jondyer.net

Regular readers of this blog will recognize that I suffer from OOD. Outcomes Obsession Disorder. I am seeing a therapist for it.

The way OOD manifests itself is that in every website and web business I work with I am obnoxiously persistent in helping identify the desired outcomes of the site / business before I ever log into their web analytics data.

The other way OOD manifests itself is that I am in your face, on this blog, constantly asking you to create goals in your web analytics tool (macro and micro conversions) as well as identify goal values for each of those beloved goals.

Without goals and goal values you are not doing web analytics, you are doing web iamwastingyourlifeandminelytics. Sorry, OOD.

After following a structured process to create a Web Analytics Measurement Model most companies find that they are able to identify the goals for their web business.

What they find exceedingly hard to do is identify the economic value added to the business when those goals (micro-conversions) are met.

Framing the Goal Values Challenge, & Opportunity.

Here is an example.

At victoriassecret.com the macro-conversion is making a purchase. I come, place an order for a Colin Stuart Cuffed Suede Over-the-knee Boot and it is not hard to figure out what the value of accomplishing that goal was. $149. [Not net profit, just value. We can compute profit et al later.]

But what is the economic (goal) value of requesting a catalog? Signing up for an Angel Card?

How about the economic (goal) value of me visiting VS All Access and consuming all the valuable content?

There is no doubt that ordering the catalog makes it more likely I'll buy more in the future. Signing up for the Angel Card will make me a loyal customer (after all, how will I ever resist the temptation of getting a surprise birthday gift every year!). Consuming the content at VS All Access improves my perception of the Victoria's Secret brand and perhaps even makes me a Net Promoter (something so precious to the company).

Yet how does an Analyst at VS value those micro-conversions?

And if she does not value any of these micro-conversions is she not doing a disservice to her organization by only having them focus on online conversions (remember just 2% for most sites) and not the holistic site value?

For websites I work with the economic value of micro-conversions is routinely 3 to 4 times the macro-conversion. Let that sink in. Stunning, right?

How about the Analyst for Ohio State University who does a great job of measuring online donations but not the value of campus tours scheduled, prospectuses downloaded, online applications, course registrations, job applications, etc., etc?

On Caterpillar's website there are no obvious macro-conversions, just a whole lot of micro-conversions to track as goals. Equipment lookups, lots of downloads, decision-making tools, quote requests for renting equipment, etc. How does the Analyst compute the value added by the site? Surely not using horrible metrics like Page Views, right?

You will only create a data-driven organization when you are able to compute the complete economic value created by the website. Not through data pukes.

So how does one identify economic (goal) value for the non-ecommerce macro-conversions and all the micro-conversions?

It is easy and it is hard.

You'll often need to step outside your silo of Google Analytics and WebTrends and Site Catalyst and CoreMetrics. You'll need to look in your corporate data warehouses. You'll need to work with your Finance team. You'll need to make leaps of faith.

Try these techniques. . .

#1: Assign campaign codes & track offsite converting goals (micro-conversions).

This is the easiest.

In the right navigation, you can meet one of my micro-conversions by clicking on my book's link. I track that click as a Goal (using Event Tracking). But what is the value of that click?

To answer that question I signed up for an affiliate account with Amazon and added my affiliate id to the outbound link. One great benefit: I get detailed reports from Amazon that tell me clicks and conversion rates! I know how much my book sells for and it's not that hard to compute value of every click on the book's link.

Same thing with the link to Market Motive, my startup that offers quarterly courses and certification in web analytics, paid search, etc. Rather than linking to www.marketmotive.com, the link has utm tracking parameters (utm_source=blogs &utm_medium=occamsrazor &utm_campaign=startuppromo).

Once a month, I go into the Market Motive GA account, segment the Visits from this blog as identified by the campaign tracking parameters, and look at the Per Visit Goal Value (how much economic value Occam's Razor readers added to MM by signing up for certifications, trials, watching videos, downloading stuff, etc). I use that as the Goal Value in this blog's Google Analytics settings.

Simple.

It is not unusual that in addition to delivering conversions (or not), your website links to other places where traffic you refer adds value. Whenever possible, tag those links with campaign parameters / affiliate codes / whatever works, and collect data that helps you identify goal values for your website.

