Occam’s Razor by Avinash Kaushik

Tags, tracking advanced javascript functions, navigation summaries and exit pages, delights of benchmarking, challenges with goals and funnels, monogamy or polygamy, flash tracking and ajax, multi domain tracking, entrance paths (my favorite!), bosses and robots (is there a difference?), we tackle all these topics & more in this post.

But before all that, some context.

A recent wonderful experience for me was participating in a analytics webinar hosted by NTEN (Nonprofit Technology Network). I am very fond of NTEN, they do amazing work (plus Holly and her team are awesome!).

This was my second outing with NTEN, and this time round the idea was simple. They ask questions about Google Analytics and I try to answer as many of them as quickly as I can (with a modicum of intelligence).

It was a lot of fun. Often we live in our high and mighty towers (everyone except me of course!) and it is nice to get a dose of reality. Real people with real problems.

Of course there were waaaay more questions than I could answer in the available time. So I promised that I would write a blog post to answer them. They get what they want, and I make up for the fact that in two years I have written two posts exclusively about GA!

These questions were in the context of Google Analytics. But I think they’ll apply to many different web analytics tools, in as much those of you that use other tools might also find them to be of value.

Sit back, relax and enjoy the ride!

Google Analytics: “Frequently” Asked Questions.

How can nonprofits on content management systems best use Google Analytics when they don’t have access to html code on the backend?

In order to use any web analytics tool (javascript tag based) it is mandatory that you are able to add a few lines of code to your website. If that is not possible you are out of luck.

The nice thing is that almost all websites have something like a footer.html (or php or jhtml or whatever) that gets automatically added to all the pages to the site. If you can just add your .js tag to that file then you are set. So it is not a lot of work to add the base tag a site, and you don’t need access to all the pages.

If are in the “out of luck” category, then you can opt to get access to your website’s server logs and then use a log file based web analytics solution like Urchin from Google or ClickTracks (or in the honor of Dr. Stephen Turner: Analog!).

Remember the important part is that you don’t have to live without data. : )

I would actually be interested in knowing how to track Javascript function links.

I think this question is related to links on a page that are encoded with javascript (hence can’t be tracked natively by web analytics tools). Examples are links like: Print This Page or Email Me (with a mailto:) or Form Fields or Buttons etc etc.

Here’s a specific one:

www.msnbc.msn.com is using Google Analytics (and Omniture) and they might want to track the number of people who click on the slideshow link on the home page. Note the way that link is encoded, that’s a javascript function call.

MSNBC can use the _trackPageviewfunction in Google Analytics to track those clicks. Essentially that enables the javascript event to be assigned a page filename and boom (!) data. :)

More technical details in this help document: How do I track JavaScript events?

I had a question about Exit Pages: if a visitor uses the ‘Back’ button to exit out of a page, what is counted as the exit page? Is it the last page they got to before they started backing out, or is it the last page the hit ‘Back’ on?

Exit pages are typically the last page that gets recorded in a website visitors session.

Let answer the question in layers.

One difference between logfiles and javascript tags is that the tags will more accurately capture back button clicks. The reason is simple. When you press back button the page is most likely served from your browser cache, which means your logfile has not entry for it. But the javascript tag gets executed every time the page loads, so it will send data back to the server.

Specific to back buttons the answer will depend on which type of solution you are using.

But in this scenario: Home -> About -> Back (Home) -> Speaking Engagements -> Back (Home)

Google Analytics will report the Exit Page as the Home Page (the last page recorded in the session).

Navigation summary question - why is previous and next page often the same as the page you are viewing?

This is a good one, I was confused about it a while back as well.

The explanation of this one is really cool, it might sound technical but stick with me and you’ll see what I mean by cool. . . . .

The report won’t fit here so here is a badly butchered picture to show as an example (click here for a higher resolution picture):

The report is for my Web Analytics 2.0 post. And you’ll notice that 15.90% of the referrers of traffic to that post is the post itself and the next page seen on the website by 15.90% of the visitors is that same post.

Bizzaro!

Cari explained it to me in September (when I was confused!). . . . .

It turns out that this page (web analytics 2.0) has close-ups of graphics (click on this image for higher resolution etc), and if a person reads the page, they will likely view the image / graphic, then hit the back button, causing a second hit.

This means that it will be its own “previous” page and its own “next” page.

Take this session history as an example:

To Google Analytics (or any other Analytics tool), it will look like this:

If you look at this in GA, you will see that the page was viewed 3 times, and that on 2 occasions, it was its own previous and on 2 occasions, it was its own next (!!). If this is the case, the previous and next values should always match (which it does in my case).

Amazed? Surprised? A] Cari is very good at what she does. B] Web Analytics is fun because it is such cool detective work!

Your navigational report might show the same page as the referrer because your Visitors might click Reload a bunch of times (generating “self referring” hits), and other such delightful behavior.

