This post shares new and traditional measurement options to sooth the savage SEO.  We’ll also offer a different take on organic keyword tracking, based on page level semantic cluster analysis using Webmaster Tools to mash in keywords, missing as a result of Google’s encrypted search. SO… read the whole post or skim down now for the sexy stuff. OK, let’s get started solving the new success measurement riddle-SEO, brothers and sisters! We’ll start with the most basic solutions like ranking reports, Bing data and new vs. returning organic keyword visitors + conversion. Then, we’ll progress to more radical approaches using Webmaster Central, you may not have thought of yet.

Background: Read It & Weep
Since the onset of Google’s encrypted search, which masks keyword data in analytics for users signed into Google.com, the effect has been astonishing. Though Matt Cutts told Danny Sullivan that, “Even at full rollout, this would still be in the single-digit percentages of all Google searchers on Google.com,” the real effect is highly vertical-specific. For instance, aimClear Blog lost keyword data for nearly 23% of organic visitors for November of 2011. We’ve seen significantly higher percentages on client sites.

Google actually has no actual privacy argument for masking the data because AdWords PPC passes keyword data just fine. Yep, big G has finally confirmed their long-rumored disdain for SEOs. It’s gross, really. Still, there’s no use crying over spilled keywords, so let’s just move along and find ways to operate in this more challenging environment.

Obviously this development makes measuring SEO success a bit more of a challenge, but not insurmountable. To Google’s credit they’ve also provided important capabilities, though still strategically limited, in Webmaster Tools. Our take is that keyword data is still there to be had with a little ingenuity, though organic conversion at the keyword level is a problem. There are a number of effective Webmaster Tools hacks that provide plenty of insight as to how SEO efforts are progressing, including mashing conversion at the page level, with good (though not empirical) semantic insight from both Webmaster Tools and Google Analytics. We’ll talk about that in a bit.

From mild to wild, here are solutions to consider:

Unpersonalized Ranking Reports
I know, I know, I’ve been saying that ranking reports were dead for years now. That all changes (again) with the Google’s masked organic keyword referrals. We like the SEOMoz and Raven ranking report tools the best, but there are others. Unpersonalized ranking reports actually matter slightly now for perspective on SEO efforts and to track progress of keywords in regionalized SERPs.  Such reports provide a general glimpse of how pages are performing at the KW level, trending, etc. Remember though: Actual users consume personalized SERPs and ranking reports don’t give any insight as to deep personalization. Average Position in Google Webmaster Tools provides additional perspective.  Ironically, some executives never stopped believing in ranking reports. LOL, now that they matter a little bit again, there’s nothing to sell. It’s back to the freakin’ future.

Overall & Bucketed Organic Search Traffic & Conversion
Though the method is as zoomed out, using Analytics to measure overall organic keyword traffic and conversion provides some insight. You can also run organic conversion at a granular level for keywords you can still see and run bucketed conversion numbers for those you can’t see.  This is the metrics approach that most businesses will understand and SEOs will use.  Keep reading for additional “basic” methods and then more intensive approaches.

Analytics New Vs. Returning Visitor/Organic Keyword
We think clients understand when SEO efforts yield new visitors from organic keywords, whether or not we can see all of the keywords responsible for traffic.  The report is easily accomplished using the Visitors report with keywords as the secondary dimension. Clients also seem to understand bucketed organic conversion from new visitors. Again, granular reports are available for whatever percentage of search traffic is not masked and the rest can be bucketed as a lump. This report is easy for aimClear Blog because we did not run PPC during for these days, so it’s all organic search traffic. That said, it’s not hard to use Advanced Segments to filter out PPC traffic.

Bing Organic Keyword Traffic
This is not sexy (skim down for sexy), but for larger sites, don’t rule out the usefulness of Bing as a measure of SEO performance. Yes, the search engines are different. Yes, Bing’s volume is not as great. However, at present Microsoft is not masking organic keyword data. We’ve looked back at Bing organic keyword conversion data vs. Google and, while different, it’s clear that in an age where we can’t see Google organic KW data, it’s better to have Bing data at hand than not.

Google Webmaster Tools: Keyword Impressions, Diversity & Average Position
Even before Google pulled the transparency plug, savvy SEOs were already using Webmaster Tools to measure increased keyword diversity, organic impression count, and rising or declining CTR (click through ratio). Such metrics are also very valuable because they’re apples-to-apples with PPC measurement, which provides a common denominator to calculate how organic traffic dilutes the cost of pay per click.

The screenshot below is the “Top queries” tab of the “Keywords” report. To measure success, keep track of organic keyword volume (Impressions), diversity (Queries), and rank (Avg. position). Monitoring CTR in light of rank gives SEOs wonderful insight as to how well the tag creative performs. We’re speaking of course of the title tag, which is essentially a headline in the organic SERPs. To the extent that meta description tags actually make it to the SERPs these days, the CTR/Avg. position also speaks to the effectiveness of the description which, when displayed, is the body copy of the organic ad. Sadly, Google does not display all impressions or clicks. This is in keeping with their philosophy of giving webmaster crucial information but not enough to easily impact SERPs by SEO. Boo.

In the Keywords report, filters are cool for culling keyword trends subsets segmented by image, mobile, smartphone mobile, videos, web, geography, and queries with more than ten impressions/clicks. Use this feature to distill data by various subsets to gauge performance along different lines of inquiry.

Filters are also super cool to create “concept groups” of keywords to track.

It’s notable that filtering down to a small enough subset of keywords seems to mitigate the transparency problem. All impressions and clicks are shown in this example.

Google Webmaster Tools: Top Pages Impressions, Diversity & Avg. Position
Click the “Top Pages” tab for (to my mind) the most useful report of them all.  This incredibly actionable report shows which pages in the site performed best organically and, better yet, a list of keywords responsible for the success. The reason this report is so actionable is because clicking on the little “+” or the link to any page expands to a list of keywords driving traffic to that page (second screen capture).

Of course, Google limits transparency by reporting <10 as opposed to actual numeric data. Are you catching the theme here? Google gives webmasters data, enough to help them keep sites from sucking, while not revealing enough actionable information to allow SEOs to really mold the page semantically, thus maximizing the importance of spending money on Google PPC products.

Over in Analytics, obviously we can’t measure organic keyword conversion for the “Keyword not provided” bucket. Measuring granular organic keyword conversion, for visitors with masked data, is simply not possible using any software. However, it’s useful to matriculate organic traffic and conversion at the page level, using analytics, with the keywords Webmaster tools reveals as primary drivers to that page. This does not tell us empirically which keywords are responsible for that page’s conversion, however it does give us decent insight as to the keyword cluster causing conversion. Mashing up:

• Page Traffic & conversion from keywords you CAN see in  analytics+
• Overall traffic & conversion at the page level in analytics +
• Page level keywords you can mostly see in Webmaster tools =
• A decent understanding of the “keyword not provided” bucket in analytics

In other words, Webmaster tools provides a snapshot the missing keyword granularity in analytics. Welcome to the age of measuring organic keyword clusters at the page level to prove #SEO. There are barriers, like what data is available on the Webmaster Tools API or exportable. You need to build your own data extraction API to use such a tool.  It was clear to us as we explored this issue, exactly where Google made sure to limit the usefulness of Webmaster Tools data.  Moving on…

Again, filters are your friends when it comes to page level measurements, along similar lines as the Keyword report filters.

