3 Advanced Web Analytics Visitor Segments: Non-Flirts, Social, Long Tail

SunshineThe last blog post shared custom analytics reports that you can use to find amazing insights faster, enabling you to create a focused, truly data driven organization.

In this blog post I want to continue the let's help make your day-to-day life better path. I'll share three advanced segments that I personally find to be of value in the process of moving from data to actionable insights. I hope you'll download and use these segments, but more than that I hope you'll learn how to create delightful analytics segments with the options you have at your disposal.

I am an unabashed segmentation fan: Web Analytics Segmentation: Do Or Die!

Without segmentation our analysis is focused on unrecognizable blobs of traffic. Total Visits. Average Page Views Per Visitor. Overall Conversion Rate. Yada, yada, yada. Boring. Useless. Life wasting.

With segmentation we focus on groups of people and we focus behavior that has logical connections (everyone who used a particular keyword, group that came via Twitter, people who viewed a TV ad, visitors who saw more than 4 pages on our site etc., etc). That helps us understand data & performance better. It helps us get data-gasms, improve ROI for our web efforts and get our bosses promoted.

How can you not love that?

Below are examples of segments that help us make a lot more sense of all the data we have and the insights that await us. You'll be able to download these segments and import them into your Google Analytics accounts and start using them right away!

Additionally, as I often do, you'll learn lots about the types of delicious analyses you can do with these segments. For good measure there is also a tutorial on regular expressions at the end (no good analyst can live without regex!).

If you use Adobe's Site Catalyst or CoreMetrics or Yahoo! Web Analytics or WebTrends or. . . you'll have enough detail below to create a segment in 5 minutes in those tools as well. Trust me, it takes just 5 minutes and, like with Google Analytics, you won't need to update your JavaScript tags or have to do extra work with IT or buy other expensive versions of their products just to do segmentation.

Let's go. . . three awesome analytics data segments. . .

#1: Non-Flirts, Potential Lovers

Did I get your attention? :)

We all obsess with our bounced traffic because it seems nutty that the person you spent so much time and love attracting to your website bounced! They did not click to see another page. They did not hit play on the video on the landing page. They did not click on a link on your landing page to your corporate site. They just left.

Here's how that segment looks:

web_analytics_segment_bounced_traffic

It is tempting to analyze these people. Where did they come from? What campaigns? What landing pages? Etc., etc.

You can find value, but to grow the business it is not prudent to focus on analyzing just the people who flirt with us.

Why not first analyze people who do engage with us?

At this point people switch to analyzing all the non-bounce traffic. This is how that segment looks (bottom right):

web_analytics_segment_non_bounced_traffic.png

[The above is a standard segment in GA, just look under Default Segments.]

Better. Ignore the flirts. Focus on everyone else.

Unfortunately that is still a "blob." It includes anyone who just had two "hits" in their visit (hits is a technical term for a page view, event, custom variable, etc., etc., more than one hit = non bounce visit).

I want us to be a lot more deliberate.

Look at the Depth of Visit report (standard report in GA in the Visitors section). It shows the distribution of the pages people see on your site (not the "silly" metric, average page views per session).

The distribution will show you the "tipping point," the point at which a core group of people decide to stick with your site after overcoming their initial "fears" (and your perhaps sub optimal pages!).

Segment that.

To use a metaphor. . . look for people who made it with you to a third date. For many sites, but not all, that's people who have seen three pages. It might take 14 pages to buy, but if they stay to three they are giving you a chance. They might read 8 stories on your non-ecommerce content site, but you note that people who see three engage for a longer time.

Here's that segment:

page_depth_engagement_analytics_data_segment

So simple right?

These 7,610 Visits were ripe with promise. Some people ultimately ended up buying, others just gave you a chance and decided not to consummate.

Rather than focusing on the bounce traffic ("flirts") it is much much more interesting and valuable to initially focus on people who give you a chance.

Where did they come from?  segmentation_engaged_traffic_sources

12.11% from Organic Search via Google. Enough? Not enough?

More questions for you to answer. . . .

What pages did they enter on? What campaigns have a higher percentage of these people? What countries? What keywords? What is the delta between content they consume on your site compared to everyone else?

Look at the row with % of Total. . .

non-flirt-traffic-content-consumption

Helps you find what they are interested in, right?

More questions to answer. . .

Do they all happen to use the comparison chart first? Do they all absolutely read the Sports section? What's so unique about them?

This an astoundingly simple segment to create. Yet analyzing visitor behavior for this segment helps you identify, and perhaps do more of the things you already know are working.

Do this first.

Here's how you can get this sweet and simple segment:

  1. Log into Google Analytics.
  2. Come back here.
  3. Now click on this link: Non-flirt Potential Lovers Segment. It will open in GA.
  4. Click on the Create Segment button to save it in your account.

If you want to share this report with others (say via Twitter / email) you can use this url: http://goo.gl/SuwKp

Have fun.

#2: Social Media, Baby!

Social media is all the rage. Suddenly Marketers have discovered that convincing people to buy their products/services or read their content or apply to university takes just two things:

    A. 140 character missives sent frequently during the day extolling the glories of the company / newspaper / university

    B. Creating a Facebook page, and then proceeding with the glory extolling

So easy. </ever so slight sarcasm>  : )

Our job is to hold the feet of these adventurous people to the warm accountability fire, right?

[Remember everything below is only if you use Twitter, Facebook et al for pimping. If you are participating in those media in the manner in which you are supposed to, conversation and adding value rather than pimping, then I encourage you to read my Social Media Analytics post to learn what the best metrics and tools are.]