Benchmarking - how are the categories assigned or determined?

One of the features in Google Analytics is that those clients that opt-in their anonymous data can avail of features like Industry Benchmarking (Important : You have to make the choice to do this, you can choose to opt you data in anonymously or keep it private - not provide google permission to look at it. See: Data Sharing Setting FAQ.)

Here is the official answer to your question: When benchmarking is enabled, Google crawls the websites in the account then categorizes them by vertical and the amount of visits. The data is then made anonymous through aggregation.

In English: Google indexes and categorizes websites and uses that categorization to bucket your website.

But here is the nice thing:

Click on that link that says Open Category List, and you’ll see this:

You can choose your own category, if you don’t like the one you were placed in automatically by Google. Win-Win.

You get three levels of categories, in this case: Computer & Electronics -> Software -> Operating Systems. And as it says at the bottom, as more data is available more categories will be available to allow you some very granular comparisons.

For more delightful details see: Using the benchmarking service.

How valuable/accurate is the benchmark data in GA?

Let’s break it into two pieces.

The data is valuable.

You should not be surprised to hear that from the person who presented the web analytics 2.0 mental model - a core of which is competitive intelligence.

Here’s a helpful analogy: If you only look at your web analytics data it is like sitting in a car with the dashboard in front of you. It tells you that you are going at 75 mph etc. But its as if the windshield and windows are blacked out, you have no idea what’s going on around you. Using competitive intelligence data is like scraping that black paint from the windows so you can look out - and see that you are in a race and everyone else is driving at 200 mph. Context is king.

So use benchmarking in Google Analytics, use www.compete.com, use index.fireclick.com, or use the new Google Trends for Sites. Get context to your performance.

In terms of accuracy, when it comes to competitive intelligence that is such a tough word (for any tool / data provider). Here is how the team works hard on your behalf:

Compare trends, ensure your category chosen is correct and you’ll be set. Over time as more sites opt in and more data is available it will only strengthen the benchmark.

Our debate here-Do we have very specific niche topical blogs or have more general topic blogs so we “have bigger numbers”?

This is not a Analytics question, more like a blogging strategy question. IMHO unless you have something absolutely unique to offer (big number of bloggers, famous people to write, astounding offline reach etc etc etc) it is much hard to break through with a general topic blog.

You are probably very good at one thing, pick that topic and go. If you are good your unique audience will find you and Lady Success will be yours. Here’s a helpful post: Ten More Blogging Tips From A Novice Blogger.

Funnels - ?? just a bit confused about how these things work!

Simple. You probably have a “structured experience” on your website. The simplest example of this is a cart and checkout experience. Or filling out a multi step application (credit card or a adwords account etc). Or sending a money order from a bank site.

Essentially anything that goes: Start -> Step One -> Step Two -> Step Three -> Done.

On your site perhaps: Add to Cart - > Start Checkout -> Billing Information -> Shipping Information -> Submit Order.

When you set up a goal in GA you have the opportunity to input the steps to get to that goal. In the above case the goal would be Submit Order and you can add the page urls from add to cart to shipping info. Then GA will automatically show you:

Here is a funnel:

It tells you that you have a major problem on the first step, 76% abandonment.

Most people come to that first stage from mifotonatura.php but a good bunch also come from the home page.

Of the 25k that exit about 10k exit your site! They are upset! :)

The second step is doing better, 58% abandonment. And your overall conversion is 9.98%.

You know what to improve and fix.

Funnels are very good at understanding where structured experiences on your websites are failing. They are typically the easiest things to fix on your website, so please use ‘em.

Sorry - can you repeat again how to set up funnel and goal?

Here are a couple of helpful links:

Funnel Question: Does funnel visualization parse old data or just start tracking new visitors after it is set up?

Only the data from the day that you set up the funnel (starting an hour after you set up the funnel).

This is a common “feature” in pretty much all web analytics tools, you have no (or severely limited) ability to “reprocess” data. Some of the analytics tools comes with options where you can purchase an add on data warehouse component that will allow you to “reprocess” data. But most off the shelf ASP based solutions don’t allow reprocessing of data.

Also if you set up a funnel today and a month later you remove a step, or add a step, then that change is only going forward. It is important to make a note of it.

How can I DELETE an existing goal?

You can’t actually delete a goal once it’s been created.

But you can turn it off.

In Analytics Settings > Profile Settings > Goal Settings click the ‘Active Goal Off’ radio button.

Bingo!

Does it make sense or is it fair to compare data among a couple or more analytics solutions? For example Google Analytics and HBX?

Nothing in life is fair. :)

It seems like a good thing to have more than one tool on your website, just in case. And I should not complain, I have eight tools on this blog.

