Diving into Data (Web Analytics) looking for key Insights / Advice of Avinash.

Diving into Data (Web Analytics) looking for insights.
Advice of Avinash:
Segmentation:

New Nirvana Rule: Never report a metric (even God’s favorite KPI) without segmenting it to give deep insights into what that metric is really hiding behind it.
The power of segmenting a metric is that you peek behind the curtain and find out more about the metric. These are the benefits that you will gain:
1.    It is impossible to segment any metric without putting in the effort to understand what we are reporting and the business value that the metric represents. This is hard work but what does not kill you makes you stronger. :~)
2.    Segmenting allows you to quickly hone in on areas of deeper dive from which will emerge key insights that will drive real and meaningful action.
3.    Our senior executives and decision makers don’t understand all the complexity and magic that is a web experience, showing them segmented trends is a extremely effective communication tool (and the best part is you barely have to talk, the picture will tell the story).
4.    You will earn a big fat bonus and promotion.

KPI Attributes:
1) What is good for Jane it might not be good for John. Every web business is unique !!
2) Do not go for perfection: Good is enough !!
3) Critical few baby, critical few !! Few KPIs:Most common: 3. Maximum: 4 KPI for each website analysis.
4) KPI Lifecycle (Half of KPI will die in one year), because your competitor become stronger. So apply Lean Six Sigma Process (Define, Measure, Analyse, Action, Improve or Eliminate). If your KPI do not give you insight, kill it, be brutal and kill it, and then define a new better KPI .

Each KPI must be:
1) Uncomplex
2) Relevant
3) Timely
4) Instantly useful

Do Not forget of Conversion Trinity
1) Relevant
2) Value
3) Call to action

Alex Rojas Riva

Ninja Analytics, HiPPO's, Master in Digital Marketing Plan & Direction, Web & Social Analytics, Free Consultation, Mobile: +44 (0)755 2839713, Skype:janibalrojas.

I can't improve your Website by 1000% but I can improve 1000 things by 1%, if you execute my recommendation immediately or action to take care.

There are Data known known, there are Data we know we know. We also know there are Data known unknowns; that is to say we know there are some Data we do not know. But there are also Data unknown unknowns -- the ones we don't know we don't know. And if one looks throughout the web history, it is the latter category that tends to be the difficult ones.

Segmenting Brand and Generic Paid Search Traffic in Google Analytics

Segmenting Brand and Generic Paid Search Traffic in Google Analytics

Thursday, June 26, 2014 | 11:09 AM

Labels: AdWords, Announcements, Features

Many advertisers with paid search campaigns advertise on queries mentioning their brand (e.g., “Motorola smartphone” for Motorola) and also on generic searches (e.g., “smartphone reviews”). Because the performance metrics for ads shown against brand and generic queries can be vastly different, many advertisers prefer to analyze these two groups separately.  For example, all else being equal, searches containing the advertiser’s brand name often have higher clickthrough-rates than those that don’t.

Automatic classification

To make analysis of brand and generic performance as easy as possible, we’re introducing a new feature which automatically identifies brand-aware paid search clicks tracked in Google Analytics. We use a combination of signals (including the clickthrough-rate, text string, domain name and others) to identify query terms which show awareness of your brand.  You can review our suggested brand terms and then accept or decline each of them. It’s also easy to add additional brand terms that we’ve missed. 

With the resulting list of brand terms, we classify your paid search traffic in GA so that you can split your “paid search” channel into two separate channels: “brand paid search” and “generic paid search”. This can be done both for Multi-Channel Funnels (for attribution purposes) and for the main Google Analytics channel grouping. See this straightforward step-by-step guide to get started.

Industry feedback

Back in 2012, George Michie from the Rimm-Kaufmann Group, a leading online marketing agency, called analyzing brand and generic paid search together “the cardinal sin of paid search”. We showed him a preview of our new solution and here’s his reaction:

"I've been arguing for many years that advertisers should look at their brand and generic paid search separately. There are massive differences in overall performance - but also in more specific areas, like attribution and new customer acquisition. 

Google Analytics now makes it a lot easier for advertisers to segment brand and generic paid search into separate channels. I'm sure this feature will help many more advertisers measure these important differences - and more importantly, take action on these new insights."

Getting started

Finally: note that this feature works for all paid search advertising, not just Google AdWords. It will roll out to all users in the coming weeks.

To get started, use the step-by-step guide to set up separate brand paid search and generic paid search channels. We’ve already suggested brand terms for every GA view with sufficient paid search traffic.