The challenge in measuring social media impact on your business is two-fold.

    1. Most content gets consumed in applications (think tweetdeck, my beloved twicca, mobile etc). They don't send referrers allowing us to tie to the source with our analytics tool (any tool, GA or Omniture or CoreMetrics).

    2. Splitting out activity that we caused vs. activity that was caused by others.

My recommendation is, again, two-fold.

First, if you tweet / update / tumble links back to yourself then please for the sake of all that is holy in the world add campaign tracking parameters.

Here's the link I tweet:

http://goo.gl/myisj

It points here:

http://www.kaushik.net/avinash/2010/12/best-downloadable-custom-web-analytics-reports.html?utm_source=social-media&utm_medium=twitterfb&utm_campaign=aktw

See the campaign (utm_) tracking parameters? Trackability, sweet, trackability!! Mobile, apps, html5 pages, bring it on. All visits tracked!

[If you use Site Catalyst or WebTrends or Yahoo! Web Analytics your campaign tracking parameters won't look like the above. Check with your vendor and tag appropriately.]

Second, split your social media value analysis into two different segments. Activity caused by you and activity on your site by all social media visits.

self_driven_social_media_traffic_segment

You drag over Source and input the Value you are using to tag your SM links, in my case the utm_source is imaginatively titled social-media.

This tracking mechanism (campaign tag) is used both on Twitter and Facebook links. I can, and often do, split out Twitter and Facebook separately by using a different value in the utm_medium value. I can further segment them separately if I want. For now I want to analyze them at a higher level together.

I did pimping. I got 2,486 Visits. So what?

Easy question to answer, go to your outcomes report and apply your newly minted segment:

social_media_conversion_rates

Pretty darn pathetic, right?

Only one of the above goals is connected to a "hard" conversion (leads generated, Goal 2). The rest are "engagement" and videos played and other such goals.

Still pathetic, right?

Do you know how awesome, or not, social media efforts directly initiated by you are? It's not that hard. Go figure it out.

Oh and yes, you don't have to stop here. You can apply this segment to your amazing Page Efficiency Report, to your Visitor Loyalty and Recency reports, to your. . . well any report you have. That allows you to measure a broader view of the success of your social media efforts, rather than my effort to instantly put your feet in the fire! :)

Here's how you can get this social media segment:

  1. Log into Google Analytics.
  2. Come back here.
  3. Now click on this link: My Social Media Traffic Segment. It will open in GA.
  4. Click on the Create Segment button to save it in your account.

If you want to share this report with others (say via Twitter / email) you can use this url: http://goo.gl/fvuXP

Time to create our second, more expansive, social media segment.

As I had mentioned above, this time around we'll look at the social media to our website(s) from our efforts as well as that of all our friends / BFFs / haters.

Before you create this segment you should go checkout your All Traffic Sources report and see how your web analytics tool is capturing various channels people show up from. Based on that review of my site, here's the segment:

analytics_segment_all_social_media

A quick explanation.

Values for twitter, facebook, sphinn, stumbleupon are there for people who use web based versions of these social media websites. I can add delicious, digg etc., etc., if I want to. They are simply not that important a source of traffic for me. See why the review of the All Traffic Sources report recommended above was important?

[Some people will obsess and create a ginormous catch-all segment. But remember, you don't need to understand data from the last 10 visitors to make smart decisions.]

The value for "social-media" is there to capture the social media campaigns tagged by me. See our first social media segment above. You'll use your own tracking values.

Value for awe.sm is because for a while I was using awe.sm to auto-tag all my links. There are some latent visits which should get flushed out of the system in the near future (as I have standardized on www.goo.gl and www.bit.ly).

That's *my* All Social Media Segment.

If you are thinking: "Good lord that is messy!"

Welcome to the world of social media tracking. It is messy-ever changing-and you should know that you are going to babysit this constantly. Sorry.  [Also see comment above about needing the last 10 visitors: you don't!]

But after you create the segment, awesomeness follows. . .  analysis!

Step one: Answer: "So What?"

social_media_conversion_rates-all_sources

Better, but honestly still pretty pathetic. Remember the goals are a mix of hard and soft conversions (see above)!

By now I am never surprised when I see the above result for Social Media efforts of most outcomes-driven pimping efforts via those channels.

Perhaps you are an exception. Now you know how to measure it!

As mentioned above Analysis Ninjas won't stop at just Outcomes analysis and will dig deeper to see if there is any value that this traffic is adding to our company. My personal favorite place to start is Visitor Loyalty analysis.

Ok so these people are not delivering any hard or soft conversions. Does their loyalty profile look any different?

Here, check it out (standard report in Google Analytics and other tools):

visitor_loyalty_analysis_social_media_traffic

Hmm. . . a very different profile from other visitors to the site.

Other traffic to the site has much less loyalty than social media traffic. See the delta between 60.98% and 44.35% in the first two rows? Also see the much better, sweeter, distribution for Visitors who visit from 9-14 times through 26-50 times.

For this content website there is value in the social media efforts in that they are delivering an audience that tends to then be much more loyal than all other traffic that ends on their website.

Provable value! From social media!! I know!!! :)

A couple more ideas for our Ninjas to dig deeper, and types of analysis they could do to determine other types of value.

It is trivial to measure the base metrics for your website for your Social Media segment. Visits, Pages/Visit, Average Time on Site, % New Visits, Bounce Rates, Conversion Rates. . . . and so on and so forth. . .

visits_pages_per_visit_avg_time_on_site_percent_new_visits_bounce_rates

You can quickly see at an aggregate level, or a detailed level, if your social media are delivering on the promise outlined by your $150,000 Social Media Consultant.