But I have often recommended on this blog, and in Web Analytics: An Hour A Day, that it is optimal that you end up with one tool. Life is hard enough in terms of making sense of one tool and getting it to provide actionable insights. So find the one that is optimal for you and then stick to it. This is clearly a case where less is more.

It is ok to start off with multiple tools, and rather than whittling down your choice on a RFP or a vendor dog and pony, pick from your experience in a production environment. But strive to get one.

If you do use more than one tool, say GA and HBX, then realize that numbers between different tools will never tie, it is simply impossible. They will tend to be in a narrow band and tend to flow in the same general direction. If you have more than one tool and if they are approximately 8 - 10% close to each other than thank your lucky stars and move on.

If they are beyond 10% different (and you want to use both tools!) then see this post on a recommended process for reconciling between different tools: Convert Data Skeptics: Document, Educate & Pick Your Poison.

Oh and good luck.

Describe the “bounce rate”. It’s always high.

Bounce rate is perhaps the sexiest web metric today. Period.

From a customer perspective it measures this phenomenon on your website: “I came. I puked. I left.”

It measures the landing pages on your websites that stink so badly that they can’t even mange to get the Visitors to make a single click. Sad.

It is also immensely actionable. When you look at the data, it is easy to know where you need to take action. So use Bounce Rate, it is your friend (if not a true BFF!).

There are obvious exceptions. Blogs. I don’t use bounce rate for my overall blog traffic because many of you are returning visitors, you will read my latest post and leave. This will mean a high bounce rate, and that is quite ok.

When I look at bounce rate for the blog I segment it for my New Visitors. I don’t want them to leave after one page view, I want them to read a couple posts, be convinced of the blog’s greatness and sign up for the RSS feed. So in that case bounce rate can be a little helpful.

Learn a lot more about bounce rate and how to action it here: Standard Metrics Revisited: #3: Bounce Rate.

Are pageviews/uniques getting obsolete with Ajax, Flash, etc.

Yes, atleast page views (I am so sorry I don’t know what was meant by uniques).

Almost all web analytics tools today expect a page view, it is the fundamental foundation of all computations (sessions, time, etc etc). But there are no “page views” in Gmail or www.miniusa.com or much of the Paramount Pictures website. That makes them “hard” to track using standard javascript tags.

The method so far to deal with rich internet experiences was to create fake page views. Just so the web analytics tool would measure something. But this only resulted in lots of painful tagging work (which you are probably still doing) and this fake page view data polluted your real page view data resulting in a big mess.

We are now entering a new phase of evolution where we are going to use a new way to collect data, its called “Event Logging”. Google Analytics uses this, and there are atleast one or two other analytics tools that use true event logging.

No more fake page views, no more six year implementation cycles. And most of all you get to define up front exactly what “business interactions” you want to capture and you are able to do that at scale and analyze them with reports uniquely created for those rich media experiences.

Pageviews as a measure of success are on their way out, but they will still be around for some time (most of the web is still static). They will measure less and less of the complete customer experience picture.

Here’s way more about GA Event Tracking than you ever wanted to know: Event Tracking Overview (Beta).

Do you need to use the newer Google Analytics code to add the event logging code?

Yes.

Click on the GA logo on the top left (after you are logged into the tool). You’ll be on the Analytics Setting page.

Click on Edit link next to the name of the website.

(And this is silly and waaaay hidden) Click on Check Status.

Click on the New Tracking Code (ga.js) tab.

Copy the code, replace your current (urchin.js) and you are good to go.

When analyzing navigation paths on my website, it gets really challenging because all our pages are interlinked and each can be accessed from a variety of pages. So when I ask “how many people clicked donate from the homepage and actually completed the donation form?” I can’t get an answer because I can’t tell from the donation page who got there from the homepage and then actually went on to the confirmation page. Ideas on this kind of multi-page navigation given lots of page re-use?

Long question, and a very complex one. But, and it is magnificent, I have perfect answer for you! A real hidden gem in Google Analytics (that sadly very few people use).

The Entrance Paths report.

Go to any page you want, in your case your home page, by going to Content -> Top Content (or Content by Title). In the summary of the page (data like page views, time on page, exits etc) you’ll see, on the left, a link called Entrance Paths. CLICK!

This is what you’ll see:

You are looking at the Home Page and in the middle are all the possible clicks people can make on that page. Choose the link that says, in your case, Donation Form in the middle column. The report will transform to this…

Let’s say the second link in the middle column is the Donation Form link, the column on the right shows where those Visitors ended up. You’ll easily be able to locate the Donation Form Completion Page and see how many donated. In my picture above let’s say that is the third link so it would be 246 (9.27% of those who saw the Home Page).

Super?

I love this report because it is the anti path analysis (Path Analysis: Not A Good Use of Time). This report compresses all the other pages people might have seen and paths they might have followed. It shows you very effectively if that page (your home page) is doing the job it is supposed to be doing.