Posted by: Frank Uyeda, Software Engineer, Google Analytics

Digital Marketing and Measurement Model

There is one difference between winners and losers when it comes to web analytics. Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. Losers don't.
This article guides you in understanding the value of the Digital Marketing & Measurement Model (notice the repeated emphasis on Marketing, not just Measurement), and how to create one for yourself. At the end you'll also find some additional examples to inspire you.
Let's go…
The root cause of failure in most digital marketing campaigns is not the lack of creativity in the banner ad or TV spot or the sexiness of the website. It is not even (often) the people involved. It is quite simply the lack of structured thinking about what the real purpose of the campaign is and a lack of an objective set of measures with which to identify success or failure.
I've developed the Digital Marketing & Measurement Model as a simple, structured, five step process to infuse this much needed thinking. Here is what each step in the process helps accomplish:

Step one is to force us to identify the business objectives upfront and set the broadest parameters for the work we are doing. Sr. Executives play a key role in this step.  Step two is to identify crisp goals for each business objective. Executives lead the discussion, you’ll play a contributing role.
Step three is to write down the key performance indicators. You’ll lead the work in this step, in partnership with a “data person” if you have one.
Step four is to set the parameters for success upfront by identifying targets for each KPI. Organization leaders play a key role here, with input from Marketing and Finance.
Step five, finally, is to identify the segments of people / behavior / outcomes that we’ll analyze to understand why we succeed or failed.

Simple, right? It is harder than you might think, “soft” work always is. Before we go into each step in detail I want to share something extremely critical. The scope/breadth the model has to cover.
A complete, and competent, Digital Marketing & Measurement Model will focus on three key areas of your marketing, and in each answer the cluster of questions provided:

1. Acquisition.
How are you anticipating acquiring traffic for your website / YT video / whatever else you are creating? Did you cover all three components of successful acquisition: Earned, Owned, Paid media? How would you prioritize each? Where are you spending most of your efforts?
2. Behavior.

What is the behavior you are expecting when people arrive? What pages should they see? What videos should they watch? Should they visit repeatedly? Are there certain actions they should take? What is unique about your effort that ties to an optimal experience for a customer?
3. Outcomes.

What outcomes signify value delivered to the business bottom-line? A download? A phone call to your call center? A qualified online lead? Signing up for email promotions? People buying your product / services ? A 95% task completion rate? A 10 point lift in brand perception? Simply put: Why are we undertaking this digital initiative?
My sincerest hope is that these questions will seed your discussions as you go through the five steps below. If your Digital Marketing & Measurement Model does not cover all three areas of your digital effort, then it is not complete. Please consider revisiting it. Don’t accept a mediocre model.
With that macro thought out of the way, let’s get going and look at a real example of the five step process to solidify this concept.
The business we are doing this for is a real estate company. I’ve picked a tough one because the main outcome is offline success. If they can create a good model then your job is much much easier!
Step 1: Identify the Business Objectives.
Ask this question: Why does your website/campaign exist? (Think of acquisition, behavior and outcomes.)
This is a difficult question to answer because it requires more thinking that you might anticipate. If you do it right at the end of step one you’ll have something that looks like this:

Identifying the business objectives mandates a discussion, multiple discussions, with the senior-most leaders in your company and working with them / sweet-talking their egos and hearts with gentle encouragement, to identify why the site / campaign / digital marketing invitiative exists.
Based on those discussions, in our case, we’ve identified three objectives: Create awareness, generate leads for the builders and highlight community events.
Here’s a great test. Your objectives should be DUMB:

Doable.
Understandable.
Manageable.
Beneficial.
If they are too out there, you'll never get anywhere. If they are too vague, nothing will get done. If they are too lame, they'll inspire no one. Go for real world, clear, executable and those that deliver value to the company (short term and long).
Are your objectives dumb?
Pro Tip: One way to ensure success is to forget that you are creating a set of videos or that you are building a site to host downloads of pdfs or that you are trying to mimic a campaign from Europe. Really, really, really think hard about why you are doing what you are doing. Get the answer from your executive/client.
Step 2: Identify Goals for each Objective.
Drilling down to identify website/campaign Goals requires critical thinking from both the Management, Marketers, and the Analysts – with Management in the leadership role.
My definition: Goals are specific strategies you'll leverage to accomplish the business objectives.
After going through some of the acquisition, behavior questions with stakeholders, here’s our model:

