Recently there's been a spate of infographic tools popping up (e.g., easel.ly, venngage, and infogr.am). Okay, I'm not sure if 3 qualifies as a spate, but it sure seemed like a lot in a short period of time. I gave Infogr.am a whirl, and it appears to be the front runner in terms of capabilities. Unlike easel.ly, you can *actually input data* into your infographic! What a novel concept. Venngage was hit and miss in terms of it accepting the data I entered. Infogr.am also has a bug in that you can't have the number 0 in your data. Go figure.

I took Nathan's data for Rambo kill counts and used a bit of it for my example image. These are the number of kills in the various Rambo movies where Rambo was wearing a shirt, wasn't wearing a shirt, and the sum of both. You can check out the live version to see it in all its animated glory. Unfortunately, you can't change how ginormous everything is.

Like the other tools, it lets you select from a few templates to get you started. It also lets you create just an animated chart if you don't want to go the full infographic route. Right now there are only 5 chart types (including one very odd frog chart), but they've been very actively updating the tool in the last couple of days.

It's still a bit buggy, but worth keeping in your bookmarks for future reference if you're a beginner or non-programmer.

[via infosthetics]

A.B.T. Always be testing. This is the mantra of successful website owners. But what does that mean? Well you should be testing everything, but how can you really know what’s wrong with your website, or why people are having problems, or generate possible fixes? Simple. Regular and repeated cycles of usability testing. Check out our infographic on how to use usability testing to increase your conversions after the jump…

Embed this image:

<div style=”width:604px;”><div><a target=”_blank” href=”http://www.lunametrics.com/wp-content/uploads/2012/05/usability-infographic-full.gif” ><img width=”600″ height=”5800″ alt=”How to Use Usability Testing to Increase Your Conversions” src=”http://www.lunametrics.com/wp-content/uploads/2012/05/usability-infographic-full.gif” style=”border: #FFFFFF 1px solid; padding: 1px;” /></a></div><div style=”text-align:right; font-size:11px; margin-right: 5px;”>Designed by <a href=”http://twitter.com/sayfsharif” >Sayf Sharif</a> for <a href=”http://www.lunametrics.com” >LunaMetrics</a></div></div>

TileMill is a tool that makes it easy to create interactive maps. Soon they will be adding some new features that will treat maps more like images in terms of modifying the look and feel. This will allow you to apply blending to polygons and GIS data.

AJ Ashton made these examples that are quite compelling, beautiful, and just touch on the possibilities. I can envision many different types of data being drawn with blending techniques as opposed to simply flow diagrams and the like. It will be interesting to see what comes out of these new features.

[via @bonnie]

Related

• Many Eyes Now Has Better Mapping Visualization
• What DC Metro Routes are Most Common?
• Explore large image collections with ImagePlot

The Analysis Exchange is a wonderful organization that I’m proud to be a member of. I’m sure you’re similarly excited about it if you are reading this blog! The fact that it is all volunteer driven makes each project so rewarding because you know the people want to be there. You can tell how much the end result of the project means to the individuals receiving it. And you can do it over and over again.

In fact, that is one of the best parts about the Analysis Exchange – there really isn’t a limit on what an individual student, mentor, or organization can get out of it. I’m extremely grateful so many individuals want to participate in this effort, but I know there are some of you out there that want to do even more. Good news: you can! And here’s how.

If you are already a Mentor, go find another coworker or friend that could be a Mentor as well. With so many new analysts entering the field there is a need for industry veterans to step up and guide this new wave of analysts. You’re already doing a great job by donating your time and you only have so much time to give. Life is busy and that’s totally understandable. The good news is that it doesn’t take up any additional time to have a conversation over lunch, mention your project on Twitter, or talk up the Exchange at the next conference you attend.

If you are a Student and are having a hard time getting a project, go local. And for that matter, if you’re a Mentor that wants to really help out the Exchange, go local. Wendy is great, but she can only do so much to bring in new organizations. Help her out; I did it and you can too! Earlier this year, after having some great conversations with the President of my local Ad Council, we worked out an opportunity for me to present digital analytics at a workshop.

The workshop was extremely basic – Digital Analytics 101. Many of the 40+ people in attendance didn’t even have Google Analytics running on their website. They didn’t know anything about it but they were excited to learn. We started with simple definitions and moved into some baseline reporting that Google Analytics could provide. The session went extremely well and I even had requests to do additional presentations! The grand finale was that they could get experienced professionals the help them through this, for free, with the Analysis Exchange. I couldn’t ask for a better set up.

My goal was simply to bring more organizations into the exchange, but if you really want to get in on a project, the best way to do it is bring in a local organization. I guarantee they’ll select you if you work with them to set it all up!

My final piece of advice is to pace yourself and set a personal goal relating to the Exchange. It is easy to keep putting off a project just as it is easy to do one after another and decide it takes up too much time. If you set a goal of 1 project every X months (whatever is right for you) you’ll find that you look forward to your next project because there’s a plan to do it and a plan to finish it. Scoping it out always makes it seem more manageable.

All of these are things you can do, outside of directly working on a project, that can provide a huge benefit to the Exchange and give you a satisfying feeling of accomplishment along the way. Take a moment to think if any of these sound right for you. Sure, it takes a bit of extra effort, but something tells me I’m talking to the right crowd.