Very helpful. It takes a little thinking, but remember God helps those who help themselves. :)

How well does google analytics filter out bots? Can I be assured that my results are not skewed by bots?

Most robots / bots (say like the googlebot) do not execute javascript tags. This means they do not trigger your web analytics javascript tags and corrupt your data. [This is also the reason why robots don't see your multivariate and A/B testing pages.]

So Google Analytics and Omniture and CoreMetrics and all the other tools that use javascript tags are not affected by robots as much.

This is not the case with logs based solutions, for example log file parsers from WebTrends (or Urchin or ClickTracks mentioned above). It is a constant battle to filter bot traffic from server logs.

There are some rogue robots that can execute javascript tags (gomez is one of those). But it is rare, unlike as some folks would have your believe (it suits their goals). A best practice is that if you see a really unusual spike in traffic, go to your referring websites and your keyword reports and check if it can be explained. If not dig deeper. By unusual I mean big unusual.

Also you should know that the Vendors, including Google, has mechanisms in place to be very proactive with their monitoring algorithms to monitor such stuff. They are not always 100% fool proof, but they are on it all the time.

Not the answer you want, but I hope it helps a bit.

Can Google Analytics be used to combine stats from 2 different web servers w/2 different sub-domains?

Yep.

An example could be: www.fordvehicles.com and www.forddirect.fordvehicles.com.

Here’s Alex with the answer. . . .

Unlike traditional log analysis packages, Google Analytics doesn’t rely on your web server(s) access logs. Since it’s a fully hosted solution, it doesn’t really matter where or how your website is hosted, so long as you can add the tracking code to every single page on your website. If your site spans 2 different sub-domains and your goal is to track the two sub-domains as one site:

(1) Create a Google Analytics account for yoursite.com

(2) Modify the tracking code as stated in here: How do I track all of the sub domains for my site in one profile?

(3) Add the same tracking code to both sub-domains

Happy Birthday!

How do I merge 3 or 4 websites into one set of stats?

This one can be a non trivial amount of work (in Google Analytics and many other tools). It can be done, but you are best placed in recruiting one of the many wonderful Google Analytics Authorized Consultants (GAAC’s) to help you with it. They are all over the world and they offer services at all price points.

Once again, here is the GA Supreme Guru Alex. . . .

In the absence of roll-up reporting, and passing first cookie information from one domain to the next (to de-dupe unique visitors) can get tricky if you have more than 2 domains. If you’re not so worried about unique visitors, you can simply add the same tracking code to all your domains to log the data into 1 “super” profile. [AK: Cheap trick! :)]

You can try linking a visitors navigation between the 3-4 websites together by tagging all outbound links that point to one another, using the _linker() method, but if a visitor doesn’t click on the tagged links to get to each site, and instead navigates to each domain directly, Analytics will identify each that visitor as 4 unique visitors (one for each domain hit) in the super profile.

Not exactly straightforward.

Here’s a helpful article: How do I install the tracking code if my site spans multiple domains?

If you only have 2 domains

Shortest follow up question ever!

1] ALWAYS _link() method method on any links that point from one of your domains to the other: What is _link() and how can it help me?
(2) Do as this article says: How do I install the tracking code if my site spans multiple domains?

What are the best reports to get top management to pay attention to web stats?

After two years of MBA school the one thing I learned was that you can answer any question with this: It depends. :)

All kidding aside, that is quite true in this case.

See this post for more awesome, practical, ideas: How To Excite People About Web Analytics: Five Tips.

And rather than reports might I suggest that you initially focus on reporting to them metrics that will connect with them and provide deep actionable insights.

My advice, pick metrics that pass these four filters: They are Uncomplex, Relevant, Timely and Instantly Useful.

Indepth details on strategy here: Web Metrics Demystified.

For dynamic sites, esp using AJAX, can the goal URL have a dynamic attribute such as mypage.aspx?ID=Success instead of a totally separate URL?

What?

I am way out of my league with this, here’s Alex again. . . .

I think what this question is asking is “how do I differentiate a goal page from my funnel pages if all appear to have the same URL?”

The answer is to use the _pageTracker(); method to generate fake pageviews each time a goal is “hit”. See the section titled “Identical URLs across multiple steps” in this help center article.

- - -

Whew!

You are a tough bunch. But that was a lot of fun, got me to share some of the knowledge I had and a couple things I feel excited about.

I hope you learned a lot as well and that this was productive.

Did we get the answers right here? Would you add / remove anything? Was something mis represented? Did I forget something? Is there a unique way you have solved one of these problems?

Please share your feedback with us, it would be greatly appreciated.

Important PS:
The most scalable way to get help with Google Analytics is sadly not this blog.

Google provides direct email support in 27 languages, simply click on the Contact Us link at the bottom of any Google Analytics report.

Option two is the wonderful Analytics Help website, run by Google.

