Author Archive

Intelligence Takes a Step Forward with Major Contributors

Thursday, November 4th, 2010 by Nick Iyengar
Google Buzz

The Intelligence feature in Google Analytics was designed to streamline your analysis process by proactively highlighting important changes in your data. In addition to generating automated alerts for you, Intelligence allows you to create custom alerts based on changes to your site’s metrics, like bounce rate or total visits. For example, you can set up a custom alert so that if your site’s visits go up by 70% day-over-day, Intelligence sends you an email to let you know. This is a great way to stay on top of important trends on your site, but what Intelligence never provided was the why behind the change. You had the what, but it was up to you to manually review and segment your reports to find out the cause of the change.

Today, Google announced “Major Contributors” for custom alerts, which represents a major step forward for this feature. Now, when you’re reviewing your alerts, you’ll be able to drill down and see the specific segments of your traffic that caused the change. In other words, instead of simply being notified that traffic is up 70%, you’re going to be able to see which segments of your traffic drove the increase. Which traffic source? Which landing page? Which region? With the major contributors feature, you’ll get answers to these questions as soon as you know a change happened.

Seeing the drivers of change on your website automatically saves you time and effort, which you can instead spend planning your next steps. Reacting faster to important trends on your site will help you take advantage of opportunities and address potential problems. To get started with custom alerts, try using some of Google’s handy custom alert templates.

To stay on top of Google Analytics news and to receive more of our tips and tricks, subscribe to our feed and follow WebShare on Twitter.




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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Google Analytics Adds Weighted Sort

Saturday, August 28th, 2010 by Nick Iyengar
Google Buzz

The stream of new Google Analytics features coming out of the Googleplex continues, and that’s what we like. Recently Google announced a helpful feature called Weighted Sort, which helps efficiently surface actionable data while helping you avoid meaningless outliers.

One of the innate issues with using ratio-based metrics (bounce rate, conversion rate, etc.) is that when you sort, you return all of the outliers – the 100%’s and 0%’s, even when the sample size is tiny. Let’s say you want to figure out which AdWords keywords have high bounce rates, so you can adjust your bidding, landing pages, etc. Sorting by bounce rate, you’ll get something like this:

Of course, this isn’t what you were trying to do. What you actually want to know is: which keywords most need the most optimization attention? In the past, you would have had to manually create an advanced filter to specify that all returned results have more than X number of visits. That works fine, but it takes more effort, and we don’t like that.

Now, we can simply check the “Weighted Sort” button and – voilà - Google’s new sorting algorithm automatically surfaces the most significant results!

That’s really all there is to it. A couple of things to keep in mind:

  • You can use weighted sorts on other metrics, too: conversion rate, exit rate, % new visits, etc.
  • You’ll notice that the entries in your table are no longer strictly in order. Of course, that’s because you’re no longer sorting based only on the metric – you’ve asked Google to take other factors, like sample size, into account.

Questions? Cool use cases? Leave them in the comments for us, and for more tips, tricks, and updates, don’t forget to subscribe to our feed and follow us on Twitter!




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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Get Access to Optimizely’s Private Beta

Friday, August 6th, 2010 by Nick Iyengar
Google Buzz

After our recent blog post, WebShare readers may already be familiar with Optimizely, a brand new A/B testing platform that’s currently in private beta. Today we’re pleased to announce that WebShare readers can gain access to the private beta by signing up and using the invitation code WEBSHARE.

To sign up, simply head over to www.optimizely.com/beta and fill out the sign-up form. And remember: if you ain’t testing, you ain’t trying.




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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Limits to Advanced Segmentation in Google Analytics

Thursday, August 5th, 2010 by Nick Iyengar
Google Buzz

Today I stumbled upon an undocumented (or at best, minimally-publicized) limitation to Google Analytics’ advanced segmentation feature. It’s hard for me to knock what I think is GA’s best feature, but I’ve found that I can only create 100 advanced segments at a time. That may sound like a lot, but when you have more than a few Google Analytics accounts, it’s easy to start creating a lot of segments for yourself. In case you run into this like we often do at WebShare, here’s what you need to know and a workaround you can use.

In addition to the limitation to the number of segments, there’s an annoying little glitch when you try to create your 101st segment. Let’s say you’ve laid out your segment, named it, and tested it, as shown below:

Once you try to save your segment, you’ll end up receiving the following error. Notice how in addition to giving you the error message, Google wipes out your segment. It’s a minor thing, but it would be nice for Google to preserve our segments so that we could open up a profile in another tab and delete a pre-existing segment.