Here's another bit of analysis that can be useful for certain types of websites.

Say you have a real estate website, or you are responsible for craigslist.com. Both sites are primarily internal site search driven. People come to the site, search, find what they want, do business.

Take your newly beloved Social Media segment and apply it to your delightfully sweet pre-configured Internal Site Search reports. [Left nav -> Content -> Site Search]

Here's what you'll see. . .

internal_site_search_analysis_for_social_media_traffic

You'll be able to analyze if people who come to your site from your Social Media campaigns engage with your site more or less (Total Unique Searches per Visitor). Do they exit from the internal site search results faster or slower (% Search Exits)? Do they have a harder time or an easier time finding the right result (Results Pageviews/Search and % Search Refinements)? And other such analysis.

You don't have to just report clicks and visits from social media. In our real estate website we got to the root of what's a deeper engagement (searching) and we got down to measuring real value (or lack thereof).

Ready to do some real social media ROI analysis?

Here's how you can get the all social media traffic segment:

  1. Log into Google Analytics.
  2. Come back here.
  3. Now click on this link: All Social Media Visits Segment. It will open in GA.
  4. Click on the Create Segment button to save it in your account.

If you want to share this report with others (say via Twitter / email) you can use this url: http://goo.gl/YnJON 

Good luck!

#3: Search Queries With Multiple Keywords [3, 4, 5, 10, 20]

On this blog and in my keynotes I have bemoaned the obsession Marketers have with brand keywords and their sub optimal strategy of optimizing for keywords, rather than key phrases.

I am a search long tail lover. It is the way to happiness (and finding relevant users!). Hence our first segment focuses on helping you understand the balance between keywords and key phrases in the queries used by Visitors from search engines.

It is not actually a "segment," it is more like using advanced segmentation as a reporting engine in a way you can only do in Google Analytics!

My strategy is simple. Use a regular expression to get GA to segment search queries into various "words this query contains" buckets. Here's what it looks like:

search-long-tail-words-segment

"Magical" part: ^\s*[^\s]+(\s+[^\s]+){2}\s*$

Not that magical actually, just a humble regular expression. It is looking for the number of words in a query (in this case queries visitors typed into Google or Bing or Baidu that contained three words). The second regex counts visits with four word search queries.

[A quick note of thanks to Nick Mihailovski for helping me come up with the perfect regular expression. I was using ^\w*\s\w*\s\w*$. It was good but would not have caught some variations and it would not work for queries in non-English character languages.]

Ok back to using advanced segmentation as a long tail search report.

The final segment I have created, using the method above, has more "or" conditions that contain buckets for counting search queries with 3, 4, 5, 10, 20 and 20+ words. You can of course create any buckets you like; these were ones I find initially interesting.

When you click the Test Segment button (top right) you get this gratifying view (cropped to a small size):

search_query_words_used_distribution

Delightful right? It really is.

You get such an immediate sense of the long tail in a way that is hard otherwise in the mass of queries from search engines.

521 Visits from people who typed more than 10 words into Google/Bing! There were 36 visits by people using 20 words in their search query! And 237 people typed in more than 20+ words as their search query!

OMG!

Is your search engine optimization and paid search strategy accommodating for this type of behavior? You still bidding on a word or two?

While the above is not even your complete search universe view, it is a very simple and straightforward way to appreciate how long your search tail is.

And notice you did not even look at a report. You could do all of the above in the advanced segmentation view!

You likely want other buckets than 3, 4, 5, 10 , 20. No problem. Just download the segment below and make the appropriate changes and bam!

Here's how you can get this search long tail segmentation reporting:

  1. Log into Google Analytics.
  2. Come back here.
  3. Now click on this link: Search Query Length Segment. It will open in GA.
  4. Click on the Create Segment button to save it in your account.

If you want to share this report with others (say via Twitter / email) you can use this url: http://goo.gl/v3KbM

Being the Ninja that you are I am sure your thirst of knowledge is not satiated.

Now you are probably wondering how the bounce rate looks for one segment of the long tail traffic (lower usually) or how the conversion rate looks (higher usually) or how many pages do they see (more engagement usually) etc., etc.

The above segment won't help you with that. But all you have to do is create the segment you want.

For example here's the segment for people who see four words exactly:

segment-for-four-words-in-the-query

Save the segment, here it is: Visits via Search Queries containing 4 words.

Now apply it to your favorite search report and hello sweet, sweet delicious data!

performance-data-for-four-words-in-the-query

You know the search queries, you know how many people came and you know their performance ("engagement" or conversions or downloads or leads etc., etc).

Furthermore, you can also segment this data by Paid Search and Organic Search, or Google vs. Bing and start to do very focused analysis that should fundamentally improve your search marketing program.

You can also take another slice at segmenting your search head, mid, and tail. For example you can easily create a segment for Visitors who came to your site via search queries that had more than four words in the query.

Here's that segment: Visits via Search Queries with more than 4 words.

Now go apply it to your search engine or organic search or paid search or goals reports and do really valuable analysis that will earn you the eternal love and adoration of your peers and superiors!

[SIDEBAR]

In case you wanted to do something more sophisticated beyond what's outlined above here are a quick set of instructions, and a tutorial on using regex.

If you want to create a segment for search queries that contain just one word use this regular expression in your advanced segment:

^\s*[^\s]+\s*$

If you want Visits with two words in Google search queries use this:

^\s*[^\s]+\s+[^\s]+\s*$
or
^\s*[^\s]+(\s+[^\s]+){1}\s*$

If you want to identify Visits by people who use three words in their search queries:

^\s*[^\s]+(\s+[^\s]+){2}\s*$

Now you can keep adding to the number in parenthesis and do a happy dance.

