript tags!

A best practice in web analytic’s page tag configuration is to use the noscript tag to serve the gif to non-javascript executing browsers.  Here’s some commonly seen (obscured) code for doing that:

<noscript>
<div><img alt=”foo” id=”bar” width=”1″ height=”1″ src=”http://
foo.bar.com/xyzab57yw10000s1s8g0boozt_9t1x/foo.gif?baruri=/
nojavascript&xy.js=No&xy.tv=1.2.3″ mce_src=”http://
foo.bar.com/xyzab57yw10000s1s8g0boozt_9t1x/foo.gif?baruri=/
nojavascript&xy.js=No&xy.tv=1.2.3″div>
</noscript>

<NOSCRIPT>
<IMG
src=”//foo.bar.com/xyz.gif?Log=1&URL=/javascript_disabled” mce_src=”//foo.bar.com/xyz.gif?Log=1&URL=/javascript_disabled”
BORDER=”0″ WIDTH=”1″ HEIGHT=”1″ />
</NOSCRIPT>

<noscript>
<img src=http://pt.foobar.com/images/xyz.gif?js=0” height=”1″
width=”1″
border=”0″ hspace=”0″ vspace=”0″ alt=”"> 

Thus, if you are using noscript tags in your page tag *and* someone with the AVG Linkscanner views a SERP (search engine results page)  from Google/Yahoo/MSN that lists your site, the traffic from the LinkScanner will be counted. 

Of course the simple solution to fix this problem is to exclude the user agent: 

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

If don’t have full control over your page tag based web analytics implementation (i.e. hosted), you need to verify that your vendor has excluded this agent.   And you should have them audit your data going back to April, and refund/credit you any money.  Good luck with that though!

How big is the problem?  Well, it depends!

The amount of AVG traffic will vary dramatically by site.  Your site must show up in the SERP’s on computers of visitors that have AVG LinkScanner installed, and you must be using noscript tags to serve the gif.

I’ve made AVG aware of this issue.  And frankly, they’ve been a fantastic company to work with, so I’m sticking with them (for now ;).  First they allowed me to join a private Google group to discuss my findings, both the Head of Global Communications and Chief Research Officer quickly responded to all my emails (good social media response), and their engineers are looking into this issue so that they can fix it…  That’s pretty impressive and quick response.  So cheers to them!

It’s worth mentioning that the LinkScanner isn’t _supposed_ to request images, so I do think this issue will get fixed.

Only time will tell whether or not AVG obfuscates the user agent so it looks just like a “normal” browser.  Let’s hope not! 

What I do find interesting is that I’m already hearing that an agent exists with the string (Mozillia/4.0 (compatible; MSIE 6.0; Windows NT 5.1;1813). Note the “ia” mispelling of Mozilla as incorrectly documented here.  And it accepts cookies.  So AVG’s agent is already being spoofed.  Not good, not good.

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? 

Nedstat, CoreMetrics, and Omniture offer capabilities mixed into their current offerings.  Nedstat even carves out some mobile specific reporting.  You can gain some insight into mobile activity from companies that enable log file processing, like Unica and WebTrends, but be prepared to configure a bunch of filters to isolate the data.

Lesser known companies pushing mobile offerings include: Amethon, Mobilytics, Bango, TigTags, Xiti, and AdMob.  Some of these mobile players are even offering capabilities where they cross-sell analytics as an integrated part of their ad networks, content delivery  and transactional processing systems, marketing and barcoding services, and even as infrastructure or network appliances.

On the audience measurement side, we’ve seen comScore acquire M:Metrics, which was no surprise to me.

On the multivariate testing side, we see my friends at SiteSpect offering mobile MVT testing capabilities. 

And I’ll bet we see Google get into this space within the next 6 months…  I’d even wager an announcement at eMetrics DC…

From what I can gather, when we’re talking about “mobile analytics” we’re talking about “mobile browser” activity across a variety of handsets, not everything that happens on the device. 