Moving On
It’s apparent the encrypted keyword change is a paradigm buster that makes measuring SEO more of a task. Still, the problem is far from unbeatable and we think everybody should relax. There is useful data for those willing to work at methodology. Most notably, digging into the semantic “cluster” concept at the page level, with good though not empirical  insight from Webmaster Tools, is the way to go. Happy measuring!

Spaceman Image: © Byron Moore – Fotolia . com

Next month, Thom will lead marketers through the Introduction to Analytics on Day 2 of Search Engine Strategies San Francisco. aimClear’s Matt Peterson attended this same session in the New York installment of SES earlier this year, remarking, “Elementary essentials of analytics were addressed, but there were deep technical chestnuts that would pique the interest of even seasoned marketing vets.” In other words, don’t let the “Intro” angle of Thom’s session fool you; attendees should saddle up for a seriously deep dive into the core technologies of analytics every deep marketer should master.

aimClear had the pleasure of sharing a candid interview with Thom a month outside of #SES SFO. Topics of conversation ranged from shop-talk to dream dashboards and metrics in need of some TLC. Read on for the full effect.

| aimClear: You’ve been knee-deep in HTML code for almost two decades and involved in search marketing for more than ten years. Impressive. What about coding attracted you in the first place – and what prompted the shift towards SEM?

In 1991, I got involved in a student-run campus information system for RIT. It was, essentially, a series of hypertext map of the campus with information about the buildings, departments, etc. When we were at beta, another student outside the project said to us, “That’s cool and all, but why didn’t you just use Mosaic?” At the time, I didnt’ know what Mosaic or HTML was. I learned very quickly, becoming the “Web guy” at every position I held afterwards.

A number of years later I started one of the first Web development (and hosting) companies in Rochester. I took a unique approach of teaching my customers about the Web. I would create custom back-end interfaces to updating information on their site, putting that power in their hands. These types of interfaces are known today as a CMS.

During that time, I had a number of clients asking for confirmation that if I build it, they (the customers) would come. After a while, I couldn’t guess my way to that answer any longer and started researching how people got found online. I read everything I could and started attending SES Conferences. Ultimately, the coding was less important to me than helping people make the Web actually work for them. I learned a great deal about SEO, conversion and calculating ROI online. I passed this on to my clients and led the new SEM initiative after successfully merging my firm with a local interactive agency.

Now, I’m back at RIT as an employee, passing on information to students and leading the charge on analytics for the university’s mobile web initiative.

| aimClear: Quite the backstory. I dig. What’s your “most underrated” analytics package or feature? Or what metric do you think doesn’t get the love or attention that it should?

I think bounce rate gets more attention than it should, but not in a good way. Everyone looks at bounce rate as a bad metric (even Google, to an extent). But in the grand scheme of life, if someone searches for some arcane piece of information that’s burred deep within your Website, finds it in the first few blue links, clicks it and instantly has their answer by viewing the first page they see on your site, is that bad? Having deep content appear atop the search results and serving the customer’s needs quickly with less clicks is what good SEO is all about. Content is king. Not having a confused and frustrated customer clicking 20 links only to fail to find the information they seek is horrible service. Certain returning visitors with high bounce rate may conceivably show customer retention and loyalty.

| aimClear: You turn on your computer one day and the analytics dashboard of your wildest dreams magically appears on screen. What three features or data points are present that you couldn’t see before?

It should show that I’m earning enough to retire early and spoil my kids rotten clear through college!

Seriously, it depends on which site I’m looking at and which metrics I’m measuring. However, I can assure you the metric will never be an aggregate number measuring all visitors at the same time. The metrics will be segmented by certain criteria and would include historical trends, groupings and automatically suggest actionable recommendations for me.

| aimClear: Care to share your two cents on the future of analytics, in regards to recent EU case law, and where we may be heading with Do Not Track? Are we moving towards more obvious disclosure, opt-in only analytics, or are we about to lose all the cool data we love so much?

Privacy is going to be a concern. I’ve seen many opinions, too. On one hand, there’s a few generations of individuals who do not want to be tracked at all. I know many people that don’t want to be tracked ever, but want to make sure we track everyone who hits their site. On the other hand there’s a whole generation of students at our mostly technical university who have the opinion that they’re not doing anything wrong, so track away. Which, by itself isn’t a stance on privacy laws. Both the EU and Congress need to apply some common-sense rules regarding non-personal tracking. Everything on a computer is tracked; it’s the way networks are analyzed and repaired. Marketers just happen to hitch a ride on existing logging of publicly accessible information. If the government says we have no reasonable expectation of our cars parked in our driveway, we should clearly have no reasonable expectation of privacy when we request information from someone else’s Web site.

| aimClear: What is it about analytics revs your proverbial engine?

Making sense out of chaos; it’s the ultimate thrill.

Having gone from simply building “cool Web pages” to tracking how much revenue a company earned as a direct result of those same cool pages is really fascinating. I’ve been helping build the Web longer than this year’s incoming freshmen have been alive. I’ve grown from “this is cool” to “I had 100 hits” to “how do people get here” to “these kinds of people are more apt to buy” to “We saved n-thousand dollars directly because of x,y and z actions online.” It boggles my mind everyday.

The ever-changing Web landscape and the myriad of metrics feed my ADD, too.

| aimClear: Day 1 of SES San Francisco will find you up on stage delivering a solo presentation on Intro to Analytics. Can we get a little behind-the-scenes look at what you’ll dish up? (Also… what are some ways you like to get beginners excited about something as analytical as… analytics?)

I truly go through the all the basics of collecting data and determining which metrics are available. I start with how data are collected to how they are measured and a bunch of lame jokes. I move on to which metrics are available and, without actually mentioning the phrase KPI, I talk about which metrics make sense to use and which ones don’t. As we progress, the jokes get worse, but you’ll have some great insight into a dry subject by someone with a gentle bedside manner. When you’re done, you’ll have a good understanding of where to start measuring your own site and a better appreciation for good comedy.

| aimClear: Right on, Thom Thanks for your time today. See you in San Fran!

Facebook Ads, “Advertising Performance Reports” are the primary analytics marketers use to optimize FB Ads campaigns and create reports. Over the last few weeks, and through the May 25th UI update, our aimClear team thoroughly researched available optimization metrics,  what they mean, where they appear, and at what access points they are editable live in various screens. The process reminded us of reverse engineering an octopus. Simply stated, some of the most insightful analytic attributes available, are not available at a point where FB Ads account are editable for optimization. Therefore, knowing what metrics are available, where to access them, and what they mean, is crucial because you’re going to have to build spreadsheet applications to figure things out.

The results of our study, along with tons of insight and optimization recommendations, are detailed for release in our upcoming Wiley/Sybex book about Facebook Ads (“Killer Facebook Ads”), which is scheduled for release at SES San Francisco. As SMX Advanced Seattle and All Facebook Summit approach, we want to share top line results with the online marketing community, by way of this handy guide.  Below the chart, we explain what data screens comprise the chart, how to read the grid, and what each Facebook metric basically means.

For advanced marketers, we think the, “Connections” metric is the biggest takeaway, because it’s a new internal metric, which can be used for tracking internal conversion to internal FB assets. Also, we should mention that other Facebook Ads reports, “Responder Demographics” and, “Responder Profiles” can be very useful for optimization purposes. This post focuses on the, Advertiser Performance Report, because it is the root data for the FB Ads Manager UI.

(You may need to open your browser up wider or zoom out to view this entire chart)

Facebook Ads, “Ads Manager” is where advertisers, who don’t  use API apps’ like Acquisio, analyze performance data and make the moves to optimize the account. There are three basic views:

Clicking on “Campaigns & Ads” brings you to a list of all campaigns in the account. Clicking on any individual campaign brings you to the (individual) “Campaign” screens. “All Ads” is a list of all the ads, account wide.