Want a non-blog example?

Take a quick look at Tesco's website. You can see how easily you can use this simple tip to identify goal values for at least 10 not-on-the-corporate-site micro conversions (finally valuing tesco.com at an economic value it deserves!).

#2: Uniquely track online micro-conversions in offline systems.

Someone visits www.cat.com and submits a "Request A Quote" for a Backhoe and Industrial Loader. This goes into the CRM system for Caterpillar. Make sure it is marked uniquely as a "web_quote." Now wait 60 days. Look back and see how many of the web_quote marked requests converted into fully fledged purchases. Now do this:

Total revenue divided by number of web_quotes

You have the average goal value!

Of course you also know how many quotes were originally submitted and of those how many converted. You can use that going forward to get from Google Analytics the number of requests a day and apply the conversion rate and the goal value to compute economic value every day!

Go back and revise the goal value each month using the same method as above. It will help you, over many months, understand seasonality and whether your site is getting better quality quotes (increase in goal value) or worse quality (reduced goal value).

Not very hard. Just takes some time and patience.

Use the same method for people who ordered a Victoria's Secret catalog. Make sure they are identified uniquely in your company database, and then use their purchase behavior (as recorded in the database) to go back and enter a goal value into your web analytics tool.

Same thing for job applications received online (vs. those received from recruiters or via phone or people walking up). Compute conversion for online, identify costs saved due to non-payment of bounty, identify goal value!

Couple more examples. . . Tie applications submitted on the Burger King website to conversions offline, or coupons downloads on the Target website to the number, and value of, redeemed in-store.

Remember don't just take one number and stick with it forever. Periodically (at least once a quarter, though once a month is optimal) go back and validate you have the right number.

#3: Get the current "faith based" number from Finance.

Here's a simple example.

I can go to L'Oreal Paris and spend 10 minutes watching all the TV spots they are airing currently (and conveniently have on their website). Micro-conversions! Goal value?

Not as hard as you might imagine.

I walk over to the Finance department and ask them for the value of one TV ad impression. They have that number. That is what they use to allocate the TV budget (the $$$ spent by the GRPs for the ad, or another faith based number of how many people "possibly" watched the ad, used to computed $ per TV ad impression).

Use that number as your goal value. After all, someone came to the website willingly and watched your TV spot! You know that these people were not in the bathroom when your ad aired on TV. They were there on your site. They hit Play and Pause and Next!

[Use this exact method to place value on your YouTube video views.]

Another example.

How do you value the micro-conversion of me downloading the brochure of the GMC Acadia? The finance team is currently allocating budget to Marketing to spam half of the US with unasked for glossy brochures of the Acadia, in addition to putting millions of them in dealerships. That funding was allocated based on some smart Finance person cooking up some numbers that looked liked this: "When we send 2 million brochures of a car, typically we can get 20,000 people into the showroom, which yields 19,000 Acadias sold, so each brochure gets us a ROI of $45." There you just got the goal value for someone who comes to your site and proactively (with much stronger intent) downloads the brochure.

It is important to note I am not endorsing what the offline folks are doing nor how Finance currently computes the value of offline marketing activities. I am simply asking you to use what they are already using. You can improve upon things later (given that you have a lot more and better data).

Your newspaper ads, your TV blitzes, your billboards, your athletic sponsorships, your logos slapped on NASCAR cars, your conference sponsorships, your. . . other things are all currently being justified via, often faith-based, financial ROI models. Use the exact same numbers. And who will argue with you? You are using what everyone else is!!

People in Finance are your much underappreciated BFFs.

#4: Use "relative goal values." 

Sometimes the first three techniques are not an option for you. No worries.

We'll eyeball things! Because we MUST have goal values. Ok not really eyeball, rather we are going to try something clever.

Let's use ti.com as an example. Texas Instruments is a delightful company with amazing products. It is also a B2B company with no real online conversions, which makes our job in this context harder to do, and hence a great example.