Clean. Has a clear direct line between Goal and each objective. Provides immense clarity.
To deliver on "Create Awareness," in this case, the site needs to support all the offline efforts along with having a relevant online traffic acquisition strategy.
"Generating Leads" comprises the twin goals of providing all kinds of information that will help potential home buyers to make their decision and to collect e-newsletter registrations as well as e-requests for an onsite tour of the model home by the builder.
Finally, "Highlight Events" is for prospective home buyers (visitors to our site). By making them happy with delightful events, at the construction site hopefully in model homes for sale, they can be converted into Net Promoters (to others) and Buyers (themselves).
These goals provide clarity, but they also contain large chunks of specific marching orders for what the Marketers and Analysts need to get done.
Pro Tip: This is super key: Macro + Micro Conversions! If the goals identified don’t cover all the jobs the site/campaign is doing then you might need to revisit your work.
Step 3: Identify the Key Performance Indicators.
Finally we get to deal with data!! I know you’ve been dying to get here. You’ll be the ideas leader here.
My definition: A key performance indicator (KPI) is a metric that helps you understand how you are doing against your objectives.
For each goal, sweat, and find the most hyper relevant KPI. This is what it will look like:

So amazing right?
I am sure your head is buzzing with all the possibilities for custom reports and things to report on, and how much clearer it is what you are supposed to do! Awesome, but hold your horses. We have two more steps to complete. Stay with me.
Pro Tip: Try to look for smart KPIs? Here’s specific guidance to help you…

Pick super awesome key performance indicators that truly reveal success or failure.
Step 4: Identify the Targets.
It is heartbreaking how few people complete this step. It is absolutely critical, in so many ways.
My definition: Targets are numerical values you’ve pre-determined as indicators of success or failure.
Why do you need targets? Consider this: You had an amazing campaign on YouTube. You got 1.2 million views. Is that great or awful? How do you decide? That is why you need targets!
Ok, so you also need them to plan your site / campaign / marketing initiative better. If you were responsible for getting 5 million visits in a month would you execute your campaign differently than if that number was 500k? Or if you were supposed to reach 1,000 CMO’s would you remember not to use Social Media as your primary acquisition strategy? That’s also why you need targets.
Targets can come from historical performance (how you did last time you / someone did something similar). They can come from other efforts (if my one hour long boring video can get 30k views in a week, should your two min peppy video get 1.2 million views?).
Seek people who are accountable (client, management, Finance), they will help you identify targets for each KPI.
Your Digital Marketing & Measurement Model will now look like this…

Now everyone knows what the company is shooting for. When you crack open Google Analytics, or other tools you’re using, you'll immediately jump with joy or weep when you see the KPI. You'll instantly know what is good and what is bad.
Pro Tip: If you have no targets then make something up. Use a number that if reached won’t embarrass you / your management / me. :) That is a good start; you can revise the number next month after you get the first blush of data. What’s important is that you never measure without having some sense of what good or bad performance looks like. The more experience you have, the better you’ll get at setting targets. Good targets.
Step 5: Identify valuable Segments for analysis.
This last part is one that is particularly meaningful to me because of its incredible value.
My definition: A group of people, their sources, onsite behavior, and outcomes.
When you log into Google Analytics or any other data source you are deluged by data and you could go in a million different directions.
Remember: We not only wanted focus, we wanted hyper-focus.
Take 10 more minutes from the key executives. Have a discussion with them about what the most important segments to focus on are for each goal.
Identify the sources of traffic, types of people desirable, their attributes, their behavior, business outcomes that they care about the most. And what customers to the site might want to accomplish. Balance for the company and the customers.
You’ll provide leadership here and if you did a great job then your DMMM will look something like this:

What groups of visitors were important? What visitor behavior is desirable? What a traffic source was Marketing focused on? Who are we trying to attract? What on our site is important – at least according to us? And more such questions are important to answer to get to the optimal segments.
Pro Tip: How to Identify Analytics Segments. Read. Act. Enough said.
Hallelujah, praise the lord you are done!
This was a lot of work, but I assure you that at this point you will thank God and your Cat that you worked this hard. You now have a structure that will guide your measurement efforts. The insights you derive will be of value because they are grounded in what’s important to the business and the leadership. And when you make recommendations based on data… guess what… action will be taken. Worth it, right?
Here's the sexiness: You now know what's important and where to start and what to focus on. Your boss/client knows what success or failure looks like and how to connect her/his business objectives to your data. Prioritized business focus for relevant data analysis!
You have the basis of a solid contract. Get the DMMM signed (preferably in blood!) so that all parties are clear on what everyone is supposed to be solving for.
Punch-line: Always, always, always work with the above "Marketing & Measurement contract" in hand.
Two Bonus Items.
Some of you might have noticed that I’d eliminated the Tour Conversions KPI in step five. That was simply to make the image in step five looks prettier. But worry not, with that KPI included our Digital Marketing & Measurement Model will have this beautiful final form…