Each of the three main screens is essentially a lighter preset version of the, “Advertising Performance Report,” also available with many more options via the, “Reports” module. What makes these Ads Manager screens unique is that some (and I mean some) attributes are editable, to facilitate optimization.  Knowing which attributes are editable where can be something of a Rubik’s Cube.  There are important missing pieces, like the ability to easily live-optimize campaigns, account wide, side by side.

Each of the three main Ads Manager UI screens, “All Campaigns,” “All Ads,” and (individual) “Campaign” feature HTML data grids which are sortable by column heads, with selectable date ranges for viewing purposes. There are also non-sortable attributes available above on the page, in some instances.

Clicking the, “Full Report” button from each of the main Ads Manager UI screens, calls a deeper HTML version of the same Advertiser Performance report, culled from the, “Reports” module. Look to the left sidebar and you’ll see that now you’re actually in the reports module. Non of these attributes are editable for optimization purposes, but additional data is available. Each of the Full Reports, include options to, export the report to .CSV, each of which includes even more metrics in a deeper spreadsheet version, again, of the same root report.

How To Read The Chart Above
From left to right along the top, we’ve listed each of the three main UI HTML screens, their Full Reports and each Full Report’s .CSV Export.  The final column to the right is for the .CSV export for both the (individual) “Campaign” and the, “All Ads” .CSV export, because they are essentially the same.

The left hand side of the chart lists metrics available in the main Ads Manager UI screens, their Full Reports and Exports.  * means that the attribute is editable live for optimization.  Where attributes are editable and where they are not, is key for optimizers. Please note that some UI screens have attributes which can be viewed or edited at multiple levels of account hierarchy. For instance in the (individual) Campaign screen, CPC is visible at both the campaign and individual ads levels.

What The Metrics Mean
OK, let’s dive into the metrics themselves.  As an upfront, just because FB says a metric is supposed to exist, does not mean it works. For instance the, “Conversion” metric is retired, as FB does not offer native conversion tracking for external pages any longer. Campaign Name, Ad Name, Clicks,  CTR, Impressions, CPM (Cost per thousand impressions) require no explanations. The following metrics deserve mention and/or a bit of clarification.

Connections
Tracking conversion to internal FB assets is possible with Facebook’s newly released, “Connections” metric. Connections replaces the retired Actions metric. If you’re not routing your ad or sponsored story to an internal FB asset (Page, Event, or App) you won’t have any Connections data.

Audience & Response Graph

The brand new circular, “Audience” graph provides relative visual representations of:

• How many people the campaign targets (“Targeted”)
• How many unique people saw your ads (“Reach”)
• One way that FB Ads support socialization of ads is to display the names of users’ friends who engaged with FB assets you’re marketing with Facebook Ads. “Social reach” is a proprietary FB metric which shows, “People who saw your campaign’s Sponsored Stories or ads with the names of their friends who liked your Page, RSVP’d to your event, or used your app. If you’re not using Sponsored stories or advertising a Page, event, or app, you won’t have social reach.

Roll your mouse over either the Targeted, Reach, or Social Reach circles in the Audience graph, to see the exact count of users that comprise the circle.

The “Response” graph shows a line graph for the last 28 days of:

• How many total clicks your ads garnered (“Clicks”).
• FB describes as “The number of users who liked your Facebook Page, RSVPed to your event, or installed your app within 24 hours of seeing this Sponsored Story or ad. If you’re not promoting a Page, event, or app, you won’t see impressions Time data.”

Reach
How many unique FB users saw your ad.

Social Reach
When a FB user sees an ad impression, marketing to an internal FB asset that any of their friends interacted with, the ad has an extra caption highlighting which friend(s) Liked, RSVP’d or used the app’. “Social reach” shows, “People who saw your campaign’s Sponsored Stories or ads with the names of their friends who liked your Page, RSVP’d to your event, or used your app.

Frequency
Brand marketers will love this new metric. Frequency is how many individual users, in your targeted segments, saw your campaign or ad. Frequency really means unique impressions.

Status
Sort  by campaigns or ads that are running,  paused, scheduled dates and those deleted or completed. When editable, click the downward-facing triangle to pause an ads or campaigns, make them active, or delete them. When editable, this is an important optimization attribute.

Bid
How much you’re willing to pay for a click or by CPM. The only notable factor about bids, is that you can only bid at the ad level, and not the campaign.  When editable, this is a prime optimization attribute.

Price
For CPM ad, this really means average CPM- the average cost per thousand views. For CPC ads, this really means average CPC- the average cost you paid per click. -Spent

Start Date
Edit or sort campaigns by their start date and whether they are running continuously (ongoing), paused, completed, or deleted.

End Date
Edit or sort the end date for scheduled campaigns or by those running continuously (ongoing).

Date Range
Refers to the time period you’re currently viewing in an Advertiser Performance Report. When editable, this attribute lets you changes the time period for which you’re viewing the report.

Remaining
Money remaining in today’s daily or lifetime budget for a campaign

Spent
The total amount spent on the campaign for the time period selected

Budget
Facebook Ads have several budgeting points, including the daily limit set by FB and a lifetime budget advertisers can set. The attribute in Advertising Performance Reports speaks to daily campaign budget, either as set by the day or automatically metered our over the shelf life of a scheduled campaign. When editable, this is a key optimization attribute.

Campaign ID and Ad ID
Facebook assigns unique identification number to campaigns and ads, thus the, “Campaign ID” and, “Ad ID.” This attribute, only available by .CSV export, is useful for building API and spreadsheet (bulk upload) applications.

Unique Clicks, Unique CTR
The unique statistics take into consideration that a single person may click an ad multiple times and that person is counted as only one click in the unique metrics.

Social Impressions
Facebook has described this metric as, “How many times your ad was displayed along with social context surrounding the viewer’s friends who have connected with your page, event, or application.” While this metric still appears on some reports as of this writing, FB appears to be renaming it, “Social Reach.”

Social %
Facebook has described this metric as, “Percentage of overall impressions that included social impressions.”  Keeping in mind that, “Social Reach”  means how many users saw your ad with friends’ names, “Social %” is the percentage of users who saw the ad in social context.

Social Clicks
How many clicks resulted from Social Impressions (Social Reach). I love this metric because it clearly demonstrates if there is any value to   serving ads in social context.

Social CTR
The social click rate is the percentage of Social Impressions (Reach) that result in social clicks

Wrapping Up
Of Course, there’s much more to say about these metrics and FB Ads reporting. We hope you find this guide a useful aid in your optimization and reporting work.  Feel free to reach out with any questions or comments and happy Facebook advertising!

The types of marketing conversations that dominated #SESNY 2011 demonstrated a turning-point of analytic maturity for the industry. From the complexities (to some, futility) of attribution modeling, to the advertising implications of Do Not Track legislation, to borderline existential discussions of user intent & behavior, it’s easy to forget just how far our interpretation of web analytics have evolved. Some analytics packages and logfile analyzers (such as IPRO) will be turning 17 along with Justin Bieber this year. Just because we’ve gone from summing “hits” from a single web page to cross-channel user attribution, are we beyond revisiting the basics for refreshed perspective?

In the session Introduction to Analytics at Search Engine Strategies New York, we looked at differences between the core technologies of analytics, uses, as well as advantages & drawbacks of each. Don’t let the “Introductory” angle of this session’s title fool you. Elementary essentials of analytics were addressed, but there were deep technical chestnuts that would pique the interest of even seasoned marketing vets. Read on for a recap of the insightful discussion.