I don't know anyone at TI or ti.com, so I'm making some assumptions. With a quick look at their website, we can identify that a good macro-conversion is orders for Samples. I want to get a Low Power Zero-Drift Instrumentation Amp, I go to the the page, I add a free sample to cart, and I checkout. Boom! Macro-conversion.

In order to establish a goal value for this macro-conversion, TI has many options. I would recommend using the one in tip #2 above.

That's done. Now you'll notice the site also has many micro-conversions. Let's just pick a few. Loads and loads of videos. Valuable "Selection Guides" (and other documents). New my.TI accounts. Completed designs. Outbound clicks to Authorized Distributors. There are others as well but let's just ignore those for a second.

Now how does one value these micro-conversions? If the first three techniques fail then my recommendation would be to use "relative goal values." That is, the value of one goal relative to another goal.

Our benchmark will be our macro conversion. Let's say it is $25 (it is probably a lot higher in real life, but stick with me).

So the question we'll ask is this: "How much is the download of a selection guide by a relevant visitor to our site worth relative to getting an order for a Sample?" Or "How much is someone watching an entire video for one of our products?" So on and so forth.

Don't do this yourself (especially if you are a Consultant and not an in-house Analyst). Get the decision makers in the room. Get Finance to join you. Get the Marketers to bring their wisdom. Essentially, people other than you who really know the business and have experience in making these kinds of judgment calls. They'll bring their baggage, but its a small price to pay.

The first output of this exercise will be a relative ranking of conversions. It might look something like this:

1. Sample orders
2. New my.TI new accounts
3. Completed designs
4. Videos watched
5. Selection guides and other downloads
6. Outbound clicks to distributors

Essentially a priority order of what's important to the business. (If you do nothing else with this info, treat this as Gold. It is so helpful in prioritizing your analytical efforts!)

Then you'll say: "So if a sample order is worth $25, then how much is a new my.TI account worth?"

(Before you jump and yell, let me rush to add that there are 10 good ways to answer that question. But remember, in this case we have no idea how to do it.)

The job of the collective intelligence in the room is to give you that number. An "our best estimate" or "closest judgment call" or "if you put a gun to our heads then based on our 10 year experience we would say x dollars."

Then you go to the next one. "If a sample order is worth $25, then what is the worth of a deeper connection with additional marketing potential and prospect address details and their future behavior on our website by creating a my.TI Account?" You get a number.

Then you continue, so on and so forth. Using the sample order as an anchor or relative anchors ("Well, if the video watched was worth $2 then a selection guide has got to be worth $5 [or $1, or whatever]").

You end up with something like this:

1. Sample orders. Goal value: $25
2. New my.TI new accounts. Goal value: $40
3. Completed designs. Goal value: $18
4. Videos watched. Goal value: $2
5. Selection guides and other downloads. Goal value: $5
6. Outbound clicks to distributors. Goal value: $5

Go put that in to your web analytics tool settings and compute economic value!

I know this is completely faith-based. I know that there are better ways of computing everything above. I know that you are doubtful. I hear you that a group of experienced people can't come up with something close to reality. Actually, you would be wrong about that last one.

I have done this many, many times and it is a surprise how often people say "OMG that was so close to what we had estimated before we did this expensive 9 month process with an outrageously expensive external consultant!"

Just try it. I just want you to start with something. Once the numbers start flowing you'll see that, almost as if by magic, you'll know some value of all that search traffic to a no-obvious-conversion B2B website or a non-profit or a Church's website or. You'll know the Per Visit Goal value of your Twitter and Facebook efforts. You'll know which content creates most value and which tools on the site suck. You'll know… so much.

And this is just the start. Once your execs get into the rhythm of this data and see its power and see your value (so IMPORTANT!), they'll give you the time and the resources to go compute the right goal values. That's the real outcome you want. But you don't get it by hounding people and trying to get perfection on day one without earning your chops. You get it by being nimble and getting key stakeholders involved and going with the "best we got" and building from there.

Trust me, it works.

#5: Use $1 as the goal value for all the outcomes. 

This is the worst case scenario. 

Nobody loves you. Nobody will talk to you. Nobody is interested in telling you anything.

You are the most unique business in the Universe. There is no possible way to get any vague idea of the site's worth. And you just got out of college.