Measurement issues in this area include:

• Data Collection.  As many of you know, not all mobile browsers will execute javascript.  They cached the imagesThus, vendors offer us choices.  Folks like Mobilytics and Bango use an image-based data collection method, while Amethon offers a packet sniffer (they call it wireline detection), and we even have Omniture and Coremetrics talking about “no tag” implementations - what my good friend Phil Kemelor mentioned on his CMS Watch blog (”To compensate, you need to stuff the image tag with query strings that will collect the data you require for reporting.”)  Then we have Unica and WebTrends with log files.  Interestingly, packet sniffing has some advantages here because some devices pass unique id’s (such as the phone number) in the HTTP header or other unique id’s.
• Unique visitor identification due to lack of cookie support and IP addresses changing.  IP addresses change, I’m told, as they switch from tower to tower.   In addition many mobile devices will take the IP address of the gateway, making all the devices look the same “person.”  I’ve certainly seen evidence of the host changing pretty quickly during a mobile session. Compounding the difficulty in assessing “uniqueness” is that not all mobile devices support cookies.  In web analytics, cookies are used to define uniqueness.  The fallback method when you can’t use a cookie is IP address/user agent.  If you can’t set cookies and the IP address and user agents are the same, how do you identify uniqueness?   However, when you can detect a unique value in the header, you can easily detect uniqueness.
• Handset capability detection.  Does the device support WAP pushing, streaming video, ringtones, downloading video clips, and so on?
• Phone and Manufacturer identification.  Database from WURFL and DeviceAtlas can be used to identify phone and manufacturer device attributes.  Larger vendors are further behind on integrating this data into their current offerings, whereas the smaller niche players are making use of it. 
• Screen resolution detection.  The Mobile Marketing Association’s (MMA) standards for the four “standard” screen sizes may carry enough weight to push this disdained piece of metrics trivia available from javascript based tagging in web analytics into a brighter spotlight.
• Traffic source detection.  Capabilities for traffic sources seem rudimentary.  I don’t just want to know about search and direct entry.  But I want detection of sources from my marketing and advertising campaigns, rss feeds, and email newsletters, if mobile visitors are coming in from those channels.   Interestingly, Bango solves the campaign tracking issue by pushing you to a Bango-specific URL.
• Geographic identification.  Where are the visitors viewing your site coming from?  And what does the mobile audience environment “look like” in each country.  From this information you can extrapolate country-specifics for site optimization.  But not all devices enable geographic detection because the gateway’s IP address is used or the IP address from the network is used, not a GPS signal.
• No standards.  There are few, if any, commonly supported mobile standards and no web data standards, so the problem is no standards for the devices and no standards for the tools.  There are no standards.  Did I mention that there are no standards. 

So I was thinking, what would I want to see in a mobile analytics solution?  Allow me to riff here.

• Dashboards for KPI and specific-metric reporting.  Views, visits, visitors, referrers, popular pages, traffic sources, resolutions, geography, time-based reporting and custom defined KPI’s….
• Support for multiple data collection methods.  Logs, no-js image tags , and packet sniffers.  Let me pick what I need for whatever application fits my goals.
• Support for mobile-specific constructs not present in historic web analytics data.  Manufacturers, operators, handsets, and device capabilities.
• Advertising-based reports.  CTR, CPM, eCPM, that stuff…
• Tracking for mobile downloads, installed applications, SMS, and MMS.  Seems like a no-brainer.
• API’s.  Closed systems are dead ends for integrated marketing, so give me an API or enable pre-built integrations with other systems, like CRM.
• Segmentation.  By country, by device, by network, by manufacturer, and so on.  It’s necessary.
• Repeat or return visitor identification.  Simple measures of recency and frequency, core to media buying and planning and to site optimization, should be a data point available in mobile analytics.
• Conversion and goal metrics.  Do visitors on mobile devices convert better, worse, the same?  Do they reach site goals?  Without tying performance data  and outcomes to mobile visitor activity, I’m left wondering…
• Value scoring for engagement or proxy scoring for revenue and ROI analysis.  I want to be able to score attributes or actions to approximate an engagement score or to identify value or indicate revenue. 
• Non-human traffic and web-browser based detection and reporting.  Mobile pages are full of links.  The ads are links.  Mobile vendors must support detecting, filtering, and reporting, non human and web-based agents from pure mobile agents - otherwise the mobile data gets muddled and skewed.
• Data Export.  Must be able to export reports to Excel or Word, and email them.

So there’s a quick blogviation on Mobile.  Am I right, wrong, what did I miss?  Let me know…

So it’s a good question certainly valid to ask.  The answers are even fairly easy to understand, but the root causes are often difficult to pinpoint and even harder, if possible at all, to remedy.  The fact of the matter is that data discrepancies in analytics result for a multitude of reasons, such as:

• Different data collection methods.  We have a bunch of tools and services that collect web data using various, non-standardized, proprietary data collection methods.  Ad servers use javascript page tags.  Many web analytics tools use page tags too, but it’s not uncommon in web analytics to use additional methods, such as log files or packet sniffers.  Or perhaps a combination of these methods, called hybrid data collection.  And all the tools have different algorithms for processing the data collected.