Thom Craver, web and database specialist at the Saunders College of Business, was to be the solo presenter, and our guide through the history of web analytics. He warned the crowd that things might be geeky. We were ready. To prime us, Thom showed a slide highlighting various analytics platforms, and asked the audience to raise hands if they use one or more of these. Several hands remained lowered. To the owners of the hands, Thom recommended they use the Hope & Pray method.

What Are Web Analytics?
Analytics are a lot of things to a lot of people. Everyone has to look for the particular metric that means something to them. The biggest take away from this session should be that you’re actually doing something actionable. You’ve probably already optimized your on-page stuff… things like title tags & ad copy. Then you test. Use analytics to have a deep look at what went wrong and what went right.  Always test & analyze before you repeat!

Log files vs. JavaScript Analytics
The origin of analytics data started in log files and then moved on to JavaScript collectors and cookies. The log file is a server log. Someone went to my site or my server & it happened on this day and time, etc. It’s very geeky; it logs specific files & URLs.

JavaScript Analytics, on the other hand, comes along with your page– meaning it happens within the browser itself. JavaScript can allow you to track many other on-page actions that log files can’t, such as hitting pause on an embedded video.

Analyzing log files presents an issue because you have to define exactly what a page is. Does your page always end with .html, .htm,  or .php?  Every time you have to figure out what a page on your site was created in, you have to go back to your developer & let him/her know when configuring.

Also, consider Ajax. One example of how Ajax affects log files is Twitter, where you may not click on anything to trigger a new page view. It’s all on-page interaction & what makes that appear is a .php on the server somewhere.  If you only look at log files, all these little interactions become additional page views, which over-inflates the true number. Conversely, JavaScript more accurately counts page views & events via on-page actions.

The downside of JavaScript analytics is that it’s often blocked. If you’re B2C & the average Joe is your consumer, it’s not a huge problem. The general public usually uses the least secure features and accepts every cookie. If your customers are Internet-savvy, socially conscious and active in organizations like the EFF, chances are many of them will block cookies & you won’t be able to learn a great deal about their behavior through analytics.

Another thing to take into account is who sends the cookie; is it  you, or a third party? Some users are configured to not accept third party cookies. Consider your solution carefully… you won’t be able to count visitors accurately if you’re not configured properly.

Sample Process: Logs vs. JavaScript
Let’s look at the log file process in practice. Say you have a user on your site… that user goes from homepage to another page, but then goes back to homepage. Now, the user going back to the homepage may not count as a page view because log files are often configured to use a cache copy of the log if the page hasn’t been updated.

Let’s look at that example on the JavaScript side. The user is on your site. They go from the homepage to another page and then back. With JavaScript, it actually logs the additional homepage page view. What happens when that user decides to leave the site by going to www.yourcompetitor.com? Well, if you code the JavaScript properly, you can let it collect where the user left, the next site they went to. Now’s you have the opportunity to set an exit event. Familiar with those really annoying exit events… those awful popup dialog boxes that say “Are you really really sure you want to leave?”  Don’t do that. Use exit events for good; if users are leaving your site, use the data to understand why, so you can better fulfill their needs.

Which method should you choose?
Often, you have marketing guys that need one set of data and the IT guys who want another set of data. The IT guys are concerned with things such as, “How can we handle increased server load?” and “Do we need to upgrade our hosting?” when looking at log files. The Marketing guys are more like, “I don’t care, I want to know how people are moving around my site.” They’re are focused on JavaScript-based analytics packages.

It’s important to understand that neither one reports your visitors with 100% accuracy,  but the point is to visualize overall trends and patterns.

It’s Definition Time

• Hit – This is a single request to a web server (code/images etc.). These are all separate log file entries. Loading multiple elements might mean 5-10-15 hits for any given page.
• Page View – Occurs when a web page and all of its parts are fully displayed.
• Visitors – Someone who visits your site, but each software tracks them different. Consider that log file analysis of users is all IP-based. For example, when you have a site that gets accessed frequently from a computer lab at a college, one machine might see 50 students (visitors) a day. If you just use log file analysis, it looks like one continuous user. With cookies, each login and browser is unique & you know there are 50 unique visitors.
• Returning Visitors -  Anyone with a cookie from previously viewing your site.
• Unique Visitors – Not necessarily a new visitors, they’re defined in time periods.  This can change depending on the stats you’re looking at.
• Visit Session – The start to finish browsing period of someone surfing your site. If you use log files,  it looks like the same user.
• Bounces – Users that come to only 1 page and then leave. You can make it time-based or you can define it by certain number of pages viewed.

There are many more things you can learn about users, geeky stuff, through analytics.  Things like computer type, browser, screen resolutions, connection speed and if they’re on a mobile device.

You need to pay attention to all of these. What if your mobile user base grows rapidly, but your site isn’t currently equipped to best serve them? If these users come and can’t use all or part of your site because it’s doesn’t support mobile, they’re going to bounce.

Content Metrics

• The Landing page – This isn’t always the home page, but it’s the first page a visitor viewed during the visit. If you’re properly optimized, somewhere in the middle of your site should be a typical landing page, too.
• Exit page – This is the last page a visitor viewed during their visit. This can be misleading if you look at pure log files.

Miscellaneous Content Stats
Look at most popular pages on your site. Also, examine user navigation paths… are your users going to unpredictable areas?  Don’t forget to examine events or on-page interaction.

Tracking Events
Examine users’ time on page & overall time on site. If you have a video player or embedded video on your site, you can look at load times, when people pause, stop or rewind the video, if they hit the mute button (is your audio annoying?) or if they turn the volume up/down (too wide a dynamic range?).

Map interaction
You can tell if people are interacting with your map on your page. This is especially useful if you’re a local business.

Traffic sources
How & from where are people coming to your site? There are 3 main possibilities here:

1. People can enter your site URL directly into a browser.

2. They can find it from search engine results.

3. They can be referred from other sites.

However, there is a 4^th type of visit; Google analytics calls it “Other.” (This can be a lot of things, often times it’s visits from email.)

When you want to get deep when looking at traffic sources, start using Google tracking variables. They’re just a little extra tail at the end of your URL that looks something like: ?variable=somevalue&var2=something else

This code does not affect the page delivered (unless you’re doing some dynamic text swapping based on URL variables) but allows you to see these custom sources in Analytics by themselves. It’s also recognized by server logs and scripts.

Thom recommends using the Google URL builder  because it allows you to tag the URL with many different variables that you can use to track usage of specific users groups, channels, campaigns, etc.

Tracking Off-line Visitors
What if you still use traditional media? Posters print, news, & TV? You’re not going to put in a long Google URL for your contact info… no one’s going to visit it. Try fitting, “If you’d like to learn more, visit www.mysite.com?variable=radio&variable2=conservativetalkshow etc. now!” in a 20 second radio spot.

Instead of the long URL, consider using a short redirected URL that’s unique to the campaign. Something like mysite.com/promo (only listed in TV ads), then redirect to your longer landing page URL to track visitors from the TV ad.

Another neat upcoming trend: QR codes. Pay attention to them. Get a smartphone with a barcode reader, go up to a QR code to scan it, and access all different information from the code. You can also put URLs in there. This is very important because QR codes are a medium where you can have a gigantic URL  and you can output the QR codes. This only works for mobile users, but it’s still an additional source to track.