Here's what you do.

First, identify all the macro and micro conversions. This is important. Can't skip this. If they won't help you then go to the site and identify them yourself. You might miss some, but that is okay.

Second, log into Google Analytics / Omniture / whatever and create the goals. Two seconds of work there. In the field that says Goal Value, proudly type in $1.

Hit save.

Start reporting the data with "Revenue," "Per Visit Goal Value" segmented by traffic source, "$index value" of the content, and so many more delightful things. More delightful than lame metrics like Total Visits and Average Page Views/Visit and Total Time on Site etc., etc.

The first time you do this people will be shocked. Then they'll ask "where the heck did you get that number?"

That is exactly what you want! 

For them to be impressed that you are not a lame reporter but someone who takes initiative and reports outcomes and value.

For them to get excited, or agitated, and ask you to explain.

You explain. Then you say, sweetly, blinking your eyes in a bewitching manner: "I took the best guess I could. Could you please help me come up with the best goal values?"

Boom!

You are in!

Sometimes they might say: "Take the $1 out, and report Time on Site." Do that. Start looking for another job.

99% of the time I have been asked: "Okay so how can I figure out the exact value." To which I say: "I read this blog called Occam's Razor, it is awesome. The author shared three specific techniques we can use. Let me tell you about them."

Boom!!

You got a promotion. : )

All from going with $1.

In all seriousness, using $1 is the last resort. But it is a great way to avoid waiting for Jesus or Krishna to come from heaven and give you the goal values. Just start the conversation. Start great reporting. Start doing some actual analysis.

Godspeed.

Ok, it's your turn now.

Do you compute goal values of all the micro-conversions (and if it applies, the macro-conversion) on your website? What approach do you take to quantify the economic value? Have you tried any of the above methods? Worked? Did not?

Please share your experience, hard knocks, love critique via comments below.

Thanks.

Excellent Analytics Tips #19: Identify Website Goal Values & Win! is a post from: Occam's Razor by Avinash Kaushik

Let's start off the new year with lessons learned from a tough life on the front lines of trying to make the world a smidgen more data-driven.

This post is a collection of six things I wish I knew before I started my career in decision support systems (of which web analytics is just the latest incarnation). These lessons might have made some goals easier to accomplish, some frustrations easier to avoid and some salary jumps easier to come by.

Perhaps you are just starting out, perhaps you are in the middle of your professional journey, or maybe at the end. Regardless of where you are I hope these six lessons help speed up your journey, avoid the mistakes I made and achieve success sooner:

#1: An obsession with tools & implementations will kill you.

Everyone wants the perfect tool that bounces rates in real time while computing multi-channel attributable impact of an email sent to grandma via Facebook based on competitive intelligence gleaned from TV watching behavior of customers with lifetime value greater than $358 and FICO scores of 700 or higher.

Get over it.

The smallest part of my success, and yours, will come from having the prefect implementation of the Omniture Marketing Suite or Google Analytics.

10% of your time should be spent in implementing tools, not 15 months with an eye towards analysis in the middle of 2012.

You can win with Omniture or WebTrends or IBM or Google. Stop switching tools!

A majority of your success will come from following the 10/90 rule, hiring smart analysts and then ensuring their work day is optimally structured, weaning your management away from faith based decisions, and ensuring you have a clear line of sight and that you are following the process outlined in the web analytics measurement model.

It took me a while to realize that 100% of what makes a successful web analytics program in any company has nothing to do with tools for the first five years. After five years of success worry about tools.

Next time someone from Google Analytics or Omniture or WebTrends calls you promising to make you a data driven organization. . . tell them to suck it.

#2: Your magnificent analytics skills are tertiary to your success.

In our industry we believe that you have to be good at creating pivot tables in Excel. And using Site Catalyst. And possess at least some knowledge of the fundamentals of statistics. And create box plots and frequency polygons etc., etc.

It will surprise you that pretty much all of your success will not be sourced from your ability to deploy the above skills. Rather it will come from two surprising abilities: 1. Your business savvy and 2. Your soft skills, your EQ (emotional intelligence quotient).