Some more cute things.

If you want to query for more than x words, say more than three words use this:

^\s*[^\s]+(\s+[^\s]+){2,}\s*$

Did you see the comma after the number two above? Good.

If you want to identify all search queries where visitors to your site typed 2 or 3 words into the search engine, use this regular expression:

^\s*[^\s]+(\s+[^\s]+){1,2}\s*$

Fun eh?

So what the heck are all those characters in these regular expressions doing? Glad you asked.  Let's consider the regular expression we used to identify 2 word search queries.

The expression is (identified above): ^\s*[^\s]+\s+[^\s]+\s*$

Here's an explanation (as best as I can express in lay terms). . .

^          start at the beginning of the line
\s*        match zero or more white space characters
[^\s]+   match at least one or more non-white space character
\s+       match at least one or more white space character
[^\s]+   match at least one or more non-white space character
\s*        match zero or more white space characters
$          end of string

I hope all this "magic" makes a lot more sense.

[/SIDEBAR]

Isn't advanced segmentation cool? And to think you did all this with your standard javascript tag, all on the fly (including historical data analysis) and without having to buy extensive expensive add-ons!

Ok it's your turn now.

What are your absolutely dearest advanced segments? What's the coolest thing you have done with the advanced segmentation capability in your web analytics tool? Care to share some of your favorites? Perhaps a downloadable link?

It would be incredible to have your wisdom help all of us. Please participate.

Thanks.

Comments

  1. 1
    Patty says:

    Without segmentation our analysis is focused on unrecognizable blobs of traffic. Total Visits. Average Page Views Per Visitor. Overall Conversion Rate. Yada, yada, yada. Boring. Useless. Life wasting.

    This is so true! I like your writing style, very entertaining to read :) I will check out further each of the tools presented. It's true that we have been told the importance of analytics and taught to check its "overall" results, but as you pointed it, it makes no sense without proper guidance.

    Thanks for this article :) It'll be really useful in the near future.

  2. 2
    Josh Braaten says:

    Avinash you are definitely the master of segmentation. It's always reassuring to read posts like this and realize that I actually have simliar segments set up already.

    The biggest issue with the social segment is the time it takes to track each URL your share. Luckily tools like Hootsuite are helping to automate the process by including campaign parameter fields within their status posting UI.

    Thanks for another great post. Happy Holidays!

  3. 3

    I haven't done the conversion thing just yet..Google Analytic have so many great features..including the "Goal" tab.

    I thinks its about time I start using these to help me get some better stat numbers..thanks for the article.

    "Black Seo Guy "Signing Off"

  4. 4
    Ned Kumar says:

    Key to Successful Analytics (Guaranteed) =1 part common sense + 2 parts willinings to experiment + 3 parts of patience + 4 parts of "the underlying thinking process" used by Avinash Kaushik :-).

    Avinash – your last two posts provide outstanding practical value for anyone in the web space. I really don't have much to add other that the segmentation methodology is applicable to simple one channel scenarios with a few data points to complex cross-channel situations involving qualitative and quantitative data. Irrespective of where it is applied, one will always come away with insights. Your post(s) amplifies this message with examples way better than any detailed case studies or explanations.

    Great stuff with real execution value.

    Regards,
    Ned

  5. 5
    Matt says:

    Hey Avinash,

    Great post and great segments. The Regex one is really educative and I am doing my best to understand all that crazy black magic you use (I have to because I want to pass the GA IQ test).

    The only problem with the share link for the segments is that GA show them in the first profile of the account and if you switch to another profile you lost the information. I hope the google team solve that in that future.
    Thanks for this post!

  6. 6

    Thanks once again Avinash,

    Note when clicking on this link from #3: http://zqi.me/smallvisits also "smtagged", Bit.ly is throwing up warnings.

    Also, if you could, every time I try to download and create a segment, it chooses the top account via alpha out of the 11 I manage. I am using FF and Better Analytics 0.9.1. Or am I missing something?? My intention was to use this for some of the other accounts.

    Many thanks!

    Jonathan

  7. 7

    Thanks for sharing Avinash – are these Christmas presents? :)

    Matt you can apply the segment to other profiles on opening it by selecting the dropdown at the bottom where it says “visible in (name of 1st profile) and 0 other profiles” – click the button, tick which other profiles you wish to use then save the whole lot to be in segmentation utopia :)

    Avinash, the use of regular expressions for search is excellent and another area of use could be if applied to external search and internal search and compare the two (this would require opening the regex segments again, changing the dimension to “search term” and also reentering each regex, retitling and resaving) – in theory users should get more specific with internal search therefore a bigger ratio of long tail searches – but I haven’t found that to be the case on a group of sites I’m working with at the moment – more questions!

    Personally, I’ve used the pipe to pull out groups of specific keywords containing semantically similar words eg keyword1|keyword2|keyword3|etc – this requires a set up of Keyword dimension, matches regular expression, then use the pipe “|” between each keyword – here’s the share link, you will need to change keyword1 etc to whatever is appropriate – it’s the “|” that’s the important part. Here’s a shortened share link
    http://bit.ly/geQPMp – this is throwing a warning but does go to the share, or here’s the full link in all its glory

    http://www.google.com/analytics/reporting/add_segment?share=7fwaBi0BAAA.RD_MY1rbVaEf7ayaUJLvVI1QTGO2bYaCima4hb1UUDzDgrzkAi2LvEMWt_j7iu2iS5sICCOGiuYrJ0OEuGesXg.xUAHXCzCVkTdU-JvWMZDTw

    This same structure can be applied for other dimensions eg search engines, service providers etc – anywhere where you wish to create a group of items to test against. Another one I have set up is for some service providers that seemed dodgy as well, which I monitored for a while then created a profile using regex to filter them out.