Option three is the fantastic Analytics Google Groups site, run by our users (who we love and adore and cherish!).

Option four is getting Accountable Support through GAAC’s - Google Analytics Authorized Consultants. This option is very affordable, the GAAC’s provide full service or a la carte service at very competitive price points - worldwide!

There is perhaps no challenge greater than tracking offline impact of your online presence (campaigns or other activity). It is perhaps one of the last few complex nuts left to crack.

Why? Because it is hard. Not impossible. Just hard. And for now it is equal parts quantitative, qualitative and faith.

This post bravely attempts to:

1] Highlight the importance of holistic multichannel analytics

2] Outline why online to offline tracking is a difficult exercise, atleast for now

3] Provide you with a bushel of specific multichannel measurement ideas to help quantify the offline impact of your online presence

It’s a tall order, but after two years of blogging why stop now. : )

Why should you care about measuring multichannel impact?

You have a delightful website, it is chugging along merrily at a 1.7% conversion rate (average as reported by shop.org) and you are dutifully reporting our revenue of $1 million as a result.

Happiness?

No.

While you might be doing great in terms of direct revenue impact of your website, pause and consider what in God’s name is happening to that other 98.3% “unconverted” traffic on your site?

It is quite likely that your website is delivering some value to that 98.3%, how about quantifying it? Ok ok some of them puked and bounced. But the rest probably got what they were there for and your website was helping them by doing all those “jobs” as well, along with pure ecommerce.

Your ecommerce website is helping people who will only do research online and then buy stuff in a store. Its job is also to provide information to people who want to learn and then call your phone center to buy.

Or just submit a lead and have you call them. Or there are people who will get their tech support question answered and as a result not call you on the phone (saving you $50 it costs you to answer the phone). Or help someone learn about your company and then apply for a job (saving you $2,500 in recruiting cost per person!). Or. . . .

There are many jobs your website is doing, it is your job to measure the holistic impact. In blue below is the typical direct conversion impact and in red it a very large area that we almost always ignore quantifying. . . .

It is quite likely that by the time you quantify the impact of your site on the 98.3% Visitors it turns out that the site delivered $4 million in value (which dwarfs the $1 million in direct value).

That’s why multichannel analytics is so important.

You struggle to get budget to hire Analysts or Marketers. Your head is sore from banging it to get funding for a new CMS. Your hair is thinning from repeatedly trying to get funding for online campaigns. Ever thought that you might be making a case from the wrong base ($1 million impact)?

The effort you invest in measuring offline impact will finally help your company understand how valuable the online channel is (or not!). Do it.

Framing the online to offline “data” problem:

Why is quantifying offline impact such a problem?

Two words: Primary Key.

In English: We simply don’t have a way of joining the online data to offline data.

What do I mean by that (to those of you who are not database geeks)?

Here’s your online data:

You are capturing the above information using your web log based or javascript tag based web analytics tool. Name, a unique persistent customer id (Geek ID), the keyword the person came on and their underwear size. Well just assume. :)

You also work at a large retailer that sells stuff cheap and when people purchase at your big box store you collect this information:

A unique persistent customer id (which the customer kindly forks over), the product purchased by the customer and the store at which they purchased it.

The two tables above have something in common, a primary key (Geek ID).

This means we can join the two tables with simple sql and understand which online shoppers ended up making a purchase offline (and what keyword they used to arrive on your site):

Boom! Nirvana!!

You know exactly how much online contributed to offline sales, you know how to optimize your online campaigns (buy Apple iPod terms to increase Microsoft Zune sales!!), and if you want to predict (after collecting enough data) if underwear size has a causal impact on what digital music player people purchase.

All this made possible by a simple thing, yes the Geek ID, the primary key.

The problem? [Cue sound of a balloon deflating...]

Usually no such thing exists in the real world.

For almost all the websites today the data that is collected is unique to online only, it is non-PII (personally identifiable information) and anonymous. When people visit our stores, call our phone centers etc, and ring up at our registers they give us their credit card and their names etc but not, as an example, their unique persistent cookie id.

There are small exceptions, like banks where your offline data can be tied to your online behavior using the primary key of bank_account_id.

But usually: No cookie_id = no primary key = no soup for you!

Still some web analytics vendors and consultants are fond of saying, “Yes we can track everything, online and offline and underwear sizes, and you won’t have to lift a finger!”.

Next time you hear that ask them in a sweet voice: “What is the primary key you use to join the two online and offline data?”.

Get your surprised look ready! : )

But. . . . hope :

The path to hard quantification between online to offline is littered with obstacles, for now, but it does not mean you can’t track anything at all (unlike say your TV campaigns!). The current obstacles simply mean that you’ll have to get a little creative, be a bit thoughtful and show a willingness to make a few leaps of faith.