On the audience measurement side, data is collected from self-selecting panels who install proprietary software (i.e. toolbars and so on) on their computers, perhaps at work or at their university, but most likely at home.  Then, the collected data from different panels is rolled-up and combined, and the limited subset of the Internet population that chooses to be monitored, in exchange for some incentive, is inflated and projected to the entire Internet audience using proprietary statistical methods.  We also have data collected from a limited set of geographically specific ISP’s.  And regardless of whether we’re talking about audience measurement or web analytics, the different data collection methods often, but not always, involve cookies and all their inherent issues of cookie deletion.  

• Unique data models.  Ad servers aren’t focused on counting page views and the other dimension of web analytics (visits, time, and so on).  Rather ad servers focus on serving and counting impressions served (and loads of related derivative calculations, like CTR, CPC, and view–thru).  Metrics are based on an ad request and an ad code.  Ads may or may not be targeted to a page, and instead to various constructs, like a “zone” or “keyword.”  What that means is that the “page” dimension may not even exist in your ad server’s data model.  In other words, you aren’t looking at impressions measured on a page, but rather at the number of impressions served in a different conceptual construct.  That’s one of the reasons why people say metrics and ad-serving systems “don’t measure the same thing.”
• Untagged pages.  Specific to technologies that collect data or serve ads using javascript page tags, there are challenges to ensuring and verifying complete coverage of page tags across every page on a site.  When the pages aren’t all tagged with the different tags for the assorted technologies, guess what?  The numbers won’t come close to falling within tolerable variances.  And questions and skepticism will ensue.
• Non-JS executing clients and ad blocking software.  Let’s imagine for the moment, your site is perfectly tagged for all technologies, so the numbers between your ad server will be close to your web analytics system, right?  Nope, regardless of data model issues, not all browsers execute javascript and many Firefox users have installed Ad Block Plus. 
• Cookie issues.  When you’re counting based on cookies, third-party cookies get blocked (often by privacy software).  Many ad servers and web analytics tools still serve third party cookies, and many corporations have not tricked out their DNS to accommodate this issue.  And we all know how cookie deletion affects unique visitor counts, even if you use first-party cookies.
• Many other issues.  Latency from visitors moving off the page prior to the tag executing to latency in the call to pick up an ad from a third party while your ad server counts the traffic (so your ad count differs from the agency’s count), to refresh rates making it hard to correlate page views and impressions, to no rich media installed and no fallback, to robotic traffic not being filtered from logs or tags, to certain types of user agents (such as mobile devices) not executing javascript… there’s a whole host of other factors that cause data discrepancies.

And of course, there’s always the nebulous issue around the complete lack of consensus-based, enforceable standards for online measurement.  No industry organization can say what vendors or companies “must” do, only what they “should” do… And no industry body is going to get successful companies to change their secret sauce just because they said so…

So what’s a practitioner to do?  Understand the potential sources of discrepancies.  Work with your team (from IT to vendors) to prevent and minimize the root causes when possible.  Educate your team when discrepancies are not remediable.  Ensure you use the different sources of metrics judiciously in the context of your business goals.  Finally, realize that none of the tools are more “correct” than any other.  All of our analytics tools serve different, and sometimes overlapping, business purposes - from counting ads, to influencing media buying, to sizing audiences, to measuring business performance, and to optimizing the site.

First, let me digress, packet sniffing isn’t new to web analytics.  From Accrue to Omniture (Visual Discover Sensor?) to AuriQ to Metronome Labs.  Packet sniffers are used to “do web analytics.”  It’s an uncommon method when compared to javascript page tags.

Web analytics packet sniffers are used to write logs for sessionization (and thus measure) the traffic on behalf of site owners (who don’t want to use tags or logs).  Once you’ve logged and sessionized you know what content people have looked at or downloaded on your site. 

“Deep packet inspection,” like WA sniffers looks at the entire payloadof packets in real-time across a huge number of simultaneous sessions.  Deep packet inspection, like regular packet sniffing, examines the files downloaded and the content of the pages viewed - the whole ball of wax. 