Can we run the most fantastically actionable web analytics program in any company now? Yes we can!
One last gift for you.
When you create your own Digital Marketing & Measurement Model you don't have to use the format I've used above, you can add to it as you see fit.
I wanted to share with you a different format, and example. Below is the model for a retail e-commerce website with an online and offline presence:

 FY= Fiscal Year.

ABC= Authenticity, Benefits, Communication.

I hope that the two examples in this blog post will help inspire you to use the Digital Marketing & Measurement Model as the foundation of your web analytics efforts.
I believe, with every fiber of my being, that this is will empower magnificent success.
Good luck.

Occam's Razor
by Avinash Kaushik

Produce Actionable Insights: Mate Custom Reports With Adv Segments!

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99.9996253% of Web Analytics reports produced are utterly useless.
Partly because of a lack of any tie to business strategy (ensure you have a Digital Marketing & Measurement Model!), partly because they are out of the box standard reports that web analytics vendors create for “average” people (and we both know that you are not average!), and partly because all they do is present data in the aggregate (a punishable criminal offence if there ever was one!).
As a cure to this malaise, I’ve encouraged y’all to switch to using only custom reports (bring just relevant metrics and dimensions into one place, and throw away 90% of web analytics data that does not apply to you). Here’s a blog post: 3 Awesome, Downloadable, Custom Web Analytics Reports
Read the post and go from “OMG there are so many reports and I don’t know what to do with them” to “OMG I can’t believe just five reports give me 90% of what I need!”
My second prescription was to (repeatedly!) pimp the value of advanced segmentation. I can’t even think of two other things that are quite as life altering as segmentation for an Analyst and/or a Digital Marketer. You go from looking at amorphous globs of goop to a crystal clear understanding of people, their sources, onsite behavior and business outcomes. Here’s my most recent blog post (with downloadable segments): 3 Advanced Web Analytics Visitor Segments: Non-Flirts, Social, Long Tail
Read the post and go from “Arrrhhhh this web analytics is so haaaard” to “Awww… being data driven is so much fun!”
Despite the obvious and incredible advantages, precious few in our dear community have their web analytics existence centered on custom reports and segments. Here’s the hashtag: #heartbreaking
If that is due to the lack of a relevant example to enchant you with its native sexiness then let’s fix that problem. Here it is…

Enchanted?
No?
Okay here is a higher resolution version: Page Efficiency Analysis with Long Tail Advanced Segments
Now?
Maybe not yet. Okay let me break down the components.

Enchanting Analysis: Rule 1: Business Context.

Surprised that I am not jumping into telling you about metrics and dimensions and segments and all the other things that bring Analysts goose bumps? Remember all data is secondary. Your primary quest is to understand the business context, which in turn will dictate procurement of data.
Why this Custom Report?
We produce a ton of content on our site. Which content is most engaging? Which subject matter experts should we hire more of? What type of content (videos, demos, pictures, reviews etc.) do visitors value more? Which content delivers business or non-profit value?
These are very important questions to answer, and with content reports fragmented in tools like Google Analytics and, worse, metrics spread out across reports (or outright hidden), it is hard to answer those questions easily. That’s where my Website Content Efficiency Analysis custom report comes in. It hopes to bring all the key metrics into one place (no more hunting and pecking!) and help you analyze site content optimally. Log into Google Analytics and download the report here: Website Content Efficiency Analysis Report. The report you'll download is a V2 version from what you see in this post. It is more improved with a new technical analysis tab!
[If the report opens in a profile other than the one you want the report in, just scroll to the bottom and in the Profiles section you'll see Additional Profiles, click on the drop down, make your choice, hit Save.]
Why this Advanced Segment?
One of the key ways in which we get relevant traffic to our websites is to have them properly indexed by Google / Bing / Baidu / Yandex. Search Engine Optimization is key. But not just SEO or keywords or our brand name. It drives me bananas how much we still talk about words. Few people search with a word or two. People type phrases into search engines – some of them write entire stories – and those phrases and stories account for an enormous amount of traffic to your site.
[rant] It is so horrible that SEOs still get asked: “Can I rank #1 for word x?” Good lord! Wake up! [/rant]
So two relevant questions come up: How are we doing for the head (few, brand) words? How are we doing for the super important long tail search phrases?
Log into Google Analytics and download these two segments: 1-2 Word Search Query Visitors, 3 or More Word Search Query Visitors.
[If the segments open in the old version of Google Analytics simply open the new version in a new browser tab and copy the segment into the new version.]
We are not doing all this analysis because it makes us happy. It is mandated by the business reality described above. Always, always, always be a slave to business strategy/needs. Let that drive analysis. Don’t puke data out of Omniture/WebTrends and go looking for business problems to solve. Please.
Why Apply these Segments to this Report?
With the above two in hand you are now ready to answer the killer question: How are different pieces of site content doing in terms of SEO in driving visitors via head words and tail phrases, and is it delivering business value?
OMG! OMG! OMG!
Yes! Think of all the possibilities. The ability to focus people in your company on the right content creation. The opportunity to balance efforts between head and tail phrases. The chance to understand what is actually driving business value (you know: the thing that pays your salary!).
This is why as little children we told our moms we wanted to grow up and become Web Analysts. :)
Let’s break down various components of this enchanting bit of analysis. . .