If you are willing to create a small portfolio of initiatives then you can get a pretty decent understanding of the hidden impact (offline) of your web presence. Pick a few different correlating data points and you will be surprised as to how far you can get in this game!

In the longer term in corporations data won’t be quite as siloed as it is today, maybe consumers will be willing to share more of their PII data with companies (though I admit I am not budging with my privacy settings!), or perhaps magically we will have the primary key we need.

Either way it might be less of an issue in a few years, be hopeful.

But also be pragmatic, about how much, how accurate and when. Right now, yes today, try some (or all) of the things immediately below and make progress.

Tips for measuring offline impact (”conversions) of your online channel:

Some of these you might have heard of before, others might be new to you. New or not, with each my hope is to provide bonus tips and ideas that I think will be new to you. Let me know if you find that to be the case. Here we go. . . .

#1: Track your online store locator, directions, other direct offline dimensions.

I can’t believe how easy this one is and often people don’t value it. You have stores, you are smart enough not to hide your store locator on your site, you have integrated with Google Maps and hence now it is time to track usage of the store locator as a proxy for driving people to your stores.

First thing to do is track how many Unique Visitors (or Visits if you are so inclined, Matt!) are using the store locator in a give time period.

It is not that hard, check out the Omniture report for the above url and bam (!), a hint of offline value delivered by the site.

Bonus Tip :

Oh and if you want to get a smidgen more value, configure the store locater search parameter in your internal site search and bam bam (!!) you have a bit more data (what geographical areas have people that have a higher tendency to use our website). In the case of walmart.com (above) that would be the “sfsearch_zip =94043″ parameter in the url. You boss will be impressed with this additional set of insights.

But wait there is more. A little more. This guy….

If people use the maps and directions feature in your store locator feature then they are showing a higher intent to visit the store (else they would have bounced long ago!). Track it!

After I go through the pain of typing my address, doing next, next, and getting the directions I end up here and. . . .

. . . . and you have one more page in Omniture you can configure to compute customer offline intent (THDStoreFinderDirections baby!).

See how easy that was, a medium sized intent by measuring usage of maps and a strong sized intent by measuring customer offline intent.

Bonus Tip :

But don’t stop there. You have already identified these two buckets (location, directions) in Omniture (or in Google Analytics!), that took ten seconds. Now segment the Unique Visitors (or Visits) that display offline intent by referring urls or by email campaigns you are running or by search keywords or affiliates traffic or …. the list is nearly endless (a very good thing).

You now understand what online activity you are doing in terms of acquisition that is driving the kind of people to your site who are displaying a strong intent to visit your stores. Happy birthday!

#2: Use unique 800 (toll free) numbers on the website.

1-800 numbers are so cheap now that our local phone company sends us a free one when we sign up for a home phone line. Each person who calls us on that number is something like 7 cents. Really not a big deal.

So on your website use a unique phone number that is not available through any other channel.

Now track the calls to that 800 (or whatever) number via your phone (PBX) system and you have another signal for the calls driven by your website.

This is very effective for many kinds of websites, be they ecommerce or technical support or lead generation or whatever else is your quest in life. :)

On your website if your phone number is well hidden (like on most tech support websites, #$%@*&!), then using IndexTools or ClickTracks track the views of that page. Gives you something to correlate to your call center (PBX) data.

Bonus Tip :

Are you using unique phone numbers for your Paid Search landing pages? A quick Google search will yield a ton of companies that will put a unique phone number on all your landing pages and will only charge you when people call that number and will give you (in some cases) the data you need to track offline conversion information (by every single keyword / campaign!).

If you are spending “a lot” on AdWords and AdCenter, this can be a excellent add on to track conversions offline due to your Search Engine Marketing (SEM) campaigns. Obviously it would also work for all other kinds of online marketing you are doing and allow a very deep level of accountability.

Bonus Tip :

For a extra cute level of tracking why not let your phone system “ping” your web analytics tool so that you can track the phone calls generated by your website directly in WebTrends or CoreMetrics or Google Analytics?

A quick “hidden page”, a small chq to Mongoose Metrics, add campaigns tags, and now every time someone calls that number it pings your site, the phone call data shows up in your web analytics tool. Nice ain’t it? Check out: Offline Phone Call Tracking With Web Analytics Integration.

So you see there are atleast two simple things you can do that will greatly extend what you can do with good old phone number, needs a bit more elbow grease but nothing worth having in life is easy. Right?

#3: Use unique coupons, offers, promotions online.

Not that hard. Use unique prices, promotions, coupons etc in your online marketing and then track the redemption of these through your offline (phone or retail) channels.

[Yes I am using the Starbucks coupon as the example, yes it is ironic.]

Regardless of the redemption rates of coupons, many businesses find them to be very effective at tracking conversions offline. Not all online offers have to be fiascos (like Starbucks) and if they offer something partly of value they can be great at driving store traffic.