Setting & Tracking Goals
Before you can make sense of Analytics, you have to have a goal first. If you don’t already have one (or multiple), sit down with your marketing team and have a serious talk about it. Look at each of your audiences differently. For example, if you’re a college, some of your audience consists of current students. A lot of them will be checking out the office hours of their professors & finding what they need right away (if it’s there). In this case, a high bounce rate is good; they found exactly what they needed and then left. On the other hand, some of your audience will be prospective students: a high bounce rate here could be very bad.

Like any good marketing campaign, you should create a funnel where you have a broad base of people you target initially and continuously narrow them down until they convert.

On your site, you have certain pages a user must hit before they ultimately convert. Each of these pages/point is a small goal towards a final conversion goal. Here’s a simple example funnel:

Add to Cart – Checkout Page – Confirm Information – Complete Purchase

Where in this funnel people drop out is key to optimizing conversions on your site. It may be a display, connection, privacy, or trust issue. Look at that data with granularity in the funnel.

Thus concluded Thom’s excellent Introduction to Analytics session; an informative examination of analytic basics with some interesting tidbits & takeaways for the masses. For additional post-conference coverage of SES New York 2011, stay tuned to aimClear blog.

photo credit: woodleywonderworks

More analytics mavens are becoming aware of Woopra, a relatively inexpensive software package, available on the web and as a desktop application.  Woopra is best known for its gorgeous daily dashboard (pictured above) and extremely useful real-time analytics features (below).  For this post, we’ll use the desktop application.

What’s less known are Woopra’s killer KPI reporting capabilities, using custom segmentation features Woopra calls “Filters.”  This post extrapolates on my previous SearchEngineWatch article, “Google Analytics, Conversion Tracking & Single Segment Reporting Power,” bringing the powerful conversion tracking technique to Woopra, one of the most intuitive analytics UIs in the world.  Let’s get started building our KPI dashboard.

Creating KPI Segmentation “Filters” in Woopra
Start by clicking on the analytics link on the left-hand column.

Then choose “Create a new filter.”

Choose from the standard suite of analytics segmenting criteria, including search query, platform, browser, full referral URL that includes any URL variables and referrer types, among others.  Note that various engagement metrics are unique to Woopra, including an intriguing capacity to track segments flagging specific users you’ve tagged in the course of day-to-day real-time analysis.

For this demo we’ll track progress of our recent Google Keyword Tool article.

While we’ll keep this segment simple, note that it’s possible to stack complex segmenting criteria, just like when using Google Analytics Advanced Segments.  After returning to the analytics link on the left-hand column, select the segment just created.

Then specify a date range. The link is in the UI’s upper right.

Great! Now we’re focusing all the power of Woopra analytics screens solely on our conversion segment.  Our KPI, again, is traffic to a specific page.  This certainly could be a “Thank You” page with a confirmation URL variable for a form submission or an e-commerce purchase.  Actionable insights gained, whilst perusing single conversion segments, can be dramatic, colorful and super easy to read.  Here are some reports we’re fond of.

Conversion by Daily Visitors & Time On Page
This cool report highlights time-on-page each day that converting visitors invested in our content. Note that by clicking on Friday the 8^th, the purple graph shows our page views for the selected day.

Conversion By Country
This über pretty report rarely fails to wow clients. Click on any line graph to expand the graph.

Search Engine Conversion
Wondering if keyword referrals from search engines around the world result in conversions? This report is crystal clear.

KPI Conversion Calendar
We love this one, and it’s truly one of the coolest features of Woopra.  The upper left-hand corner shows KPI performance for month-to-date.  Moving across the top row, we see conversion for the average Monday, Tuesday, Wednesday, etc. Then KPI success is tracked by the day for the rest of the month.  This report kicks ass.

Conversion by Browser Type
Sometimes conversion problems are associated with issues sites have with certain browsers and platforms.  Perhaps a key page in the funnel is not parsing correctly for some reason.  This report flags conversion by browser.

KPI Conversion by Referring Site
It’s easy to see that Sphinn.com has sent some visitors. We’ve clicked on Sphinn in the Woopra UI, graphing referrals to our KPI page by day. If a picture speaks a thousand words, this report offers 2000.

Conversion by Referral Type
Woopra has preset referral buckets, sorted by a basic subdivision of site-types that send traffic.  The sort is by social networks, search engines, social bookmarks, feed readers, etc.

Exportable reports are uninspiring, but useful nonetheless.

Using Woopra as a KPI Dashboard
We suggest that those serious about reporting with Woopra build a macro that screen scrapes or otherwise documents reports for clients.  It’s very cool to do a narrated screen cast and email the file to clients, giving a weekly 60-second overview of KPI progress from the previous week or other time interval.  Also, clients can install their own local version on a computer to track KPI progress. It’s quite simple to teach anyone to choose between various KPI segments that we set up for them.

Enjoy, and let us know what you think of Woopra for KPI reporting.

* Sigh * As long as I can remember, spring and summer have been the time for (but not limited to) barbecues, swimming and the effects of semi-surprise search algorithm updates on our clients. Recently, we’ve seen Google tinker under the hood, announcing the Mayday and (long advertised) Caffeine algorithm changes. Yahoo has been making various mods as well.

To the benefit of our readers, we’ve put together a client case study that looks at measurement techniques for evaluating site performance through Google and Yahoo’s algo’ changes. Some precursor notes: for this particular study, we pulled conversion data using the surfing single analytics segments technique. The featured site is a small but very profitable trade publication in Google News.  Also, there was a major push to improve organic conversion in preparation for the Caffeine update. That adds for more intrigue to some cool reports further down the page.

Global Traffic April 1 – July
Doing well…wonder where that traffic’s coming from… It’s always important to have a look at overall traffic and where the visitors come from.

All Conversion
Here we have all of the conversion sources.  Remember we’re going to be looking at the effects of organic algorithm changes. Still, it’s cool to take note of how organic fares against PPC. Don’t worry, we know this is basic yet. Trust there are going to be some pretty sexy reports coming up in this post.

Traffic Effect On Yahoo Organic Through Yahoo Algorithm Change
Wow, we actually gained organic keyword traffic through the change. The red dot is where the algo’ shift took place.

Conversion Effect Yahoo Organic, Through Yahoo Algorithm Change.
How fun is this! In reality, we prescribed and the client executed a major organic conversion effort. It worked so well the organic change at Yahoo barely even mattered.

Bing Organic Traffic
The traffic trend is pretty similar that of Yahoo. We’re watching Bing because, well, sooner or later Bing will become Yahoo.

This is the same view by the week as opposed to by the month.

Bing Conversion
This data tells us straight-up that traffic from Bing does not convert. However this may be a red herring. Run the percentages. The percentage of overall organic search traffic for Bing is still low because it’s still Bing, although Bing is growing.

The Effect of MayDay & Caffeine on Organic Google Keyword Traffic
Interestingly enough, the downturn in traffic here was only a slight one for this client. The green line is the previous 30 day period of organic keyword traffic. The blue line is the current 30 day period.

Reduced PPC Expenditure
In the overall profile of this site, we look at the client’s 3o over 30 PPC investment. The client ratcheted down PPC spend because conversions now come from organic.  How cool is THAT!

Progression of PPC Conversion
Also, the reduced PPC expenditure has not hurt because PPC conversion is up. Hey, this stuff looks good.

Progression of Organic Conversion, Even Across Caffeine
Again, the organic conversion initiative success obscures the Mayday and Caffeine updates.