To be fair, there actually is a small warning notification when you try to create a 101st segment. It’s not very visible, though, so be careful.

As a workaround, you can create a “dummy” second login to use for GA. For example, if your username is user@example.com and you’ve run out of segments, create a new username for yourself under “user+1@example.com” or something similar. Note that this works for any GMail account, but may not work on other email platforms. If that doesn’t work for you, simply create an entirely new login to get beyond 100 segments.




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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5 Helpful Custom Alerts for Google Analytics

Saturday, July 24th, 2010 by Nick Iyengar
Google Buzz

One of Google Analytics’ under-appreciated features is Custom Alerts, which allows you to receive a notification from Google any time certain metrics fluctuate beyond the bounds you set. Custom Alerts is a great way to avoid this:

In this case, we can see that no conversions have been recorded at all for several days. This kind of thing happens frequently, in part because there are so many potential causes: changes to the website’s goal URL, the addition of a filter to a GA profile, the removal of the GA tracking code, etc. Without custom alerts, you’re only able to detect these kinds of issues as frequently as you log in, which may not be every day. By setting up custom alerts, you’ll be able to diagnose and address these issues much more quickly. Let’s take a look at a few of the most useful custom alerts.

Custom Alert #1: Goal Conversion Rate Decreases

As you can see below, Google Analytics gives you several ways to set up your alerts. In this case, I like to use the “% changes by” condition so that if my goal conversion rate decreases by more than 80%, I get an email. It’s possible that my site could just be having a bad day, but an 80% drop in conversion rate is a pretty good sign that I need to investigate what’s going on.  To set up this alert, click on “Intelligence” in your reports navigation menu. Then, find the “Create a Custom Alert” link.

Next, you’ll be taken to the alert setup wizard, which is awfully similar to the advanced segmentation wizard (which you should all become familiar with!). Choose the segment of traffic to which you want to apply the alert, and then set your conditions. Here’s how to set up our first alert.

First, we need a name for the alert. Next, we choose the profiles for which the alert will be set. Then, we choose between making this a daily, weekly, or monthly alert; for this alert, daily is the most useful. Then, importantly, we need to make sure we check the box that says “Email me when this alert is triggered.”

Next, you’ll set the various conditions for your alert. For this alert, we’ll want to make sure the alert applies to all traffic. We choose “Goal Conversion” rate as our metric, “% decreases by more than” as our condition, 80% as our value, and the previous day as the comparison value.

Press “Create Alert” and you’re all set! Now that you know how to set up custom alerts, let’s run through some more alerts that are frequently useful.

Custom Alert #2: Revenue Decreases

If you’re an e-commerce site, you should have revenue tracking set up as well as “static” goals like contact forms, etc. Setting up our first goal won’t tell you when your actual revenue is fluctuating; you’ll need to set up a similar alert, but with revenue as your key metric.

Custom Alert #3: Traffic Decreases

Hopefully, if your website is down for an extended period, you won’t need Google Analytics to tell you about it. However, setting up alerts based on traffic decreases is a great way to be alerted when something has gone wrong with your Google Analytics implementation. The following scenario happens regularly: a website update is pushed out, and your GA tags are adversely affected somewhere along the way. Although your site doesn’t go down, you see your visit metrics flat-line. To minimize the time for which you’re affected by issues with your GA implementation, set up an alert based on visits decreasing by more than, say, 60%.

Custom Alert #4: SEO Metrics

If you’re like most organizations, organic search traffic is probably something you care about quite a bit. Want an easy way to keep track of how visible your site is across the various engines? Set up a weekly or monthly alert based on organic traffic only (rather than all traffic). Try one alert for decreases of more than 20%, and one for increases of more than 20%.

Custom Alert #5: Monitoring Brand Terms

Measuring response to branding efforts can be difficult, but one good approach is simply to measure how searches on your brand terms change over time. This is super easy with Custom Alerts. Set up a weekly or monthly alert that’s based only on the specific keywords you care about, and have Google send you an email if your metrics go up or down 20% week-to-week or month-to-month.

We hope these ideas for Custom Alerts will be useful for you, and that they get you thinking about what other kinds of metrics could be helpful for your organization. To get more analytics tips and tricks, subscribe to our RSS feed, and don’t forget to follow us on Twitter.




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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First Look: Optimizely

Friday, July 23rd, 2010 by Nick Iyengar
Google Buzz

One of the cooler things about working at WebShare is the fact that we regularly get our hands on the newest, most exciting tools in the analytics and testing industry. One tool we’re especially excited about right now is Optimizely, a brand new (it’s still in private beta) A/B testing platform designed to make testing easier than it’s ever been before.