Enchanting Analysis: Rule 2: Establish Macro Importance.

It is possible that I was completely wrong about doing this analysis. Before you waste precious hours of your life (and even more precious hours of your management team / client) always look at a 10,000 meter level view to see if there is any there there.
So that is what we do first, and here is that simple, yet absolutely critical, piece of data. . .

First you will notice that I was right!
Back up a little bit. What we are looking for is whether this analysis is important to do. My proxy for that is how much website traffic are we talking about? Often we end up obsessing about a keyword or campaign or xyz without realizing we are talking about 0.05% of the traffic. Sub optimal.
To the being right part… and this is where the Google Analytics UI is simply brilliant…
In a flash and a bang I can see that my first head segment (one or two words typed) accounts for 13% of the site traffic (yowza!) and the long tail segment (three words or more typed) accounts for an awesome 24% of the site traffic (zoowee mama!).
We’ve established that the analysis we are doing is worth doing, that the long tail is worth focusing on, and any insights we can find will have a material impact.
Life Lesson: In life, before you get too deep into any analysis, use a barometer to establish the work is worth doing. How much desirable traffic or desirable outcomes does your report represent? Be explicit about it and your boss will pay attention to your reports / analysis.

Enchanting Analysis: Rule 3: End-to-End view, or Death.

Very early in your analysis you want to establish a view of the dataset that gives you the end-to-end view of performance. The lack of this view is why I am so critical of standard web analytics reports. You can tickle GA, you can twitch Site Catalyst, or you can rub WebTrends just the right way and find the data. But they all conspire to work against you by not giving you want you want.
Why wait for the vendor? Pull all the data you need (and honestly only you know what you need) into one place. Don’t be satisfied with a report that just shows Visits and Bounces or Time on Site and Load Time or Goal Completion or (worse) %Exits or …. one of the many data distractions so liberally available.
Here is how I define end-to-end… Metrics on your report should give you clear understanding of your performance in these three areas: Acquisition, Behavior, and Outcomes.
So often we tend to obsess about acquisition (impressions and clicks and visits and abc), and sometimes we care about outcomes (revenue and conversions and xyz). It is rare that we care about behavior. You need all three.
In this report my acquisition metrics are Entrances and Unique Visitors – how many people came, how many entered on this page, and with a glance at both I get an idea of how many might have come multiple times.
My behavior metrics are Bounces, Pageviews, Avg. Time on Page – how many people choose to leave right away (“I came, I puked, I left”), how popular the page was for all visits, and how long do people stay on the page (if they stay on the site).
Here’s how that part of the report looks. . . 
 