Your real output is not the data; your real output is a set of decisions the Senior Leaders can confidently make to drive business priorities. Recommending actions requires an ability to understand business strategy, marketplace dynamics, some complex situational analysis, root cause identification, and, perhaps most importantly, an ability to identify the right business question. You don't necessarily need an MBA, but if you can't have a intelligent business analysis conversation you won't be effective.

Your real impact comes not from providing pretty pie charts from a complex Discover2 query. It comes from your ability to deal with multiple psychological personalities, from being a warm and friendly person, from constructing relationships across the aisle, from your ability to speak confidently and persuasively about hard decisions and brilliant insights, and disarm people with your charm and un-arrogant demeanor.

If you want to be a great Analyst who has an ability to have business impact with data, work on the above two skills.

[I am not saying analytical skills are not important. They are, see #6 below. But without the above two you are not going anywhere, no matter how smart you are. Prioritize.]

#3: Obsess about Outcomes.

Every other channel is so data poor that when I got into web analytics, like everyone else, I was ecstatic to see very specific customer behavior like the number of Visits! Man that was awesome!

Then I saw page views. And then time on site and unique visitors and browser types and % new visits and I became one happy data-shoveling monkey.

Here's the amazing thing: everyone else who got all those reports thought I was quite simply magnificent. After all I had all this, as they put it: "OMG data!"

That only lasts a couple of months, six at the most.

Then no one cares because no one is any wiser and the business still stinks at the web.

I remember when I first created a simple spreadsheet with 12 rows that just summed up the revenue made by the divisions of the company (even that simple task no one had bothered to do) on the web. The CMO was shocked at how big the number was. The next day he approved a job req for a VP for the Web position.

Great lesson.

Companies care about money, non-profits care about impact, governments care about costs reduced. They all care just about outcomes.

Here is the only way to succeed at web analytics: Identify the business macro and micro conversions. Torture everyone to identify economic value of non-revenue micro conversions. Obsess about this analysis: What's the economic value generated by the company? Why?

Your peers will think you are the embodiment of the messiah. Your boss will listen to your every recommendation. Your CEO will invite you to a private dinner with her/his family.

[Here is my personal recommendation in this context. Obsess about the outcomes for your customers. Use Kissmetrics or 4Q and measure primary purpose by task completion. Buy some sessions with UserTesting or Loop11. Feel the pain of your customers. Identify with their failures and hug / stalk as many people in your company as you have to in order to fix things. Deliver the outcomes your customers want and you'll ascend directly to heaven when its your turn.]

#4: Be pragmatic.

I learn this lesson every single day.

At the end of a recent keynote recently the first question to me was:

"Sure you can optimize the page and campaign based on clicks and on amount donated. But how can you optimize it for the fact that the person voted in the election?"

This was in context of a President Obama A/B test.

I can't measure if the person voted.

I can measure that they came. I can measure that they signed up for a lead. I can measure that they donated and which email campaigns caused them to donate actual hard earned dollars. But no I cannot measure the offline go into the vote booth action.

I ended my answer with:

"If after signing up and donating money to Obama the person voted for Sarah Palin then you know what? I am perfectly okay with that. I did great with my online campaign!"

Be pragmatic.

You will always always, always, run into people who want to achieve the impossible on day one and push you to do the same. Who refuse to fix the high bounce rate on top landing pages. Who want to measure Engagement as defined by x time y divided by z to the power of m with the resulting sum multiplied by n and subtracted from o. Why? Maybe because they are over-achievers. Maybe because they are bored with the "mundane." Maybe because they have no idea what the heck they are talking about. Maybe. . . well who knows.

It is your job to be pragmatic.  Don't focus on what should be measured in a perfect world of persistent nirvana. Focus on what can be measured in a world that is imperfect and needs improvement now. You already have data, a lot more than any other marketing channel on the planet. Use it. Make love to what you have. Produce beautiful analyses tied to business priorities. Get people to take small actions every day and some big ones every month. Go back make more love.

Achievable victories, every day. Aggregation of marginal gains!

Don't get suckered into the impossible. Not because being ambitious is bad, but because putting points on the board matters a lot.

#5: Embrace agility, nimbleness & a portfolio strategy.