At the core of Optimizely’s promise is its WYSIWYG (What You See Is What You Get) variation editor, which allows you to create variations of your original page with drag-and-drop simplicity. You can easily edit text, rearrange your content, re-size images and buttons, etc., all without having to do any coding whatsoever. Below is an example of a variation of our Seminars for Success microsite: I moved the “Reserve Your Seat” button, our major call-to-action, to a more central location. Then I moved our dates and locations information, which we know is among the most important information on the page, to a more prominent location. It’s nothing revolutionary, but it could be different enough to show a significant difference in performance, and it took me a grand total of about 45 seconds to do.

Original:

Our original page

Variation:

This core benefit strikes at one of the biggest hurdles to efficiently testing your site: the creative process. Many small to medium-sized businesses simply don’t have creative resources in-house, which makes developing variations a major challenge. Optimizely minimizes that issue by allowing non-creative resources (such as myself) to quickly and easily generate variations that are significantly different from the original.

When you’re ready to launch a test, all you have to do is install one compact block of JavaScript into the <head> of the page you’re testing. This simple, streamlined implementation process adds even more weight to Optimizely’s claim that they provide “A/B testing you’ll actually use.” With your test running, Optimizely will measure user engagement with each variation, and report back you on the winners and losers.

As you might expect with any raw, beta-stage product, Optimizely is missing some things we hope it’ll incorporate in the future. There’s no word yet on whether Optimizely will handle multivariate testing. The WYSIWYG editor can be clunky and unpredictable. It’s difficult to save your variations while you work. There are no undo, copy, or paste buttons. But all in all, the concept behind Optimizely is clear and compelling. There’s a huge market for a simple A/B testing platform, and we think Optimizely could be well-suited to serve that need. To sign up for the beta, head over to www.optimizely.com, and to stay on top of all the latest news in the analytics world, don’t forget to subscribe to our RSS feed or follow us on Twitter.




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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New AdWords Reporting in Google Analytics: An In-Depth Look

Tuesday, June 29th, 2010 by Nick Iyengar
Google Buzz

Many of you may have recently noticed a new addition to your Google Analytics account: a revamped AdWords reporting suite. In the past, GA provided AdWords reporting via two reports: the AdWords Campaigns report and the Keyword Positions report. These were, and are, two of the most powerful reports for AdWords advertisers, but Google has now created a new, expanded set of AdWords report. Today we’ll be taking a detailed walk through the entire AdWords reporting suite, looking at the following new features. Feel free to skip ahead to the parts that interest you most!

  1. New AdWords “Overview” Page
  2. Changes to “AdWords Campaigns” Report
  3. Additional Segmentation Options (dimensions)
  4. New AdWords Reports

First, a quick refresher on how to find these new reports: after you log into GA, click on “Traffic Sources,” then click on the AdWords (Beta) section, as shown below.

New AdWords “Overview” page

When you navigate to the new AdWords section of GA, the first thing you’ll notice is that it now has an “Overview” report, just like the other main sections of GA (e.g. Visitors, Traffic Sources, Content, etc.). This tells you something about the importance of AdWords in Google’s eyes, but it also provides a much-improved ability to get high-level AdWords data at a glance. By default, instead of seeing simply visits plotted out over time, you’ll now see your AdWords click-through rate (CTR) plotted against your website’s bounce rate. This gives you the ability to immediately understand the efficiency of both your AdWords campaigns and your AdWords landing pages. Of course, you can customize the metrics that are displayed, and you can easily opt to simply view one metric at a time rather than two. Below the line graph, you’ll also get a snapshot of a series of key metrics: visits/clicks, conversions, revenue, and return on investment (ROI).

Changes to “AdWords Campaigns” Report

To analyze AdWords on a campaign-by-campaign basis, the AdWords Campaigns report will still be your “headquarters.” Note that it’s been renamed; it’s now simply the “Campaigns” report, but structurally it’s the same as it has always been, in that it allows you to drill down from campaign to ad group to keyword. So what’s substantively different?

First, you’ll notice that the metrics you see on the Site Usage tab have changed. A big part of what Google is trying to do is help GA users streamline their analysis processes. By including Goal Completions (conversions) and Revenue on the Site Usage tab, you no longer have to navigate through three tabs to get these metrics for a given AdWords campaign. It’s not a complex change, but it certainly helps you work more quickly and efficiently.

The biggest and most exciting change to the Campaigns report, though, is the addition of several new segmentation options (also known as dimensions) that are extremely helpful.