    Your “silly metric” comment started me laughing – I seem to recall you have a full post(s) on silly metrics and I know you have a chapter in the book. My (least) favourite at the moment is average time on site, as recently I’ve introduced a lot of new people to web analytics tools and this is one they get really hung up on, it takes a long time to explain all the nuances and problems with it and what would be better to use. I have in mind a post that puts it more in context with everything else, and guides people to use time metrics in a more appropriate manner, maybe I’ll even write it!

  8. 8
    Ankur Batla says:

    Hi Avivansh,

    Great Post.. , This post will really help me in doing some advance analytics to impress my clients..

    Thanks a lot…

    Thanks & Regards,
    Ankur Batla
    #–Web Analyst–#

  9. 9
    Jan de Vries says:

    Thanks for this amazing post! Love the long tail keyword segment. Segments I use are the Branded and Non-Branded search and Social Media.

    @Avinash do you know a way to use advanced segments in the Visualization option (the graph in time with all the bulbs :))

  10. 10
    Manjula says:

    Once again, Thank you! Brilliant, practical and very helpful.

  11. 11
    Brian Chiou says:

    Wheee! I REALLLLLLLLY like the regex segment for # of words. I'm going to try using that segment to see how we can optimize our pay per click to increase ROAS.

    Happy Holidays!

  12. 12
    Ankit Garg says:

    Yet another amazing post Avinash… Specially liked the way you explained Non Flirts, Potential Lovers part…

    Avinash perhaps it would also be interesting to mix depth of the visits with the social media report…

    It would help throw more light on whether social media campaigns are really working or not… since loyalty only provides partial picture… what do you think?

  13. 13
    Matthieu says:

    Since I work in Quebec, the website I take care of is bilingual (English and French). Segmenting by language allows to see the difference in behaviour between French speaking visitors and the others. I also sometime check segments for country of origins to see the impact of international promotion.
    I also have some segments to analyze visitors that buy something on the website: one segment for organic buyers, one for buyers with direct links to the website and one for buyers coming through advertising. That way I can see if buyers are all the same or if they diverge with the way they came

  14. 14
    Samith says:

    Thanks Avinash, this sheds new light to the way I used to look at data. It begs me to explore more :)

    I've been playing with advanced segments for a while but haven't digged deep this far, my best advance segment adventure is to create a custom varibale to track logged in members (to identify internal staff for an ecom website) and creating a segment to filter out members.

    Thanks again for sharing your knowledge and writing awesome posts!

  15. 15
    Marat says:

    Great post!

    I tried searching your blog for information on "Event Tracking" in Google Analytics and could not find it. I would love to read a post from you on "Event Tracking", implementation, best practices, what elements to track/tag, how to label, how to segment different actions/labels, and how, if at all event tracking can be used for conversion, for example what anchor text converts the best, or whether a link in the sidebar or within the body text converts/gets more clicks.

    Thank you

  16. 16

    Ankit: Typically though by the nature of the medium Social Media visitors tend to come for a specific blog post / article / purpose and a majority of them would not stick around for a deeper / different engagement. And that is ok, as long as over time they come back again and again.

    But depending on the type of the website it indeed might be of value to analyze depth of visit. I can imagine some educational websites where this indeed might be of great value.

    Matthieu: These are all wonderful segments to analyze. The international ones make a ton of sense for bilingual websites. But it is also so insightful to look at acquisition segments (and optimize your portfolio!).

    Thanks for sharing these with all of us.

    Marat: There is a pretty good Google Analytics guide for Event Tracking. Here's the overview:

    http://code.google.com/apis/analytics/docs/tracking/eventTrackerOverview.html

    And here's the detailed implementation guide with examples etc:

    http://code.google.com/apis/analytics/docs/tracking/eventTrackerGuide.html

    I could not possibly add anything more of value!

    Avinash.

  17. 17
    Ben says:

    Avinash,

    Per usual, great post.

    You mention that this type of segmentation can be accomplished in under 5 minutes using Site Catalyst… I'm curious how you would go about accomplishing this (without the use of Discover or Data Warehouse).

    I just don't see a way to do regex style segmentation within SiteCatalyst.

  18. 18

    Ben: For regex I am afraid you might have to extend your contract with Omniture/Adobe and purchase a license for Discover or Data Warehouse.

    For others while the initial segmentation powers of Site Catalyst might seem limited, Adobe/Omniture has more than enough additional code extensions you can do with vars and props and slots and… that you should be able to do other things on my list. If it seems difficult I encourage you to seek out some external independent consultants who specialize in Omniture / Adobe. They offer quite good prices and can help you configure your needs optimally. [It is always a great idea to take some of your 90 part $$ from my 10/90 rule and invest in great external independent consultants.]

    I encourage you to do this as soon as you can as often, without Discover or Data Warehouse, you can't segment data you have collected historically (as has been shown in the post for all the segments).

    -Avinash.