Already you can start to see wonderful patterns in the data, and since you are not looking at the data in aggregate you can start to see how the two different groups behave.
Once more marvel at the approximately 2x more traffic you are getting from your long search queries people type into Google. Because you have behavior here as well you can start to notice the differences between behavior of the two groups (a lot more page views for the smaller head visitors, but significantly less time on site!). You can start to draw conclusions about the value of the tail.
While you are already doing better analysis because you are looking at Acquisition and Behavior together, this picture is of course incomplete. We are missing outcomes.
Should we be even more crazy about the tail folks since they spend so much more time, and there are so many of them? Perhaps.
Why not look at the bottom-line.
Our outcome metrics here are Per Visit Goal value (how much value each unique visitor adds to us each time they visit) and Total Goal Completions (for when you have multiple goals –and everyone should have macro and micro conversions!). Here’s the rest of the picture. . .
For the sake of clarity I am showing just the behavior and outcomes here; the report has all three in one place.
Delightful, is it not?
While the tail traffic does very well, 14,400 Unique Visitors delivering 3.057 Goal completions, the Per Visit Goal Value is significantly lower than the head traffic, 88 cents compared to 197 cents for the head traffic. So you can double your traffic, but the site is monetizing this traffic for a lot less than the head traffic.
So is the traffic any less valuable? Should you still invest in SEO for the long tail? What is the difference in the types of Goal Conversions between these two groups? What content is driving each set of behaviors? This and all other questions you’ll answer in the next steps. For now the job was to simply get an initial burst of solid starting points from the end-to-end view of the key metrics.
Life Lesson: Friends don’t let friends have reports that are missing one of these three elements in the metrics being presented: Acquisition, Behavior, Outcomes. Choose the metric(s) that is most optimal for you in each bucket, but if your reports don’t have all three buckets. . . rethink why you even have them.

Enchanting Analysis: Rule 4: Look for Surprises, Love.

This is very important. When you analyze data your defacto mode should be to look beyond the top ten rows of data. You should look for things that surprise you. Far too often we look for things we are looking for and we move on. Totally sub optimal.
In this step we’ll analyze the dimension we care about – website content (pages) – and answer the questions above. Which content acquires more head and tail traffic? Which content drives more conversions and business value? Which content does this and which one does that and which one drives deeper engagement and which one drives more bounces and is it only for the head or the tail phrases and which one. . .  so many lovely things you can dive into easily.

If you are using Google Analytics for analysis of an ecommerce website you can easily add Keyword as an option for the drill down. I've created that version of the report for you, click here to download it into your Google Analytics account: Content Efficiency & Keyword Drilldown Ecommerce Report. You also have the ability to filter to phrases and keywords that contain a word(s) that you are most interested in analyzing first. Finally, you can also create your custom report such that it drills down into the keywords used to get to that page (head or tail).
Any of the above methods will allow you to dive deeper and look at the actual keywords and key phrases easily. Now you can start to understand things to love in your SEO efforts and drink to the sad situations you’ll surely find.
And there is more. Rubber meets the road in this step. It is raw analysis that you are going to be doing here. Have a notepad next to you and jot down both the obvious insights that will drive immediate response, and write a love letter to your SEO and blow their brains about how many things you find easily in your data.
Life Lesson: Analysis is hard. Smart people do a lot of it. 

Enchanting Analysis: Rule 5: Create a List of Prioritized Actions.

When you apply relevant advanced segments to your custom reports you are going to find a lot of actions to take for your business leaders, frontline marketers, SEO contractors, etc.
Rule #5 is going to ensure that something is actually going to be done as a result of your blood, sweat and tears. Never give a long laundry list of “thing to do.” Ever.
Rather, convert the jumble of actions into a numbered list with the first item being the highest priority, then the second highest priority, and so on and so forth.
You are the person with most access to data and, thanks to rule #4, the person who analyzed the heck out of it. So now use that to create the numbered list.
How do you identify item number one for your list? This is where real Analysis Ninjas distinguish themselves, and leave the Reporting Squirrels in the dust. Compute the impact of each of your recommendations. If you paid $a to SEO for long tail phrase zxy it will add value $q. Use performance of existing words / visitors. Look at past performance. Look at competitive data. Make guesstimates (in the worst case scenario). But compute impact.
[Bonus]
For one specific and incredible way to compute impact please see item #8 in this post: Barriers To An Effective Web Measurement Strategy (+ Solutions!) The methodology outlined, illustrated below,…

…is exceedingly effective at showing the value of the action you are recommending, and the cost of the delay in implementation of the changes! This will allow you to make a very very effective prioritized list of actions.
[/Bonus]
Business leaders simply have a much, much easier time internalizing a numbered list (less thinking for them) and approving actions (more fame for you).
Life Lesson: Ninjas never submit long globs of text as observations or random actions. If you can’t prioritize, you’ve missed the most important step that creates data driven businesses.
You can see how deeply passionate I am about custom reports and the ability to truly find magnificently impactful things by applying advanced segments to them. I hope that the above example will make you pass all your current reports through the filter of Acquisition, Behavior and Outcomes. I hope you’ll never again look at any report without segments applied to them.
Good luck!
As always it is your turn now.
What is your favorite combination of a custom report and advanced segment? Do all your reports cover acquisition, behavior and outcomes? Why not? Got best practices to share for metrics that fall into each of the three categories? Do you have a segment you want to report on but your analytics tool does not allow it? How is your business doing when it comes to head performance and long tail performance?
Please share your tips, feedback and ideas via comments.
Thanks.