Additional Segmentation Options (Dimensions)

Google Analytics has long been known for the segmentation flexibility it provides, but that doesn’t mean we don’t always want more options. Fortunately for us, Google has now opened up nine – count ‘em! – dimensions for marketers and analysts to use when analyzing AdWords. Today we’ll take a look at several of these and examine how they can be useful for us.

Ad Distribution Network

As many of you know, you can use your AdWords campaigns to distribute your ads across three major platforms: Google.com search, Google search partners like AOL and Ask, and the Google Content Network (recently renamed the Google Display Network). These platforms often perform very differently for different advertisers, so it’s crucial to understand exactly where your ads are being shown and how they’re performing. Now that we can segment by Ad Distribution Network, it’s very easy and efficient to do this analysis.

Here we can see that for this particular advertiser, Google search is most efficient from a Per Visit Value standpoint, followed by Google search partners and finally the Content/Display Network. Of course, you can drill down from the account level to an individual campaign, ad group, or even keyword! Performing this kind of analysis has major implications for your AdWords budgeting, bidding, and targeting decisions.

Match Type

Google provides three match types for buying keywords. Broad Match gives Google the freedom to automatically show your ads for search terms it thinks are relevant to you. Phrase Match forces Google to only show your ads for queries that include the bid phrase intact. Exact Match, as the name suggests, forces Google to display your ads only when the user’s search query exactly matches the bid term. For years, marketing gurus have broadcast theories and “best practices” regarding which match types you should be using. Now you can free yourself from opinions and let the data speak for itself! Which match types work best for you?

For this advertiser, Exact Match is working most efficiently in terms of Per Visit Value, followed by Broad and Phrase. When you do this analysis for yourself, you may find something very different. You may even find that different match types work best for different campaigns you’re running. Regardless of what you see, you’ll be newly armed with information that’s critical to bidding on keywords efficiently and effectively.

Matched Search Query

This is a big one, people. If you’ve been involved with AdWords for longer than a few months, you’ve probably had a moment where you thought something along these lines: “Google was showing my ads for those keywords? I’m not bidding on those!” Broad match can be a great feature in that it saves you time (you don’t have to bid on every single possible search query) and helps you find new keywords, but just as Broad Match giveth, Broad Match taketh away.

Here’s an example. Let’s say you’re bidding on the Broad Match keyword “Florida vacation.” On the plus side, Broad Match will automatically show your ads when people search for “Florida vacations,” “vacations in Florida,” and other similar variations. However, Google is not perfect. Your ads could be displayed to people looking for things that are only vaguely relevant (“Florida flights”), or even completely irrelevant (“Cancun all-inclusive”).

Google’s gotten a lot better about providing transparency into their Broad Match technology. The Search Query Report in Google AdWords is a nice report that shows you the exact term that a user types in, regardless of what your bid term actually was. But the SQR only goes so far. It can’t show you metrics like bounce rate, revenue, and per visit value. Now that we can segment our GA data by Matched Search Query though, this Dark Age is finally over!

Even though I’ve used scare tactics to get you interested in this new segmentation option, don’t forget that this kind of analysis can also help you find great new keywords that you didn’t know about. Use this report to beef up negative keyword lists, but also to find hidden gems that can make your AdWords campaigns more profitable.

These three dimensions are probably going to be the most useful additions for most people, but be aware that you can also segment your GA data in six more new ways:

Placement Domain

Placement URL

Ad Format (text vs. image, etc.)

Targeting Type (keyword vs. placement, etc.)

Display URL

Destination URL

New AdWords Reports

On top of all the new segmentation options Google just gave us, we’re also getting a series of entirely new reports: Keywords, Day Parts, Destination URLs, and Placements. They’re pretty self-explanatory, but let’s take a quick look and understand how they help us.

Keywords

This report simply shows us our AdWords keywords regardless of campaign. In the past, if I wanted to analyze my top 10 (by traffic) AdWords keywords, I’d have to do one of two things. I could either create an advanced segment, then use the generic Keywords report under Traffic Sources, or use the AdWords campaigns, and drill into individual campaigns until I found my top 10 keywords. Now, however, Google’s streamlined this process by simply providing a report that does this for us.

Day Parts

Don’t let the simplicity of this report fool you into thinking it’s not extremely useful. GA now makes it very easy to see how your AdWords ads perform based on the hour of the day. Of course, AdWords allows us to alter our bids (or even turn off our ads entirely) based on the hour of the day. Using the Day Parts report, you’ll be able to quickly decide which hours are your “peak” hours, and which hours are the ones where you should scale back your bids, or pause your ads. I’ve managed tens of millions of dollars in AdWords spend over the last several years, and at least 50% of the companies I’ve worked with didn’t use the ad scheduling feature, so use this report, and once again arm yourself with the information you need to run your campaigns more efficiently and profitably.