Something interesting to note is that the peaking, highly-seasonal search pattern for this client’s industry is in fall and early winter. This new data speaks to how the algorithm updates enabled site traffic and conversion performance, resulting in a stark difference from the normal ebb of seasonal traffic.

For further info on the three recent algorithm updates, check out some of the resources below:

Yahoo! Update
Yahoo! Search Algorithm Moves Towards Links & Authority Sites – SEObook, Aaron Wall
March Weather Report: Yahoo! Search Update – Yahoo! Blog, Dan Rampton
April Weather Report: Yahoo! Search Update – Yahoo! Blog, Dan Rampton

Mayday
Google Confirms “Mayday” Update Impacts Long-tail Traffic – SearchEngineLand, Vanessa Fox
Whiteboard Friday – Google’s May Day Update & What It Means for You – SEOmoz, Scott Willoughby

Caffeine
Our New Search Index: Caffeine – The Official Google Blog, Carrie Grimes
Matt Cutts Explains Caffeine Update – WebProNews

The main selling points of Omniture are engine-independence and paid support. Conceptually, there is something to be said about using a third-party tool to manage your spend across multiple engines. At the same time, the primary engines have formats (API and bulk loading) that make it easy to export and import campaigns.

In this regard, the gap that used to be there a couple years ago is now closed– and then there are cheap tools like SpeedPPC that quickly multiply and distribute campaigns across multiple engines. Omniture’s SearchCenter integration with the platform is in marketing only– true product integration is a long ways off and not likely, given that it’s already been a couple years in the making (data warehouse export is still not working), and that Adobe bought Omniture.

• Google Analytics doesn’t offer paid support. While there are a few GAC consultants that Google authorizes (they have to pass a test for certification– harder than the AdWords qualification), and there are some PPC/Analytics training sessions sponsored by Google– there is definitely not the kind of support/consulting you get from buying software. Many corporations prefer the idea of paid software and are comfortable with that model of having an account manager they can call up with questions, plus a block of services hours for implementation and report development. That said, you might ask Omniture about their support offering and ask a few clients that are peers of Global Sources to inquire about the support they get.
• Campaign reporting. GA allows for multiple dimensions– in particular, motion charts, advanced segments, and the various multi-dimensional views that are metric specific. I believe Omniture is inferior in this regard because of GA’s ability to visualize data in cross-tab (pivot) and related view formats. In other words, it’s easier to uncover trends in GA than by hunting through Omniture.
• Integration. This is usually a red herring across most Internet marketing companies. The most important integration in analytics and PPC software is that of CRM interaction (salesforce.com, Eloqua, Microsoft Dynamics, SugarCRM, etc..) and offline conversions. This almost always requires some custom work, since every company has a different underlying data model (which they should), as well as a different sales funnel and attribution scheme. The collection, integration, and weighting of this data is not an out-of-the-box software module, but an exercise of sophisticated marketing analytics. Online conversion tracking is relatively simple for all enterprise-level analytics tools, whether using a method like Google URL Builder or cookie tracking. Google has a significant advantage in tracking activity from and on Facebook, despite the marketing efforts put forth by Omniture.
• Funnel tracking. Omniture does allow for multiple paths. Our viewpoint is that the more sophisticated method is to measure event-level attribution (page or click), rather than force the analyst (you) to have to define each particular path to analyze. The traditional methods of slice-and-dice is a needle in a haystack approach — you should prefer your analytics tool to do the legwork to tell you what combinations of pages lead to a conversion or a poor user experience. We are not aware of any clickstream analytics tool that does this out of the box. With the number of combinations of attributes events, and pages possible, you need click level data and a correlation algorithm to pull out the right combination of trends to view. You cannot do this out of GA yourself, because you’ll need the raw data to calculate. That said, log file parsing is probably the most practical solution here if you want to go that far in analytics, given that Omniture doesn’t know how to do it (we’ve had multiple calls with their top people and they are stumped).
• User tagging. Omniture does allow for more variables to be stored. You’ll want to consider what use cases you have that cannot be solved via an advanced segment and parsing urls. If you’re interested in Omniture’s solution, please read the chapter in their implementation guide — it’s a confusing read, but they do allow collection of personal data. Google doesn’t allow collection of such data for privacy reasons. Not sure about auditing requirements — any certification of data accuracy would have to rely upon click-level data out of your logs, which Google can’t do (unless you have the old urchin, which is not recommended).
• Goal tracking. Google has recently expanded from 4 goals to 20 goals. Most companies misuse goal-setting, as they confuse segments and points within the funnel as goals. The more goals you have, the more complex the attribution. It’s hard enough to do attribution when you have only 1 goal and many events for which you have to allocate credit — now try matrix attribution with many goals and many events. To the best of our knowledge, almost nobody has single goal attribution down, so matrix attribution is not even in the vernacular of analytics yet.
• Page overlays. Cool tool with wow factors for both GA and Omniture– but usually not usable because of tracking problems and multiple links on a page that have the same URL. On the latter, let’s say that on a particular page, there are two links to get to another page (a topnav and a footer nav link)– if they have the same destination url, you won’t be able to tell which one drove the click. We have rarely found the visual overlays to offer accurate data.
• Data freshness. Generally a 2-10 hour delay on Google. Data freshness is most important is when you have events that require real-time optimization. Keep in mind that PPC data may be on a full day lag and you’re limited by your weakest link. Thus, if your web analytics is only 30 minutes behind, but your PPC and CRM are 4 hours behind, you’re really 4 hours behind (or you’re making inaccurate decisions). Further, the concept of statistical significance is such that you have to gather enough data to determine what’s going on. At Yahoo!, we decided that a 3 day reporting delay (because we needed 2.5 days to crunch attribution) was worth the trade-off in speed versus effective optimization. You’ll have to decide what data you really need at what frequency.
• Independence. Several of the government agencies we have talked to don’t use Google Analytics because open source is considered off-limits. Some major advertisers don’t use GA because of the potential conflict of interest in having your analytics being tracked with the place you spend your money. And there are the “tin foil hat” and anti-monopoly people that in general don’t believe you should have your analytics, PPC, landing page testing, mail, and so forth with the same company. Given practical realities, we don’t think this is an issue right now.
• Effectiveness. Google AdWords is going to have more effective (effective meaning increasing profits, as opposed to allowing you to create more reports) tools than 3rd party tools– they have to, because they have the advantage of more data. Case in point– the Conversion Optimizer of Google versus any bid management tools. With the exception of folks like ClickEquations (market leader who is good, but not great), in our opinion, nobody yet has a sophisticated method of bid management.

Omniture vs. Google Analytics comparison

Another potential plus for Omniture is that they’re releasing tools to manage Facebook PPC campaigns via their API.

Whether these tools are robust and take advantage of social targeting is yet to be seen, given that advertisers who blindly copy their PPC ads to Facebook don’t meet with success. They are also interacting with Facebook solely via the API, which is quite limited versus what’s available in the web interface or other third party tools that communicate by other methods.

Net-net, you can do mountains of comparison and research on web analytics tools. There is plenty to be said about the GA vs. Omniture debate. Our advice is to start from your goals and then decide, as opposed to what most people do, which is to create a wish list of every possible feature they might ever use and see who has the most checkboxes. That approach will lead you to the wrong solution, as most of the nice-to-have features you’ll never use.

The act of defining your goals, optimizations to directly improve such goals, and the reports to diagnose when you’ll take such optimizations is a re-statement of the process that BlitzLocal uses in running campaigns— that is metrics > analysis > action. If there are any metrics/reports that are not actionable, they are a waste of time. Metrics are about what has changed significantly since last time, analytics is about why, and action is what you’re going to do about it.