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Occam's Razor
by Avinash Kaushik

The Difference Between Web Reporting And Web Analysis

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Someone asked me this very simple question today. What's the difference between web reporting and web analysis?
My instinct was to use the wry observation uttered by US Supreme Court Justice Potter Stewart in trying to define
po rn: "I know it when I see it."
That applies to what is analysis. I know it when I see it. : )
That, of course, would have been an unhelpful answer.
So here I what I actually said:

If you see a data puke then you know you are looking at the result of web reporting, even if it is called a dashboard.
If you see words in English outlining actions that need to be taken, and below the fold you see relevant supporting data, then you are looking at the result of web data analysis.

Would you agree? Got an alternative, please submit via comments.
I always find pictures help me learn, so here are some helpful pictures for you. . .
This is web reporting:
And so is this, even if it looks cuter:

And while you might be tempted to believe that this is not web reporting, with all the data and the colors and even some segments, it is web reporting:

See the common themes in all the examples above?
The thankless job of web reporting, illustrated vividly above, is to punt the part of interpreting the data, understanding the context and identifying actions to the recipient of the data puke.
If that is your role, then the best you can do is make sure you have take the right screenshots out of Site Catalyst or Google Analytics, or charge an extra $15 an hour and dump the data into Excel and add a color to the table header.
So what about web analysis?
The job of web analysis mandates a good understanding of the business priorities, creation of the right custom reports, application of hyper-relevant advanced segments to that data and, finally and most importantly, presentation of your insights and recommended action using the locally spoken language.
See the difference? It's a different job, requires different work, and of course radically different skills.
Examples of web analysis? I thought you would never ask. . .
This is a good example of web analysis:

[And not only because it is my work! Learn more about it here: Action Dashboard.]
Notice the overwhelming existence of words. That's not always sufficient, but I humbly believe always necessary.
When you look to check if you are looking at analysis or reporting look for Insights, Actions, Impact on Company. All good signs of analysis.
Here's another example of really good web analysis:

[Click on the image above for a higher resolution version.]
Ignore how well or badly the business is doing. Focus on approach taken.
Here are some things that should jump out. . . . A deliberate focus on only the "movers and shakers" (not just the top ten!).  Short table: just the key data. Most of the page is taken up with words that give insights and specific actions to take.
Another example that I particularly like, both for the style of presentation and how rare it is in our world of web analytics. . .

[Click on the image above for a higher resolution version.]
No table, no rows, no pies. And yet data holds center stage with clearly highlighted actions.
Normally, we all do the column on the left (it might look different, but we have it). Unfortunately we don't appreciate is the power of the middle column ("segmentation reveled"). That is super important because it gives the recipients exposure to the hard work that you have done and in a very quiet ways increases their confidence in your work. Guess the outcome of that? They take the actions you are recommending!!
Analysts constantly complain that no one follows any of their data-based recommendations.  How do you expose your hard work? In a garish Las Vegas show girl fashion where all the "data plumes" are, unsexily in this case, hanging off the body? Or, in quite concise ways? Only one of those two work.
One more? Okay here you go. . .

[Click on the image above for a higher resolution version.]
Diana has loads of observations, supported by visuals (sometimes it really helps to show the search results or the emails or the Facebook ad) with highlights (actually lowlights) in red, and finally recommendations.
And note the tie to outcomes (another common theme in all examples above). In this case, the search improvements are tied to the increase in donations I can make because of sales of my book. 1.5 extra smiles per month! (All my proceeds from both my books go to charity.) A good way to get attention from the "executive" and get him or her to take action.
Do that. A lot. Be creative. Yes it is hard work. But then again glory is not cheap, is it?
Exceptions to the rule.
Not every output you get from your Analyst, or "Analyst" :), with loads of words on it, instead of numbers, will be analysis. Hence my assertion that "I know it when I see it." Words instead of data pukes is just a clue, read the words to discern if it actually is analysis or a repeation of what the table or graph already says!
In the same vein not every output that is chock full of numbers in five size font, with pies and tables stuffed in for good measure, is a representation of web reporting. It is hard to find the exceptions to this rule, but I have seen at least two in nine years.
Top 10 signs that you are looking at / doing web analysis.
Let's make sure this horse is really and truly dead by summarizing the lessons above and using a set of signs that might indicate that you are looking at web analysis. . .