  19. 19
    Ben says:

    Avinash,

    Thanks for the reply. I have definitely learned to cope with Omniture's eVars as a means of segmenting traffic in SiteCatalyst however, it isn't nearly as elegant or speedy as GA's solution. I do currently work with the data warehouse solution, and while it can segment to my heart's desire, it isn't known for it's speed…

    Given that SitsCatalyst relies so heavily on the tag and code itself, I've been exploring universal tag/tag management solutions (the industry really needs to just settle on a name) (tealium, tagman, brighttag, ensighten) to expedite the process of tagging in a large corporate ecommerce environment (lots of other benefits too). I'm curious as to your thoughts on this burgeoning new field that closely relates to analytics?

  20. 20

    Ben: I am optimistic that tagging solutions, like the ones you mention, will come of age soon and will be widely used. Given the massive complexity that web analytics vendors have built out even to do accomplish simple things, and it is not just Omniture, we need these solution to at the minimum reduce our need to constantly beg IT.

    In the long run though analytics vendors will have to work to get their act together and simplify what their tags do and how they work. All vendors grew up in the age of log files and over time have accumulated junk and stupidity in how they collect data. Each vendor will have to work to reduce that inadvertently created stupidity.

    One good example is Google moving from urchin.js to ga.js and now async. With each iteration the code is leaner and meaner and does the exact same thing more elegantly (note for example how event tracking works between ga.js and async or custom variables in async – it is soooo much better than any comparable analytics solution). [NOTE: I work at Google as the Analytics Evangelist.] There is still gunk in GA that needs to be cleaned up and I hope it the GA team keeps cleaning up and improving things.

    In closing :), tag management solutions are great, we should use them. All of us. But I hope that vendors like Google Analytics and Omniture and WebTrends and Yahoo! Web Analytics will continue to simplify and awesomize their code so the root cause of our pain will be addressed.

    -Avinash.

  21. 21

    Ok now this is seriously cool.

    I've been searching for a method of demonstrating to clients that focusing on head searches isn't always the best approach to SEO and now I'll be able to illustrate this using actual data! Can't wait to set this up.

    Thanks Avinash. This is truly great.

  22. 22

    Great way to explore segmentation. I wish the segmentation functionality available on GA was there on WebTrends. Its such a pain to build segmentation for the existing reports in WebTrends.

    I love the fact how you have used the page depth feature on segmentation. I am working on a way to define our conversion factor and focusing on the non-bounced users is of great importance for me,

    Again thanks for great post.

  23. 23

    Raghu: Google Analytics benefited from being pretty much the last one in the game to do advanced segmentation amongst web analytics vendors. The benefit of being last :) is that they could learn from the mistakes and limitations of other vendors, many of whom have never revisited what they originally built (in 1932!).

    How is it acceptable, in 2011 (!), that with many paid tools you still can't do on the fly segmentation and have to touch code and then not segment history!

    There is more that I wish was in GA though. Even more dimensions for one. Deeper unique visitor segmentation for another. Additional… well I could keep going on and on. I hope the Google Analytics team will keep adding and innovating in 2011 (as will the teams at Omniture, WebTrends, IBM et al).

    Avinash.

  24. 24

    Hi Avinash –

    I have to confess it's been months since I've been able to catch up on your blog. This post (as everyone can already atest to) is great. Thanks for the actual downloads I only ended up downloading the last one because it's much valuable to walk through the creation of the segments.

    The company I work likes to keep an eye on certain larger companies and their activities on the site so I've created company-specific segments based service provider (often larger companies can be tracked this way).

    Very interesting …

    Hope all is well!

  25. 25
    MHJ says:

    For this content website there is value in the social media efforts in that they are delivering an audience that tends to then be much more loyal than all other traffic that ends on their website.

    Is that definitely the case or could it be loyal visitors are using social media to return to your site, having followed you on Twitter, fanned your FB page, etc?

    Social media would have to be the medium of the first visit in order to prove the statement above, but I don't think we can see whether that's the case from the report?

    (I only say this as someone who wrestles with trying to show value of social media, and as an appreciative regular reader of your blog)

  26. 26
    Martin says:

    Awesome post!

    I wonder if anyone here knows how to use Adv Segs with metric "Time on Site". If I drag it over and then select "Less than"… what should I put in the Value box?

    The number of seconds? 60
    In H:M:S format? 00:00:59
    In minutes? 1

    Any ideas?

  27. 27

    MHJ: You can use the power to segmentation to figure out if your hypothesis (or mine!) is more valid for our businesses.

    Measuring the trends of New Visits from referrals that come via Social Media is a start. Going up or down over time. If SM is simply driving people who have already been to your site before (or are here again having come originally on a SM campaign) then you'll see it here.

    Then, if your tool allows it, then look at the segment of these original referrers from SM and see if they have a higher or lower rate or return to your website. This is a bit more tricky and you can't really do it with GA, at least for now, without major gyrations. But if you have one of the more expensive high end tools then this is not that hard to measure.

    So start with the first part above, that has the overall picture even if not with 100% nailed down certainty. Then go to step two if you have the time (and the money! :)).

    Martin: Number of seconds!

    Avinash.

  28. 28
    Martin says:

    Thanks AK!

  29. 29

    Avinash,

    Thanks for your wonderful insights! For years I have been listening to your webinars, bought your books, and I use your blog posts in my business.

    I guess I should begin to communicate.

    My newest analytics employee is setting up a system for reporting to our customers based on your blog posts "3 Awesome, Downloadable, Custom Web Analytics Reports" and "3 Advanced Web Analytics Visitor Segments: Non-Flirts, Social, Long Tail".

    I also "lo-o-o-ve" the AdWords "Search Terms" report. What do you think of that report?

    Bryan

  30. 30
    Brian says:

    I find tracking self referring tweets and facebook posts to be a very worthwhile task.