That last part above is important, something of value.

My peer Rene at OX2 showed a great case study with their client Panos, it shows measureability of coupons. Here is a picture from his excellent post :

[The emphasis with colors is mine.]

They measured “impressions”, “interactions”, “impact” and “income”. And they measured “fraud”! Not too shabby.

Of course you are also executing the oldest trick on the book: Send *unique* (single use) coupon codes / promotions to the relevant people on your email mailing lists and then track redemption of those coupons on your website, call centers and stores. For one of my clients the insights were astounding. The website conversion view was just a third of the picture! But what was most amazing, and it was amazing (!), was understanding the channel preferences of our customers. For example the young ‘uns went to the store and those born earlier preferred the website. What was up with that?

That example just shows how you can not only measure the complete conversion picture but also take a stab at understanding customer behaviour (remember for email lists you likely have their locations and demographic info and history and all that!). Try it, it is a lot of fun.

Bonus Tip :

Many companies are now targeting their offers and coupons to just Visitors with repeat visits or people who are in certain geographic location or for just certain products or at just certain hours (day parting!). All these methods provide excellent options when it comes to then measuring the value of online traffic (because rather than the generic catch all, the impact is siloed and makes it easier to assign attribution).

So you don’t want to give money off, that’s ok. Why not do a soft launch of a particular product, only “announce” it online, and only offer it for a limited time to people who visit your site from certain Geography (or campaigns). See if they then go buy the product in the stores. A great example of promotions vs coupons.

Or Tweet the promotion and see if people rush to the store. How hard was that?

#4: Marry / mine online and offline data.

It took this long to get to this “basic” idea, its because it is not that basic and is usually available only to a fraction of the companies out there.

This marriage can be tough to accomplish, but is totally worth it and amazing.

In our non-line world, example of could be Lucky or Safeway supermarkets. They both offer the ability to create an account online, they ask for your “club card” (the one you use to get discounts) when you set it up.

Now when you visit the website repeatedly (and of course get the actual physical stuff in the store, still no “virtual food” to keep you alive!) they collect data on you that they can, with a small effort, tie to your offline behavior.

Another great example of this what WalMart is doing. They offer 100% ecommerce but they allow the option of home delivery or pick up in the store. Sounds convenient.

But the sweet thing WalMart is able to do is not only track that you picked up the item in the store, but they are also able to track (even though it is a separate transaction!) all the other “stuff” (chewing gum, nachos, 39″ tv) that you picked up when you were in the store.

That is a excellent way to quantify the incremental lift that the online presence is driving in the stores.

Is your business measuring the chewing gum effect?

Bonus Tip :

Another thing that we did was to marry up the data for those Visitors who purchase online with their past historical data that we had in the company. In our business people would buy or upgrade each year (or every other year). Having their order data (name, address etc) from the online data store merged with the offline data store (which also had name, address etc) allowed a richer understanding of “channel shift” and other macro patterns.

#5: Leverage onexit online surveys (or Point Of Sale surveys)!

Enough of all this quant stuff, let’s truly use web analytics 2.0 !

Why not just ask the people (on your site and in your store) if your web presence had a net positive impact on them?

Just ask.

And they will tell you. :) No guesses.

You have a onexit survey on your website? No? Yes?

Well if you don’t then get one (4Q is free and a great start.) If you do then add a question to the survey, the question will measure “likelihood to buy offline” or “likelihood to visit a store” or . . . you get the point. . . .

All survey providers will give you this option in a heart beat. iPerceptions, crmmetrix, Foresee, WebIQ etc. In two heart beats (ok a couple weeks) you’ll have data like the picture above. Real multichannel impact of your website as rated by the people you are trying to impact: your customers .

Another great idea is what I see at CircuitCity stores. They use point of sale surveys, what a novel idea! When you purchase a something at a Circuit City store you will notice you get a long receipt. That’s because at the end of that receipt there is a request for you to fill out a online survey at www.bizrate.com.

The goal of the survey is to understand your shopping experience and various attributes that lead to that purchase, including how the website might have played a role.

The results are there for people to see on the website, but more importantly the detailed survey analysis (including open text VOC) that BizRate hopefully provides are the real gold mine of actionable insights. And yes it will help you quantify the value of not just the online channel in terms of driving traffic to the store but also if it was more qualified traffic or better educated or ways in which your site might be failing your store shoppers.

Bonus Tip :

Trend and segment. Really.

The true value of running surveys as a listening mechanism is that you don’t treat them as one night stands. There is some fun in that, but meaning is only created by longer term engagements. So have this as a continuous listening methodology, always on (and remember you can sample a small random number of website visitors and that is enough/ok).

This allows you to trend data over time and see how the website is getting better or worse for those (a majority!) who will not buy / transact online. You can also then isolate evolving needs of your customers and impacts of seasonality and other such factors.