#1. The thing that you see instantly is not data, but rather actions for the business to take.
#2. When I see Economic Value I feel a bit more confident that I am looking at the result of analysis. Primarily because it is so darn hard to do. You have to understand business goals / outcomes (so harrrrrd!) and then work with Finance to identify economic value, and then you have to configure it in the tool and then apply advanced segments, and then figure out how things are doing. That is love. I mean that is analysis! Or at least all the work that goes into being able to do effective analysis.
#3. In the same vein, if you see references to the Web Analytics Measurement Model (or better still, see it in its entirety on one slide up front), then you know that the Ninja did some analysis.
#4. Any application of algorithmic intelligence, weighted sort, expected range for metric values (control limits), or anything that even remotely smells of ever so slightly advanced statistics is a good sign. Unknown unknowns are what it's all about!
Also mere existence of statistics is not sufficient. All other rules above and below still apply. :)
#5. If you see a Target mentioned in the report / presentation, then the Analyst did some business analysis at least. See the top right of the picture immediately above.
#6. Loads and loads and loads of context! Context is queen! Enough said.
#7. I have never seen web analysis without effective data/user segmentation. I think this statement is in both my books. . .  "All data in aggregate is crap." Sorry.
#8. If there is even a hint of the impact of actions being recommended then I know that is analysis. It is hard to say: I am recommending that we shift this cluster of brand keywords to broad match. It is harder to say: I am recommending. . . and that should increase revenue by $180,000 and profit by $47,000. Look for that.
#9. If you see more than three metrics in a table you are presented with then you might not be looking at analysis.
#10. Multiplicity! If you see fabulous metrics like Share of Search (competitive intelligence) or Task Completion Rate (qualitative analysis) or Message Amplification (social media) then they are good signs that the Analyst is stepping outside Omniture / WebTrends. I would still recommend looking below the surface to ensure that they are not just data pukes, but the good thing is these are smarter metrics.
User Contributions:
#11. From Carson Smith: If someone looks at your analysis / report / presentation / dashboard and has to ask "and… as a result?", then it might be reporting. What happened should be obvious.
[I love applying the "Three Layers of the So What" test to any analysis I present or see. I ask "so what" three times. If at the end of it there is no clear action to be taken then I know it is just web reporting, not matter how great it looks or how much work went into it. Ask "as a result?" or "so what?" to your work!]
#12. From Chuck U: 1) If it can be automated, it's probably not analysis 2) If your data warehouse team says they can automate it for you, then it's definitely not analysis. [#awesome! -Avinash]

Can you think of other signs? Please share your suggestions via comments. I'll add the best ones to this list.
In the list above, and in the examples in this post, you see my clear, and perhaps egregious bias for business analysis and business outcomes and business actions and working with many parts of the business and business context. But I've always believed that if you and I can't have an impact then why are we doing what we do?
I hope you've had some fun learning how to distinguish between web reporting and web analysis. It is a fact of life that we need both. The bigger the company, the more they want data pukes, sorry, reporting.
But if you have "Analyst" in your job title then you perhaps now have a stronger idea of what is expected of you to earn that title. If you have hired a "web analysis consultant" and are paying them big Rupees then you know what to expect from them. Don't settle for data pukes, push them harder. Apply the rules above. Send their "analysis" back. Ask for more. Raise your expectations!!
I hope now "you'll know it when you see it," and have more datagasms!
Okay, it's your turn now.
How would you answer the question about the difference between web reporting and web analysis? What signs do you look for when evaluating the work of your Analyst or Consultants?
Please share your thoughts via comments below.
Thanks.
PS: In case you are curious here's the current official definition of po rn, as outlined in Miller v. California:

(a) whether the 'average person, applying contemporary community standards' would find that the work, taken as a whole, appeals to the prurient interest,
(b) whether the work depicts or describes, in a patently offensive way, sexual conduct specifically defined by the applicable state law, and
(c) whether the work, taken as a whole, lacks serious literary, artistic, political, or scientific value.

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