If I am not mistaken, for the first two years I did nothing except live in the world of clickstream analysis (with WebTrends and ClickTracks). I did some of the things recommended above (others were yet to be learned). My continued gainful employment indicated that there was some appreciation for the work. But I was still dissatisfied because there was not more slashing and burning of sites going on, not enough Executives had moved beyond using faith.

It took me some time to figure out that clickstream data left far too many questions on the table. Even though we had lots of data, we were information poor.

That led me to my first online survey. Failed. Tried again. This time it worked better. Suddenly I did not have to guess why people were dropping off like flies at stage two in the funnel. They were telling me! I knew the conversion rate for search was 2.74% but now I knew it was so low because people were heading off to Amazon and Costco to buy our product (and that was okay). I knew so much more.

I remember the first time I logged into HitWise. Total data-gasm. I could not believe there was so much to learn from our competitors that so easily helped us identify gaps in our marketing strategy. (We had not even heard of four out of top five companies getting traffic for our biggest head keyword!) It helped us find new geo's to target, new affiliates to target and more. Think of how stupid we were to just focus on website clickstream data.

Then came Offermatica. Man that was awesome. A/B testing! Finally moving beyond HiPPO's trampling the user experience. (Rather than Deciders, they became just one, of many, voices on the table powering an ideas democracy.) Also finally what a fabulous way to try ideas that came up from reading all that voice of customer.

Such a valuable lesson learned (one that would end up as two books!).

Web analytics is fundamentally about using multiple tools, because the questions we have to answer are far more complex than we are used to. It is critical to develop an internal ability (and fortitude) to be agile and nimble. Use the right tool to answer the question it is good at, and then move to the next tool and then the next one because it is better at this other thing. Web Analytics 2.0.

If all you know is WebTrends, or if all you do is spend your day with Omniture, or if your face is tanned from staring at Google Analytics, all day long you'll have a short, fruitless career in this field.

#6: Malcolm Gladwell is right, it takes 10,000 hours.

I don't think I ever appreciated what it takes to just stay current and, in hindsight, never comprehended what it takes to become good. I mean really good.

Not to be overly dramatic but. . . blood, sweat and tears.

Most blogs die in 30 days, most Twitter accounts are full of crap and have few followers, most of us never read books, most of us rarely curate a really good list of RSS feeds and then read every post, most of us will never engage in a meaningful online debate, most of us will not start a website and care and feed it and implement 15 tools every single year purely to learn and push the universe known to us, most of us never consider taking a class or two to learn new skills, most of us refuse to work a few hours extra every week, most of us refuse to experiment with what makes us uncomfortable.

And yet it takes all that to be good at what you do.

Do the job you were hired to do as well as you possibly can, regardless of whether it is a dream job or not. Then in small and big ways, figure out how to spend an extra five hours a week on you. Just five.

Your company is not going to give you this time. Your spouse / boy friend / mom might not even give you that time. Your God might be against it.

But you'll have to figure out how to watch a little less TV, spend a little less time on social media, a little less time on dinners, a little less time watching movies on planes, a little less time launching attacks on attacks, a little less time on parties, a little less time in meetings, a little less time in the bathroom, a little less time. . . something or the other. Half an hour stolen here, half an hour stolen there, invested in learning and doing and failing at the thing you want to get good at. 

Else accept that you'll be an okay Analyst, yet another non-relevant blogger, a Twitter blowhard, a winner of promotions via political machinations rather than adding actual value, always a conference attendee not a case study, someone on the professional train to somewhere convenient to others and not you.

Not that there's anything wrong with that.

Work is not everything.

But in the context of work, know that if you want to get good the path goes through putting in the 10,000 hours of hard work. Even if you just want to get good at what you do you'll still need to put in hours and hours of effort. What's more you'll have to be self-motivated because no one can want it for you, you'll have to want it for yourself.

And yes, yes, yes, there is more to life than professional accomplishments, but that's not what this post is about! [See: Nine Rules To Work / Live By]

For me trying to get really good is a journey not a destination, one on which I am still in the early stages.

There you are, six things I wish I knew before I started my career.