And I’ll stress segmentation again. You are asking the Primary Purpose question already (”why are you here”), now segment likelihood to buy offline by those tasks - are you solving for one group of visitors better than others? Segment by products people might have looked at, segment by new or returning visitors, segment by campaign traffic and direct traffic and on and on.

Seems like some amount of work, but if you are asking the right questions in your onexit survey this is really easy to do, and the best of all your survey company will do all the work. So… do it, rather make them do it. : )

#6: Conduct controlled experiments.

This is a technique our peers in the offline world have been using for time immemorial, and we in the “advanced world” seem to be totally ignorant to it. Quite sad, because it can be awesomely cool.

What is it?

Do you notice why you can buy some products in your favorite store but when you are on vacation and visit five other stores in different places you notice that they all have a slightly different selection.

Or when I first came to California I noticed that in Mountain View they had a fast food outlet called Border Bell. It strangely looked and felt like Taco Bell but the selection was different, they served fresh salsa (three kinds!) and I loved it. But I could not find Border Bell any place else.

Both are examples of companies running controlled experiments to validate their ideas in the real world by running experiments (sadly Border Bell did not make the cut, it is now a Taco Bell).

Take that as your inspiration (not the failure of Border Bell part, the controlled experimentation part).

You want to see if your website can drive traffic to your stores? Do a email campaign to your customers in Florida, Iowa and Oregon, drive them to your site to learn more, and see if that causes a lift in store visits to Costco (your co-branded partner).

Or run PPC campaigns that are geo targeted to deliver a certain message / call to action on www.google.com to potential customers in California, Michigan and Georgia. Measure impact on your site, correlate it with any signal you pick up in your call center.

Or for a week don’t send newspaper inserts (yes those things that go directly into recycle bins) in Arizona, New York and Indiana and run banner ad campaigns on related sites and drive people to your website to look at relevant and unique campaigns in their zip codes. It’s an experiment to see if you can drive the right kind of traffic to your offline channels.

And on and on and on.

The core idea is to try something targeted so that you can correlate the data to your offline data sources (even if you can’t merge it) and detect a signal (impact).

By isolating it to different states (that are far from each other) you are isolating “pollutants” to your data (things beyond your control that might give you sub optimal results).

It is not a perfect methodology, and it takes time, and it needs you to be of decent size (or have enough impressions / customers) to quantify the impact. But few things will give your more confidence in the results you find.

Bonus Tip :

Before you say it, :), correlations don’t imply causality . So if in doubt, rinse and repeat.

#7: Primary research baby!

The second technique that I have learned from our well established offline brothers and sisters. Good old fashioned market research to isolate the impact of your online presence on your offline channels.

Field surveys, focus groups, interviews and more.

Let me give you a example.

Twice a year a tech company collects the names and info of all the folks who purchased something, online or offline or non-line. It then sends that information to their market research agency who, using a portfolio of methodologies, polls those customers to discern all the drivers that caused that purchase.

The data was a gold mine of information related to product attributes, the television ads, the website, impressions from visit to a store, percent of people who touched multiple channels before they purchased the product and so on and so forth.

The survey was done twice a year and, as stressed above, it was a continuous listening methodology and hence it provided a nice series of trends and segmentation data.

I remember the first time I got someone to pay some attention to the website in that company.

It was not my constant on the knees begging.

It was a slide (one slide!) in the analysis deck that showed two pieces of data (both as a pie chart :)), that 24% of the ultimate purchasers (through any channel) listed the company website as the most trusted source of product information and secondly that 40% of the purchasers used the website during the purchase consideration process.

That got me money for Analysts, and that got the poor starved web team two resources to improve the website. All from one slide.

But that’s the power of data.

You can think of many different ways in which you can use these kinds of approaches and how they uniquely apply in your case.

Bonus Tip :

I tend to think in terms of a portfolio model. No one method might be perfect or God’s gift to you. But a couple, or more, of the techniques above will help you get a robust understanding of this hard to solve problem. Combine that with things you are already measuring as a part of your web analytics 2.0 approach and you are sitting pretty.

Good luck!

Ok now your turn.

How are you solving the problem of tracking online to offline tracking? What has worked for you? What did not? Have you tried any of the above? Does anyone believe your analysis? If you could pick one thing to try, which one would it be?

Please share your stories and wounds, and for that we will love you just a bit more. :)

Thanks.

PS:
Couple other related posts you might find interesting:

• Eight Tips For Choosing An Online Survey Provider
• Excellent Analytics Tip #13: Measure Macro AND Micro Conversions
• Stop Obsessing About Conversion Rate
• Seven Steps to Creating a Data Driven Decision Making Culture
• Emetrics Summit Reflections: Peacocks, Woodpeckers, World Bank, Lifetime Value & Click Fraud