Dennis Yu is CEO of BlitzLocal, an Internet marketing firm specializing in Facebook and PPC campaigns.  He is an international speaker and author.

Opinions expressed in the article are those of the guest author and not necessarily those of aimClear LLC or aimClear Blog.

The luminous Anne Kennedy, Founder & MP of Beyond Ink, FP & CMO Joblr.net, not to mention SES Advisory Board member, moderated the panel of authorities on Eye Tracking Research consisting of Shari Thurow, Founder & SEO Director of Omni Marketing Interactive, Jeremi Karnell, Co-Founder and President of One to One Interactive and Susan Weinschenk, Chief of User Experience Strategy at Human Factors International.

First to speak was Shari Thurow. She addressed eye tracking in relation to search engines as well as its weaknesses.

Next was Karnell who started his presentation with a question: “What is this?”

It’s the fleur de lis, but as a symbol it represents many different things to different people:

• French monarchy
• The Saints football team (I don’t know about you, but that’s what I said… )
• Boy Scouts
• Chevy Corvette, etc…

Symbols mean a lot of things and people have instinctual reactions to them. This is exactly why brands use them.

One to One Insights developed a study for eye tracking, here Karnell revealed the objectives, study, insights and their conclusions.

Objectives

1. Determine user behavior and engagement with SERPs vs. text only.
2. Asses impact.
3. Identify potential impacts on SEM campaigns.
4. Gather preliminary data to form a larger study.

Study

1. Recruited 17 subjects who wanted to change their cable provider.
2. Established 10 keyword sets- six branded, four unbranded.
3. Created four SERPs for each keyword = 40 permutations.
4. Created natural, natural with paid, universal, universal with paid.
5. Collected eye tracking.
6. Distributed two surveys (Geneva Emotion Wheel & Likert Ranking Scale).
7. Asked: ?What link would you click first? Second?”

Insights
Universal SERPs that included mixed results

• Video was typically fixated on before the first natural and right paid links (17%)
• Video links received more clicks than top pd link
• Image links receive more fist fixations

Universal SERPs and the Golden Triangle

• With text only: F pattern.
• Many scrolled below fold.
• Universal Search = golden triangle. Visual density stayed at the top.
• Video and image results increase engagement on SERPs.
• Universal only and universal with paid had significantly higher levels of engagement.
• People believe images and engage as a result.

Conclusions

1. Creating a holistic stat that considers all search interaction will create competitive advantage and drive more engaged visits through SEM activities.
2. Understanding your brand does have an impact on search environment.
3. Think about how your digital assets can be leveraged. Be sure to use appropriate tagging.

Weinschenk, the brain lady, spoke about the psychological implications one must take into consideration when using eye tracking studies.

Humans have an estimated 40 million sensory inputs coming into our brains every second! Wowza!

BUT, we are only consciously aware of up to 40. Most sensory processing is happening unconsciously.

Three Parts of Brain

• New brain (Conscious)
• Mid brain (Process emotions & visual info process)
• Old brain (Instincts. Our animal instincts are constantly scanning environment asking: Can I eat it? Can I have sex with it? Will it kill me?)

How can we get at the old mind?

7 Eye Tracking Traps to Avoid:

1. Underestimating the effect of what you ask people to do on where they look.

• Be careful what you’re asking them. Look for this/that/the other thing … or just let them do it on their own
• i.e.: the Yarbus Visitor Study

2. Assuming that where people are looking is what they are paying attention to.

• New research by Larson 2009: tested peripheral vision vs. central vision. Eye tracking uses central, but peripheral is very important (which is why anything blinking is annoying). The theory is that this is from our evolution
• The study showed deteriorated images of rooms. If it was deteriorated in the center, people could still identify the room. If it was deteriorated in the peripheral people could not identify the room
• Conclusion: periphery is important!

3. Underestimating the effects your protocol.

• If the test subject is sitting too close to screen or too far back, this will throw off data.
• These studies must be  exacting!

4. Underestimating time needed to analyze data. Analysis paralysis .

• You get a LOT of data (yuck!)

5. Underestimating time/cost to perform the study.

6. Overwhelming client with the data.

7. Neglecting to draw useful, meaningful decisions and actions from the study.

“You can use all the quantitative data you can get, but you still have to distrust it and use your own intelligence and judgment” –Alvin Toffler

There you have it, a nice piece of heat map meat, just take it with a grain of salt.

photo credit: jennaddenda

Bottom line? Utilizing and understanding the analytic data behind your website traffic is absolutely essential if you plan on making money. The Introduction To Analytics session at Search Engine Strategies New York left the audience with a depth of courage to explore Google Analytics (GA), five elements of a CEO-worthy report, the best KPIs to measure and incorporating other analtyic data and tools from diverse sources. 

Moderator, Jeff Ferguson, SES Advisory Board & Senior Director, Online Marketing, Local.com introduced the solo speaker John Marshall, SES Advisory Board & CTO of Market Motive. Marshall ended up in Online Marketing by accident and hated the primitive tools for the early web years so he started a little known company called ClickTracks and developed the Overlay Report to see where people click on your site. (Psst! You can find it now in Google Analytics)

I Feel Your Pain… (but quit whining!)

• If only we had more reports.
• If only the data was more accurate.
• If only IT could tag the pages.
• If only I didn’t NEED to tag the pages.

Sorry, there is no one-size-fits-all when it comes to web analytics. (But, that’s a good thing!)

5 Elements of a Great Analytics Report:

1. Key Performance Indicators (KPIs)
2. Segments
3. Context
4. Other sources of data
5. Bring it all together

These are not a prominent and for a reason… so you can custom tailor analytics to your own business!

Element #1 – KPIs

• Key Performance Indicator (fyi “hits” are pretty much useless)
• CEO should understand them
• 3-5 works best
• Traffic? (no, no, no)

Marshall’s Favorite KPIs

• Bounce Rate
• Conversion rate
• Average time on site
• Task completion rate
• Share of search
• Profit per visitor

The last 3 are a little more complicated… Not much insight in GA

Measure Task Rate- use a 4Q survey, they are quick, simple and very insightful.

• What is the purpose of your visit to our website?
• Were you able to complete your task?
• If you were not able to complete your task, why not?

Surveys tell you why things happen.

• Web analytics can only tell you what happend
• Give users the chance to enter open text

Share of Search

If traffic is rising slower than the rate of searches, um, well, you’re traffic is actually going down because it’s not rising as much as search. So, yeah, sorry… re-cork the wine and save it for another day.

Profit Per Visitor

• Beware of ROI (cost of goods! DOH! Google Analytics has no clue about your COG)

Element #2 – Segmentation

• What it’s not
• What it might be, depending how you look at things (especially if you come from traditional direct marketing)
• Segment based on intent, buying v. researching (Don’t disregard those who exit without converting)
• Segment your exits (ie hotels: people who are interested in weddings probably aren’t booking online…)

Google Analytics – Advanced Segments – Jackpot!

Analytic Segments Abound!