    I actually caught this tip a while back at adamsblog.netvantagemarketing.com/a-relatively-quick-way-to-track-your-twitter-and-facebook-traffic-in-google-analytics/ and since then have tried to refine which tweets lead to better visits, and it's an interesting study.

    Throwing tweets and fb posts out into the darkness doesn't leave you with anything actionable to improve!

  31. 31

    Bryan: A lot of people don't realize that when they are looking at Keyword reports in many web analytics tools, even in the AdWords specific reports, they are looking at words and phrases they bid on and not on the words and phrases that the user typed.

    Hence I love the AdWords Search Terms report, because I want to know what the user query was first and then I want to know what keyword I purchased.

    This used to also be a problem in Google Analytics. But mercifully (and painfully) now I can go to Traffic Sources > AdWords > Keywords > Click on the drop down on top of the table > From the resulting options choose Matched Search Query and I am in business!!

    It should not be that hard to find the user's actual query but at least it is there.

    -Avinash.

  32. 32
    MHJ says:

    Avinash, thank you – you're right of course. This is where the promised land of our inhouse data warehouse (many months in the making, not quite sure when it'll be delivered ;) comes in… Have a great weekend.

  33. 33
    The TechBytes says:

    Thanks a lot Avinash for such a great post. Very few bloggers goes in such detail.

    You are Mr. Perfectionist in Bloggers. :)

  34. 34
    Will Dobbs says:

    Another great post.

    I now frequently segmenting my data..Very surprised at the results. You have taught me much about web analytics!

    Thank you again for sharing the templates and your passion about this subject!

    Continued success and segmentation to you!

  35. 35

    Great post. Avinash, is there any reason you define the source as social-media and the medium as twitter, facebook, etc. rather than the other way around?

    i.e. ?utm_source=twitter&utm_medium=social-media

    Thanks… Tom

  36. 36

    Tom: The structure I decided on was: What channel? Social Media. What sub-stream? Twitter. Whose tweet? AK (me, could be someone else in our company).

    I also like that in the All Sources report it shows up Social-Media first then twtter etc (Google Analytics always does Source Medium).

    But this is a matter of personal preference, my only recommendation is that you should create some sensible structure and then stick with it for all your campaigns.

    Avinash.

  37. 37

    Nice post Avinash – I have a different approach on tracking Social Media visits and wanted to share it with you…

    Essentially I re-write, using a filter, the referring source of visits from Twitter/Facebook/forums etc., so that they are permanently labelled as referrer "social media" in all GA reports.

    The detail is here:
    Tracking Social Networks with Google Analytics
    http://www.advanced-web-metrics.com/blog/2008/11/03/tracking-social-networks-with-google-analytics-using-filters/

    Not better – just different ;)

    Best regards, Brian

  38. 38

    Thanks Avinash
    I completely got the sense of the Regex nature with this post. Besides, I learned others regex I didn't know like \s (whitespaces) \d (numbers) \w (word characters) etc. Now I can segment keywords with or without numbers, with or without words

    For instance, I made an interesting regex which lets you get the number of match query, I mean, searching with " "

    It is basically the same regex you did, but replacing \s by "

    ^"(\s*[^\s]+){1,}\s*"$

    Thanks again!

  39. 39
    Tomer says:

    Amazing, both the what and how.

    Thank you.

  40. 40
    Chris says:

    Great post – and a wonderful introduction for me to Custom Reports.

    I've had a great time playing around with coming up with my own reports, even if I'm a bit late to the party!

  41. 41
    sherry says:

    Avinash,

    I so admire your passion for advanced segmentation. Thank you for the post! I learned some wonderful new tricks :-)

    Cheers!

  42. 42
    Art says:

    Do you recommend search depth over visit duration?

    Do you use any thresholds that correspond with AIDA model that can allow sorting keywords..for example visits 20 sec or less fall under awareness, 60 seconds or more are interested. Use this to sort search terms that havent converted into leads yet… evaluate based on time on site per search term.

    Thanks, Art

  43. 43

    Art: In my humble opinion it is a little bit dangerous to assign intent to the number of seconds someone spent on the site / page. It is very very hard to know if a keyword that drove 20 seconds was awareness or interested.

    You can run surveys and marry it with you analytics visits data and find the keywords and see if you can marry intent to the amount of time spent. That might be one option.

    This is not exactly the same but I had recommended categorizing keywords into brand an non-brand and then tying them to the most optimal metric, tied to the stage through which the customer is in.

    Here's that post, I hope it will help spark some thinking: Paid Search Analytics: Measuring Value of "Upper Funnel" Keywords

    -Avinash.

  44. 44
    Garret says:

    Avinash,

    You rock! Your posts are amazing, so much meaty data to digest. Can you do some posts on using events: Category, Action, Label, Value in GA?

    Best,
    Garret

  45. 46
    Miguel Caldas says:

    Hi Avinash,

    Thank you so much for your interesting article. I tried to download the "My Social Media Traffic Segment", but couldn't. It directs me to my account home page.

    Could you just tell me how it's done?

    Thank you very much,

    Miguel

    • 47

      Miguel: The problem is that for the moment segments are not shareable in GA v5, the latest version you are using. The segments were created in v4, and now they don't work when you try to open them in v5.

      The good news is that the team at Google has said that this feature is coming soon. Until then I hope that he screenshots will help you recreate the segments from scratch inside GA v5.

      I'll of course update the links to the new v5 stuff once the segments sharing is in there.

      -Avinash.

      • 48
        Gerrit says:

        A workaround for this is to go to your GA account.