I hope you'll add a pinch of passion and a dash of daring and that your journey will be rich, rewarding and resplendent with glorious achievements.

All the best.

Ok it's your turn now.

In context of digital data analytics what are some of the lessons you have learned in your professional journey? Do these lessons resonate with you? What might I have missed that you would like to add?

It would be delightful to have your comments, feedback, perspectives & critique.

Thanks.

I Wish I'd Known That. [Digital Analytics Edition.] is a post from: Occam's Razor by Avinash Kaushik

Some of the powerful new data points are:

• Unique visitors – ga:visitors metric has been updated to support the true number of unique visitors for any date range (instead of the daily unique visitors). It also supports significantly more valid combinations.
• Organic Searches – The number of organic searches within a session.
• 10 new Adwords dimensions – Including Matched Query (what people searched for, not the bid term) and Placement Domain (which site you content ads were running on).
• Search Result Views – The number of times a search result page was viewed.
• 3 Time dimensions - To simplify plotting graphs.

We also included 111 calculated metrics to make it easy to query most common calculations in the reports, such as bounce rate, cost per conversion, and margin. Now, getting calculated metrics is both more convenient and in parity with the calculated metrics in the UI.

You can see a complete list of the new dimensions and metrics in our public changelog.

With all these dimensions and metrics, it can be time consuming to find the values you are looking for. To simplify this, we’re also launching a new interactive dimension and metric search tool. You can use this interactive tool to search for a dimension or metric using its search-as you-type feature. Even more exciting is the ability to easily determine valid dimension-metric combinations just by selecting the dimensions/metrics that you want to request. Here’s a screenshot:

If you’ve spent any time looking through your traffic sources in Google Analytics, particularly your referral sources, you may have noticed a lot of your traffic coming various mail sources:

Clearly it’s not terribly useful to see your traffic broken out this way. At the very least, you would want to consolidate all of those mail.yahoo.com sources.

But if you think about it, it probably doesn’t matter a whole lot which email service provider a visitor happened to be using when they clicked to your site. Perhaps it’d be better if we just consolidate all of those email sources into one entry. Not only would this significantly clean up reports, but it would also allow you to see the overall impact of traffic coming from email to your site.

The easiest way to handle this is by using filters:

While this is called a custom advanced filter, it’s fairly straightforward. If you noticed in the first screenshot, all of traffic coming from email had “mail” somewhere in the source and “referral” as the medium. So this filter takes all of that traffic and changes the source of that traffic to webmail.

Also note that we set “Field B Required” to “Yes” and “Override Output Field” to “Yes”. Both of these settings are necessary in order for this filter to work. The first setting ensures that we only change data for visits that fit the requirement we set in Field B, while the second one ensures that all visits that meet the filter requirements will have their source overridden with “webmail”.

Once you’ve applied this filter to your reports, your email visits going forward will be consolidated into a single entry:

webmail / referral

Now if you tend to look at your traffic sources by medium, you’ll notice that even after this filter, webmail traffic is still included with the rest of your referral traffic:

If you’re OK with this, that’s fine, but it is possible to separate your email traffic out by adding a second filter in addition to the first filter:

This is similar to our previous filter, but here we specify that we want to filter on visits with a source of “webmail” and change the medium of those visits to “webmail”. Filters build on each other, so it’s important that this filter come after the previous filter, otherwise it won’t find any visits with “webmail” as the source.

After you make this change, your report on mediums should look more like the following:

This makes it much easier to differentiate between true site referrals and traffic that’s coming from email.

Here are a couple final considerations:

1. It’s possible to use advanced filters to break out webmail traffic by source. That is, you could have yahoo / webmail, aol / webmail, etc. The filters for this are much more complicated, however, and you may have trouble finding a good reason for knowing that an email visit came from aol instead of yahoo. But if you decide you need help with this we can help you via one of our Google Analytics technical support plans.

2. Getting a lot of webmail traffic may also be a sign that you aren’t properly tagging your emails. If these are emails that you are sending out, especially from some type of autoresponder, then you should consider tagging these in some way. Click here to find out how we usually tag these emails.

As always, feel free to ask questions in the comments about this topic or let us know if you found this technique useful and/or how you used it.