Destination URLs

This is a nice, basic report that helps us quickly understand which landing pages are working and which aren’t. Struggling to figure out which pages you should test with Google Website Optimizer? This report will point you in the right direction.

Placements

If you’re running ads on the Content/Display network, and using placement targeting rather than contextual targeting, you’ll know that up until now, your placements actually showed up as part of the Keywords report. A quirk of GA that did not fall in the “charming” category! Now you have a report where you can easily split out your placements.

If you’ve been using the new AdWords reports to your advantage, tell us how in the comments! And don’t forget to subscribe to our feed our follow us on Twitter to get more WebShare tips and tricks.




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

See more posts by Nick Iyengar

Capturing First-Touch Source Information with Custom Variables

Wednesday, May 19th, 2010 by Nick Iyengar
Google Buzz

Since Google Analytics released custom variables last October, we’ve been finding all kinds of ways to use this flexible, powerful feature. From accomplishing content groupings to tracking the count of purchases by repeat buyers, custom variables have opened the door to both new data in GA and new abilities to segment our data.

One of our favorite uses for custom variables is storing first-touch traffic source information. As you may know, the default model for conversion attribution in Google Analytics is last-touch. In other words, recorded conversions and transactions are attributed to the last traffic source (with the notable exception of direct traffic, which will not override another traffic source). Therefore, it’s difficult to get an understanding of how other traffic sources contribute to conversions. Custom variables have made it much easier to get as this kind of insight with Google Analytics.

Beware this issue!

When deploying custom variables to track first touch, we’ve uncovered an interesting aspect of Google’s 64-character limit for custom variables. First, some background: to record and store first-touch source information, you need to parse GA’s _utmz cookie and store the relevant information in the _utmv cookie, which is dedicated to custom variables. In doing so, it’s easy to hit the character limit (consider that you’re potentially storing source, medium, campaign, keyword, and ad content information).

Here’s the rub: if you try to store more than 64 characters’ worth of information in the _utmv cookie, Google doesn’t simply cut you off at 64 characters and send as much data back as possible. Google flat-out won’t send your custom variable at all!

To avoid this, here are some tips:

1. Choose a short name for your custom variable’s “key,” like “FT” for first touch. The custom variable uses a “key/value” structure in which the key is basically a category of data; in this use case, your key is just first touch, while the value is something like google/organic/big blue widgets. By choosing a short name for your key, you’ll save as many characters as possible for your actual value.

2. Perform a RegEx (regular expression) search-and-replace on the value of your key/value pair to keep only characters that do not require URL encoding. You’ll save yourself many characters by avoiding the need to URL-encode some characters.

3. Trim the length of the value string to 64 characters minus the length of the key. In other words: Value = 64 – (Key length).

4. Finally, go ahead and call setCustomVar() to store the first-touch data in a custom variable.

Here’s the code you’ll need to parse the _utmz cookie and then accomplish steps 2 through 4!

<script type=’text/javascript’>
//Used to obtain a value from a string of key/value pairs
function _uGC(l,n,s) {
if (!l || l==”" || !n || n==”" || !s || s==”") return “-”;
var i,i2,i3,c=”-”;
i=l.indexOf(n);
i3=n.indexOf(“=”)+1;
if (i > -1) {
i2=l.indexOf(s,i); if (i2 < 0) { i2=l.length; }
c=l.substring((i+i3),i2);
}
return c;
}
//Retrieve campaign and referrer info from the _utmz cookie
var z = _uGC(document.cookie, ‘__utmz=’, ‘;’);
var source  = _uGC(z, ‘utmcsr=’, ‘|’);
var medium  = _uGC(z, ‘utmcmd=’, ‘|’);
var term    = _uGC(z, ‘utmctr=’, ‘|’);
var content = _uGC(z, ‘utmcct=’, ‘|’);
var campaign = _uGC(z, ‘utmccn=’, ‘|’);
var gclid   = _uGC(z, ‘utmgclid=’, ‘|’);
//Replace empty values (marked by a dash) with an empty string
if(source==”-”){source=”"};
if(medium==”-”){medium=”"};
if(term==”-”){term=”"};
if(content==”-”){content=”"};
if(campaign==”-”){campaign=”"};
//If gclid is present, explicitly set source/medium to google/cpc
if (gclid !==”-”) {
source = ‘google’;
medium = ‘cpc’;
}
//Build utmString
var utmString = source;
utmString=utmString+”!”+medium;
utmString=utmString+”!”+campaign;
utmString=utmString+”!”+term;
utmString=utmString+”!”+content;
//Replace URL-encoded ‘spaces’ with dashes
utmString=utmString.replace(‘%20′,’-');
//RegEx to retain only whitelisted characters
utmString=utmString.replace(/[^a-zA-Z0-9-~!*_.]/g,”);
//Set string to specific length
utmString=utmString.substr(0,62);
//Set first touch information if not already there, using slot 3
var fT=pageTracker._getVisitorCustomVar(3);
if(!fT){
pageTracker._setCustomVar(3,’FT’,utmString,1);
}