        Click on the (red) "old version" link on the top-right of your screen. This will bring you back to the v4 GA version. Then copy/paste the relevant code into your browser and create your segment.

    • 49

      Miguel, Gerrit: Hi. You should be able to download the segments into your GA accounts now. I've updated the links to the newly released sharing function in Google Analytics v5.

      Just log into your GA account and then click on the links in the above post.

      -Avinash.

  46. 50
    Miguel Caldas says:

    Thank you Avinash!

  47. 51
    Markus Frick says:

    Hi Avinash,

    thanks for sharing those insightful reports with us – another great post as usual.

    FYI:
    By following the link, where it says
    "Here's that segment: Visits via Search Queries with more than 4 words."
    you are ending up on a 404 page – due to an additional URL with a added, which breaks it.

    Best regards from Stockholm,
    Markus

    • 52

      Markus: Thank you so much for letting me know. It was a case of the "Enter" key being pressed where it should not have been.

      All should be well now.

      Thanks again!

      Avinash.

  48. 53
    Joe Gondek says:

    We recently launched a new version of our website, and the products section is broken out into multiple market segments.

    I am hoping to see each of the new 13 market segments defined under our brand architecture against each other for analytics. Any ideas on the best way to segment the data?

    Joe

    • 54

      Joe: There are at least three or four ways to do this, in any web analytics tool. Without knowing a lot of detail one of the first thoughts would be to use Custom Variables and set the scope at a Visit level to capture the sections they are visiting. Then you segment and measure performance.

      You could also use Event Tracking for something like this.

      The optimal path might be to engage a GACP who can go through the requirements and validate and recommend the right path. You'll find a list here: http://www.google.com/analytics/partners.html

      -Avinash.

  49. 55
    Ahsen says:

    Hi Avinash,

    Great post!

    Is there a way to combine more than 1 custom advanced segment? I don't want to compare but combine.

    I want to see traffic which meets both "Non-Flirts, Potential Lovers" AND "Visits via search queries w/ 4 words." segments.

    I saw one thread here regarding this but there was no resolution to this problem:

    groups.google.com/a/googleproductforums.com/forum/#!category-topic/analytics/discuss-google-analytics-features-with-other-users/nKcdL0lX8UM

    Is it possible?

    • 56

      Ahsen: Inside Google Analytics Advanced Segmentation interface you can do this:

      (segment one OR segment two)

      (segment one) AND (segment two)

      (segment one OR segment two) AND (segment three OR segment four)

      (segment one OR segment two OR segment three) AND (segment four)

      And other such combinations.

      If what you want to do is not listed above please use the free GA API to grab exactly the data you need. There are a ton of apps (many free) that will let you pull the data out of GA into excel and do this in 15 seconds.

      The app gallery is here: http://www.google.com/analytics/apps/

      Checkout the editors picks, and other options in the left nav.

      -Avinash.

  50. 57
    Ahsen says:

    Hi Avinash,

    Thanks for your reply but I think perhaps I was not clear enough with my question:

    Can I choose two or more custom segments that I've *already defined* from the list of my custom segments and see the combined traffic–not compare the two custom segments separately (and possibly create a new custom segment based on the combination of these custom segments from the list)?

    For example, in my Custom Segments I already have 'Non-Flirts, Potential Lovers' and 'Visits via search queries w/ 4 words'. What I want to see is the 4-word queries of ONLY my 'Non-Flirts, Potential Lovers' custom segment. And preferably create a new custom segment based on this combination by simply choosing them from the list.

    How can I do that? Or do I have to create a new custom segment from scratch to see the combined result of these two custom segments?

    I will really appreciate your answer because I can't find the answer to this anywhere.

  51. 58
    Philip Thirlwell says:

    Awesome post, this was really helpful (as a GA newbie).

    Thanks!

  52. 59
    Dan Shure says:

    WOW! Thanks Avinash

    The only thing I'd add now, is if you're doing 2 word searches, to filter OUT "not provided" and "not set" from that segment. Can really skew things.

    Thanks again.

    -Dan

  53. 60
    Dana Tan says:

    I think the heavens just parted and angels are singing. Hallelujah! Avinash this is incredible stuff. Not only that, thanks to your engaging explanations, I actually get it…like I really understand it. I understand it well enough to even experiment with creating my own segmentation…whoa! I feel so…smart! :-) Thank you!

    Seriously, this is the most amazing information. Now, no one (not even me!) can make excuses about not segmenting.

  54. 61

    Hi – Stretching my brain again… hurts a little!

    i looked to set up the flirts segment – but the options I got for the condition were :

    Exactly matching
    Matching RegExp
    Begins With
    Ends With
    Containing

    no Less than – or More than for that matter.

    When I imported your segment there it was – less than – but it's still not there on the drop down list!

    So where did it come from – and why can't I see it?

    Is there something I've not activated? Very strange – great segment by the way – I've already spotted a couple of things on the keywords from these people that look like the y probably merit their own ad group or even campaign – excellent.

    Thanks

  55. 62
    Shimantika Kumar says:

    You're a great teacher Avinash! It's easy to understand things the way you put it.

    This is a Looong blog! Took me 2 sittings to read it well and understand it, and read it I did.

    I love your details and your painstaking preoccupation with all the little extras. Without those, reading these blogs would not be so much fun.

    Thanks again!

  56. 63

    Hi Avinash,

    it is very annoying that 95% of my data is not useful because of not provided. Do you have any advice how to draw consequences from 5%?

    thanks,M.

  57. 65
    Ivan says:

    I hate it when Google changes some things, so I have to learn all over again…. but relly nice info :)

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