5 Segment Ideas:

• New v. Returning
• Keywords: brand v. product

Element #3 – Context

• Annotations (right under the graph)

• Persuasive copy with supporting facts (some people do actually like to read)

Element #4 – Multiple Sources of Data

• Not everything is in GA
• Social Media (Not easy to measure, commercial tools are best: TrackUr or Radian6)
• RSS (aka your blog – key metric = number of subscribers. You should be using Feedburner, like, now)
• Video Playback (If you host your own, Flowplayer has a GA plugin, but you need to call up IT to hook you up)
• Event Tracking
• YouTube Insights
• AB Testing

Element #5 – Bring It All Together

• Make reports brief and insightful
• Use facts not opinions
• Scannable text with details
• Data from multiple sources
• Stitched together in one single e-mail
• Significant human effort is required (get over it and allocate resources)
• Lovingly hand-tooled works best

Ok, so you’ve spent painstaking hours generating beautiful analytics reports, what happens to them?

The Agency

• Uses reports to explain economic impact of events
• And the consequences of inaction

Bonus Element: Read any book by Avinash Kaushik

Spend Money on Training, Augment with Free Resources

• Web Analytics Association
• Web Analtyics Wednesday real life social networking/commiserating for web analysts
• Twitter: #measure

Marshall’s Top Tops

• More reports wont help
• Decide which analytics work best for your business – for entertainment, decision making, job justification
• You need help from IT
• Install WASP to Firefox to view any website’s analytics tags (stealth!)
• CLICK AROUND! You can’t break anything in GA
• Offline Conversion? Use time on site, it’s a solid indicator

At first gape, these questions seem easy, yes?  “Of course, yes, socialize everything” you shout!”  “After all, isn’t the ‘net  all about social media these days?” How could it be wrong to ever consider omitting the all-powerful and ubiquitous social media click-me-now badges?

Caveat:  We understand that as social-trust augments and even partially supplants trust rank in how content is ranked by search engines, having influential tweeps and and wielding one’s own street cred’ is of paramount importance. This article is not about whether social media participation is important. Of course it’s important.

However when herding traffic to social KPIs, there can be implications in how other crucial KPIs are impacted,  serious analytic concerns and business decisions at hand.  There’s no one size fits all.  While it’s often a good decision to drive traffic from landing pages and email blasts with “follow me/friend me”  links, there a number of issues to consider–especially when socialization is not the primary KPI.  For the sake of clarity, let’s define secondary KPI:

“Secondary KPI” is an additional goal a) if the primary KPI is not reached or b) in addition to the primary goal.

Analytics & Outbound Links Exiting Directly to [Community]
(Third party social assets like Facebook, Twitter, YouTube, etc..)

There are a few analytic problems to sort out, so we’re all on the same page. So far as tracking socialization as either a primary or secondary KPI directly from an email, how do you measure success exactly?  What are viable metrics to track the outbound click (from email or landing page ) directly to [Community]

• First, we all know It’s fairly easy to track an outbound click directly to [Community] from an landing page or email. Google Analytics does not track exit clicks, in the form of destination URL, out of the box. It can be accomplished with a hack.  Most email platform analytics track outbound clicks and destinations by various methods. If technology is lacking, you can always tag outbound links to [Community] and use a script on a domain you track using redirects. Unfortunately tracking the outbound link is not enough data.
• Once users get to  [Community], unless you own [Community], you can’t directly associate clicks from that email (or landing page) with behavior in  [Community] like fanning, grouping, sharing, signing up for an app’, any desired action, etc…How do you measure the KPI?
• We must depend on less empirical, though somewhat effective correlation methods to track the ROI of direct links to [Community] from emails and landing pages.
• We like this formula: (Exits to [Community] Per Day) Graphed to (Signups/Follows/other actions Per Day). We need to see a correlation of escalating traffic and Signup/Follows/Actions. Good testing can make this, otherwise speculative metric, useful. So far as the report all I personally need to see is lines lines moving from left to right on a graph.

• Graphic email exit maps show how traffic bleed and spray effects conversion. Similarly analytic overlays illustrate how users click out from an HMTL page.  Show us on a chart  please. Does the traffic forsake the commercial funnel for the social click? Is that the desired action for the page? Are we bleeding conversions?

• 13 different exit options are nice in a pretty HTML email, but doesn’t one of the paths have more value unless the email is about general branding? If not, should one path  be designated as the primary KPI?  We market for a reason usually. Sometimes good marketing is about removing customers’ options. Herd them like sheep we say.
• If selling or hard-core marketing is the KPI, we often advise that client’s insure that “being social” is always the secondary KPI, so long you can prove it does not distract from the primary conversion. Sometimes putting the links to [Community] should be on the thank-you.php page or on the next page in sequence IF users don’t convert.
• Sometimes it makes sense to sacrifice conversions for happy social BFF pals, but make that decision intentional, data driven and based on real business priorities.
• Never underestimate the value of conversations and making friends. To this author’s mind, socialization should nearly always be, at minimum, a secondary KPI.

Our General Rules:

• I usually want to see traffic I pay for go to a landing on a site I control first, even if it’s from a little Facebook button in an email or landing page.  I don’t own Facebook and ultimately we can’t control it, only work in harmony. The exception is when socializing is the primary KPI. In that scenario it can make sense to cut down on click-count to primary conversion. All the normal caveats regarding the limitations of tracking behavior in third party sites apply.
• Should there be Facebook buttons in every email? Right! Of course there should be…That’s easy to say right? Not…I.M.H.O. sometimes we should place buttons, even much of the time… but not all the time.
• When we do place buttons, consider herding traffic to our feed or landing page, which prompt  FB savvy visitors to login using FacebookConnect.  Then they’re already logged in with a few clicks.
• Sometimes email blasts and landing pages are rather guerrilla in their intent, with immediate, even difficult financial objectives. Saying that we should “always” point them to Facebook like saying there should “always” be PPC,  “always” be Press Releases or always be in Forums, etc…That’s not a mature approach as these sorts of absolutes ignore other business considerations.
• Is the real question here is what are you doing with the Facebook friends you already have? Are they engaged? What’s do their offpage engagement metrics look like? What percentage of buzz surrounding certain content is on site, on page, off site, where, how often, when, who…and how influential is that “who” guy anyway?

Not many humans are social 24/7, nor should marketers be. We’ve even had times where we recommended a nice tight little email/landing page funnel that, instead of spraying traffic in general (albeit good) directions all over the Internet, we supply fewer options to focus.  Honestly dude, sometimes we just don’t have time, inclination or money to be social .

Can’t Squeeze Social Blood
This is especially true when a marketer is engaging in activities which barely have associated analogies in physical life.  For instance, there are no gigantic “Laundromat” analogy-applications on Facebook because real people actually tend to be disengaged and separate when washing clothes in public. Go figure…

Social Media Mirrors Physical life. As I think about it, there are very few analogies in physical life that line up with “Download $2 Walmart Coupon.”  Ok, maybe some guy wearing sandwich boards or a leaflet temp’ in Times Square. Sure their occupation is noble but we don’t ever end up…umm….hanging out, hooking up, you get it.

Coupon clipping in physical life is cool but humans don’t tend to physically congregate around the theme. Does this mean that it’s not a good idea to connect with customers at any given time…like while purveying coupons? Nope. It’s usually a great idea to make friends.

Should marketers attempt to socialize every single impression in any channel? Or, are there sometimes compelling reasons to avoid impacting the conversion funnel? There are so many channels, it’s hard to imagine that it’s always appropriate to place those link to Facebook and Twitter.

Don’t get me wrong. I’m a huge advocate and participant in social media.  Our agency has a humbling roster of SMO (social media optimization) clients, who inspire the hell out of us. SMO is crucial, especially at the intersection SEO.

One thing for sure, there’s “no one-size-fits-all” policy.  Let’s test and push the social envelope. Let’s always remember to place our customers in a well laid funnel, ask for the money and be careful where we fragment the objectives, for any reason.