</script>

Finally, a word on why first-touch traffic source information can be so valuable. GA’s default attribution model gives you only one view of how valuable various traffic sources are for you. Getting another view can only help you, especially because GA’s default model tends to undervalue traffic sources that may not be as prone to immediate direct response, but could still be adding value for you. Examples of this kind of traffic commonly include display advertising (e.g. Google content network, other banner campaigns) and social networking. By storing first-touch source information, you give yourself the ability to perform a more holistic assessment of the value of these kinds of traffic.

Be aware that this does not only apply to storing first touch information in the cookie. You should always make sure that your cookie length is not too long and does not contain any special characters.

If you have questions on first-touch source information or our solution above, feel free to leave them in the comments. To get more analytics tips and tricks, don’t forget to subscribe to our feed and follow us on Twitter!



Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

See more posts by Nick Iyengar

New AdWords Search Funnels

Thursday, March 25th, 2010 by Nick Iyengar
Google Buzz

Yesterday Google announced “AdWords Search Funnels,” a major new component for its AdWords conversion tracking package. Search Funnels is an important new feature because it represents Google’s first foray beyond last-click conversion attribution for AdWords. Historically, AdWords conversion tracking has always simply looked at the most recent AdWords keyword/ad that was clicked on prior to a conversion, and given that keyword/ad credit for the conversion. While this data is by no means inaccurate, in many cases it is incomplete. Let’s take a look why that is and explore some of the ways you can make Search Funnels data actionable.

Legacy AdWords Conversion Attribution: What’s Missing?

Many online purchases are not “impulse buys,” so whether you’re an e-commerce website or a lead generation landing page, there may well be a bit of a research period that a user must go through before eventually converting on your site. For our purposes, let’s pretend you’re selling stays at an all-inclusive resort in the Caribbean. You’re going to be charging your customers’ credit cards for thousands of dollars at one go, so your users may spend weeks, or even months, researching their vacation before deciding to purchase.

If your users have been researching their vacation for weeks, they’ve likely searched on several of your keywords, and seen many of your ads. With the legacy AdWords attribution model, however, you would only get conversion data on the last keyword and ad in that entire sequence.  What you probably would like to know in this scenario is how much, if at all, your “top-of-funnel” keywords are contributing to future conversions.

Here’s a specific example. Given the AdWords attribution model, it’s common to see conversion data that looks roughly like the following:

Keyword Conversion Rate
“purchase all-inclusive vacation in Aruba” 5%
“Caribbean vacation” 0.25%

On the surface, “Caribbean vacation” looks like a vague, generic keyword you might not want to keep spending money on. But there’s probably a lot of traffic there, and a lot of your customers may start the research process with generic keywords just like that. When they’re finally ready to buy, they’ll likely be using more specific keywords, and with the AdWords attribution model it makes sense that these kinds of keywords will have higher conversion rates.  If that’s the case, then the right decision is that you’d want to make sure you continue to get in front of people when they start their research with generic keywords like “Caribbean vacation” – in spite of what looks like a miserable conversion rate. With the traditional AdWords attribution model, it’s tough to make this decision given the numbers you’re looking at.

On top of that, Google Analytics attributes conversions differently from AdWords conversion tracking. While AdWords looks at the last AdWords keyword before the conversion, Google Analytics looks at the source of the actual visit that generated the conversion – even if it’s not AdWords. What if your user clicks on your AdWords ad, then a week later does a search on Yahoo! and clicks on your organic result before finally converting? AdWords will report a conversion for that last AdWords keyword, but Google Analytics will attribute the same conversion to the last-touch, which in this case would be an organic search on Yahoo!.

With multiple attribution models in play, it’s easy to see how evaluating the true value of your keywords can get pretty complex. That’s a big part of why the new insight provided by Search Funnels is generating a lot buzz in the industry.