Deep packet inspection is being offered as a hardware/software technology by companies like FrontPorch and Sandvine (in the US) and Phorm(in the UK).  These companies are selling the technology to ISP’s (like Charter, Comcast, and Virgin Media) so that they can monitor the sites visited and the keywords used by customers, and then use the data collected for behavioral targeting.  The ISP’s want a slice of the juicy, lucrative online ad business.

What’s the difference?  Site owners collect data about what you do on ONE site (or a portfolio of their sites).  ISP’s collect data about what you do on EVERY site you visit.  As I understand it, some of these companies create an anonymous profile of your surfing activity by assigning a unique key to your browser.  Then they monitor the site’s visited by your browser, and use that data so that the ISP, or the companies to which they sell your data, can serve you what they conclude to be relevant, behaviorally targeted ads. 

Get it?  Packet sniffing by site owners = knowing about one site you visit.  Deep packet inspection by ISP’s = knowing about every site you visit.

Now to digress… In web analytics, we know that web analytics data is collected anonymously.  Unless there’s a login, you don’t know exactly who is coming from that IP address.  And in many cases, most companies data warehouses only contain purchase information, not the entire clickstream.  Once the data is collected, if you have the right architectures you can decode cookie values to people, and make that data non-anonymous (i.e PII).  Not difficult to do with some smart BI folks on your side.  

An ISP already knows who you are and can already identify the sites you visit.  Probably not that easily though on individual level.  They can dig through the logs, etc… 

So what’s the big deal and all the hoo-hah about  the “deep packet inspection” Phorm and FrontPorch are doing?   It’s the data they are collecting and the repository they are building containing data about every site you visit and all the content you view and download… Of course, these companies say that it’s all done anonymously and that your “privacy” is preserved “to the greatest extent possible.” 

Now let me quote Sir Tim Berners-Lee about the data collected from Phorm’s ISP tracking: “It’s mine - you can’t have it. If you want to use it for something, then you have to negotiate with me. I have to agree, I have to understand what I’m getting in return.”

And that’s the point of the blogviation, Tim is correct.  In web analytics, we do this - we try to operate within Tim’s constraints.  We enable opt-in with P3P statements and disclosures when you register/login.  Privacy policies disclose what we are doing with the data.  It’s just ethical and smart business practice to do so.

Thus, I think FrontPorch and Phorm and all the ISP’s who want a piece of online advertising should adhere to the following five rules for their services.

1. Move to an obvious “opt-in” model with full disclosure.  Tracking via “deep packet inspection” should be an all opt-in model.  If you want anonymous data from your browser collected so that you can be behaviorally targeted, then you should opt-in to be.  Right now, it’s seems to be all opt-out.  You probably don’t know if it’s being done to you.  It’s buried in fine print you’ve probably never read.  Is that your fault you didn’t read the fine print? Yeah, but the point is it shouldn’t be buried in the fine print…
2. Provide me with access to the data collected.  If I opt-in, I should be able to see the data collected from my browser.  It’s very simple.  I demand to see what you are collecting about my browser.  If you are building a profile, then I demand to see the data collected in the profile.  If it’s all anonymous, then explain how it is in detail, and then follow rule #1.
3. Enable me to edit or prevent the data from being collected.  If I opt-in, I want to be able to edit or prevent certain types of data from being collected.  If you’re tracking my browser, alert me before the data is transmitted, so I can decide if I want to share it.  If a profile is built, I want to be able to edit it!
4. Let me opt-out at any time EASILY. If I’ve opted in, and I’m unhappy with the service, allow me to opt-out simply.  Having to set an opt-out cookie on my browser is absolutely and completely absurd.  I want to be able to fully opt-out at the ISP level, just once forever, not at the browser level every time cookies are deleted.  Make it easy and permanent, not easily deletable.
5. Disclose who you sell my data too.  Like online list rentals, the next step in all this ISP profiling is selling the data to third-parties.  Let me know what you’re doing with my data-before you do it- so I can opt out or prevent it from being sold to parties to which I don’t want it being sold.

Consumers must be given a choice for preserving their privacy.  Anonymity to the “greatest extent possible” is not enough and neither are short-sighted opt-out cookies.  Companies like Phorm and Front Porch would be wise to apply these rules to regulate themselves.  Otherwise freedom-loving governments will almost certainly regulate them. 

And I haven’t even mentioned the issues with net neutrality and deep packet inspection (i.e. traffic shaping and access restrictions (called “throttling” as Clint points out in the comment), have I?

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!