Search Funnels: A New Level of Insight

With Google’s new Search Funnels, you’ll now be able to see whether the keyword “Caribbean vacation” generates “assist” clicks, or even assist impressions for you. Assists, which Yahoo! Search Marketing has reported on for years, are defined in AdWords as clicks and impressions that your keywords and ads received prior to the user converting on your site. For example, let’s say a user searched for “Caribbean vacation” three separate times, and clicked on your ad one of those times. Then, a week later, the user searched for “purchase all-inclusive vacation in Aruba” and converted on your site. In the past, all you’d see was one conversion for “purchase all-inclusive vacation in Aruba.” Soon, however, you’ll see the following: for “purchase all-inclusive vacation in Aruba” you’ll still see the one conversion. In addition, though, you’ll see three assist impressions and one assist click for “Caribbean vacation.”

But wait; there’s more! In addition to being able to see assist clicks and assist impressions, you’ll be able to break down your conversion process by the amount of time and number of visits that it takes someone to go from initial click to final conversion.  These metrics have been available exclusively in the E-commerce reports of Google Analytics until now, and they provide invaluable insight into the sales cycle of your products and services.  Also, you’ll be able to see metrics like the number of impressions and the number of clicks it takes to drive a user from initial click/impression to final conversion.

By now you’re probably starting to see how useful this data can be in helping you make smarter, more data-driven decisions about the portfolio of keywords you buy for your SEM campaigns. To learn more about where to find Search Funnels and to see screenshots, check out Google’s new video below.

Google plans to roll out this feature to everyone over the next few weeks, so if you’ve got other ideas for how to use this data, share them with us in the comments. As always, if you want to get more great tips and tricks on AdWords, Google Analytics, Google Website Optimizer, and more, subscribe to our feed or follow us on Twitter!




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

See more posts by Nick Iyengar

Clean up Your Google Analytics for 2010

Thursday, February 11th, 2010 by Nick Iyengar
Google Buzz

It’s a bit late for a New Year’s-themed post and a bit early for a spring cleaning-themed post, but it’s never a bad time to get your Google Analytics data cleaned up. For those of you looking to do just that, here’s a “Quick Fix” checklist to put yourself on the path toward usable data.

1. Identify and resolve self-referrals
A “self-referral” is a visit for which the referring source is your own website. Self-referrals prevent you from seeing the original, valid referral information for the visits in question, so if you’re measuring ROI on advertising outlets, paid search placements, or offline campaigns, it’s important to reduce self-referrals to a minimal level.

First, make sure that every single one of your pages is tagged.  This can lead to situations where self-referrals occur.

Many self-referrals are a symptom of deploying Google Analytics without customizing your tracking code to track across subdomains (like blog.yoursite.com) or top-level domains (yourshoppingcart.com). Fortunately, this customization is fairly simple and easy to complete.

When a visitor to yoursite.com navigates, for example, to blog.yoursite.com or yourshoppingcart.com, GA’s default behavior is to set new cookies on the user’s computer, causing yoursite.com to appear as the referring website to a new visit that starts on the new subdomain or top level domain. However, by adding the following simple customization to your Google Analytics tracking code, you can ensure that GA preserves the pre-existing set of cookies, and therefore the original referral information persists throughout the entire visit.

For tracking across top-level domains:

On your first domain (yoursite.com), add the following to your tracking code before the trackPageview() call (obviously replacing “yoursite.com” with your own domain):

pageTracker._setDomainName("yoursite.com");
pageTracker._setAllowLinker(true);
pageTracker._setAllowHash(false);

On your second domain (yourshoppingcart.com), add the following to your tracking code before the _trackPageview() call (obviously replacing “yourshoppingcart.com” with your own domain):

pageTracker._setDomainName("yourshoppingcart.com");
pageTracker._setAllowLinker(true);
pageTracker._setAllowHash(false);

Now, for every link that you have on either domain that sends a visitor from one domain to the other, add the following bolded code:

<a href="http://www.a-different-domain.com" onclick="pageTracker._link(this.href); return false;">

If you have forms that submit across top level domains, you’ll need to add the following bolded code to each of those as well:

<form action="http://www.a-different-domain.com/form-processor.php" onsubmit="pageTracker._linkByPost(this);">

For tracking across subdomains:

This is MUCH easier than the above.  All you need to do is add the following line of code to your tracking code that appears on all your pages, regardless of the subdomain they’re on, again making sure that it goes above the _trackPageview() call:

pageTracker._setDomainName("yoursite.com");

For both subdomain AND top level domain implementations:

Lastly, you’re going to need to set up a filter to apply to each of your profiles so that you can see which (sub)domains your visitors are viewing in your content reports.  To do this, you’re going to create an Advanced Filter like this:

Filter Type : Custom filter > Advanced
Field A : Hostname Extract A : (.*)
Field B : Request URI
Extract B : (.*)
Output To : Request URI
Constructor : $A1$B1

To illustrate what this filter does, let’s say that you have an “index.php” on both www.yoursite.com and blog.yoursite.com. By default, Google Analytics will take all the pageviews for “index.php” and aggregate them on one line of data in your content reports. The problem here is that you want to be able to distinguish between those two URI’s, because they are NOT the same! The filter above will take “index.php” and prepend the hostname to it, so you’ll end up with TWO rows of data in your content reports: “www.yoursite.com/index.php” and “blog.yoursite.com/index.php” – and now you can see who’s viewing what pages.

Note that this will change the URI’s that Google Analytics stores, and if you have goals configured to match your old URI’s, you must update those goals once you’ve applied this filter.

With this customization in place, you’ll eliminate one of the biggest sources of self-referrals. Here’s an example of how you’ll benefit. Let’s say you’re running a Google AdWords campaign. You’ll now be able to track your AdWords visitors (and spend) end-to-end on your site, without the risk of losing track of them due to self-referrals. This is critically important for evaluating and improving the performance of any source of traffic.

2. Track all your goals
This sounds basic, but a very large proportion of Google Analytics users don’t track any goals at all, and most GA users that do track goals will only configure one or two. Now that you can have up to 20 goals per profile, you should be tracking every single goal you can think of. To do this, have a brainstorming session and write down every reason you have a website. For example, if you run an e-commerce website, your shopping cart will most likely be your most important goal, but what about tracking goals like these?

  • Newsletter sign-ups
  • Email to a friend
  • Buttons to bookmark/subscribe
  • “Contact us” submissions
  • Internal search

You could also track goals such as video views, specific content views, social media interaction, RSS feed clicks, blog comments left, and literally hundreds more. Using new “threshold goals,” you can even track time on site and pages per visit as goals.

It’s important to measure all of the value that your site provides. These “microconversions” will give you a fuller view of the performance of your marketing efforts, which will in turn help you make better decisions.

3. Tag your campaigns properly
Tagging campaigns properly is critically important if you plan to use Google Analytics to evaluate the performance of your various marketing efforts. Without proper tagging, it’s nearly impossible to use Google Analytics to evaluate the performance of marketing channels like:

  • Yahoo! Search Marketing, Microsoft adCenter and other SEM platforms
  • Banner ads, text ads, and other paid placements
  • Offline media like print, television, radio, direct mail, billboards, etc…

You can very easily link your AdWords and Analytics accounts and have Google auto-tag your AdWords campaigns for you, but for any other marketing channel, you’ll need to get your links tagged yourself. We recommend that you develop standardized naming conventions before you start to tag or re-tag your campaigns; this will promote consistency and minimize confusion and headaches down the road.

For example, for paid search campaigns, will you use “cpc” or “ppc” as your medium? For campaign names, will you use flight dates (“feb2010”), target audiences (“nascardads”) or something else? Once you have a naming convention in place, you can use Google’s free URL Builder to input your tagging parameters and get your campaigns set to go. Of course, you can always tag your links manually too. In either case, here’s what a properly tagged URL might look like for a Yahoo! Search Marketing ad:

http://yoursite.com/?utm_source=yahoo&utm_medium=cpc&utm_campaign=widgets&utm_content=smallwidgets&utm_term=little%20widget

Notice that we’ve defined the source of the traffic (“yahoo”), the medium (“cpc”, denoting cost per click), and the name of the campaign (“widgets”).  We’ve also used the optional parameters content (“smallwidgets”, which in this case is the name of the adgroup) and term (“little widget”, in this case the keyword we were bidding on).

IMPORTANT: Third party tracking mechanisms or URL shorteners often strip out these parameters, so make sure that any redirects that occur before a user reaches your landing page accept query string parameters.  If you click on your own ad and you end up at a URL like the above, you’re all set.

Cleaning up self-referrals, tracking all of your goals, and tagging your campaigns correctly will help you quickly get more accurate and actionable data in your Google Analytics reports.

For more tips, tricks, and strategies, bookmark our blog, follow us on Twitter or attend one of our Google Analytics & Website Optimizer Seminars!




Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

See more posts by Nick Iyengar