- What are the best books to learn about PPC?

- Are Organic search results more trustworthy than Paid?

- How should I structure a multi-national PPC ad campaign?

- Why am I seeing PPC data in my Analytics when I’m not running an ad campaign?

LunaTV is a weekly segment where LunaMetrics team members answer your questions from across the web. Got a question you want answered? Tweet at us at @LunaMetrics with #lunaTV and we’ll answer your question!

Transcript:

Phil:
Hi I’m Phil Anderson, Director of Analytics at LunaMetrics.

Brittany:
And I’m Brittany Baeslack PPC Manager at LunaMetrics, and you’re watching LunaTV, where we answer your questions from around the web.

Phil:
If you have any more questions after today’s session feel free to visit our industry blog. We publish 3 times a week and if that isn’t enough we do trainings all around the country. So Brittany, I hear you have some questions for us today

Brittany:
I Do! Our first question is,

“What are the best books on paid search and SEM and why?”

In my opinion I think that the Entrepreneur magazine publishes a lot of great books called their Ultimate Guides ; they have the ultimate guide to Google AdWords, which is obviously just specific to Google, but then they also have the Ultimate Guide to Pay Per Click Marketing, Ultimate Guide to Facebook Adverting , etcetera. I think that the best route to go in terms of getting all the information you want, in terms of  varying degrees of SEM, because the books are very in-depth, they cover a lot of information rather than trying to squeeze in all the information together. One more recommendation is actually the Google AdWords for Dummies, I hear from a lot of people in our seminars that is a great starting point, especially for those people who don’t have any experience.

Phil:
Great! I had a question that I found on Quora, which is,

“Are organic search results more trustworthy then paid search results, and do people know the difference between those?”

The fact is that a lot of research has been done on this topic and you know some people are of the belief that people can’t tell the difference between paid and organic, but really most people can tell the difference, and the click trough rate on organic search results is a lot higher than paid search results, which is all the more reason you need to write really compelling ad content for your paid search results.

Brittany:
Ok, another question from Quora was

“What is the best way to structure an international multimarket PPC Campaign? Should it be centralized or decentralized to local teams?”

This is a great question, it comes up a lot. You definitely want to start with having separate campaigns, absolutely want to have separate so  that you can target separately for location and language, remember those are two campaign level settings those are not things that can be done at the ad group level. You want to make sure then that your ad copy is obviously relevant to what the person is searching and what language they’re searching in, obviously that would make us believe that this is an ad group setting but since that this is something we cannot change at the campaign level in terms of what language and what location we’re targeting we need to have separate campaigns so that someone who’s searching in Spanish say is not seeing an English ad and vice versa. In terms of whether or not they should be centralized or decentralized in my experience I would definitely recommend making these centralized have the teams work together since it is one account regardless of where the account is showing and what sort of markets we’re in. They do normally have one goal, so you want the team to be working together so there is better communication.

Phil:
Our last question was, this is real common to get in analytics,

“What if I’m seeing paid search in my analytics but I’m not paying for paid ads?”

Well, first thing is really make sure there’s not some AdWords out there somewhere, that somethings that’s not running, that you’re not aware of. The most likely reasons this occurring is the tagging that is on the links; essentially if you tag something with a sourcing medium of Google CPC it’s going to show up as paid search in analytics so you want to be careful to make sure people aren’t just copying links around and otherwise make sure you don’t have your AdWords out there running rogue

If you have any more questions feel free to visit our website and register for training, it is LunaMetrics.com/training, you’ll see the link below.

Brittany:
Bye!

So I got to thinking, since I'm on this pie chart kick, "what would be the worst pie chart ever?" And I decided it would be a Venn diagram made with pie charts. I laughed to myself, imagining such a creation. Then I thought, somebody's probably done this. And indeed, there's an app for that.

At long last, the power of Venn diagrams and pie charts combine to turn the world of mathematics on its head! If you've ever felt the need to create Venn diagrams with pie charts, or wished your pie charts could overlap to provide even more informative data, then Venn Pie-agrams is the app for you!

I'll leave it at that.

Wow, Manuel Lima, Senior UX Designer at Bing, got through a world of information in this 11 minute RSA Animate video. He spoke about the topic for which we all know him - networks. Beginning with the tree as a symbol of relationships (e.g., Aristotle's Tree of Knowledge), Manuel then quickly sweeps through many concepts through the centuries to finally land on a modern day approach to relational information, the web or network. As trees are no longer capable of representing the complexities of the modern world, we have to find new ways to visualize these structures or perhaps even find a universal structure. His talk is loaded with beautiful examples of trees and networks.

If this fast paced animation is above your processing capacity, you can view the more austere real world video of Manuel instead. It has the bonus of an interesting interview with him in the last 6 minutes.

“The theme this year, At the Crossroads, explores convergence—how entertainment, advertising, publishing, television and news companies are finding ways to be meaningful and profitable online, uncovering the overarching lessons applicable to all industries as they forge new paths in the digital space.”

Gary Ragusa (VP Business Development) and I will be heading up there for the day and would love to meet up with you if you’re attending. Drop by the Visual Revenue booth and we’ll happily walk you through Instant Headline Testing, Real-time Recommendations, Postion Importance and Performance and Active Site Overlay, to name but a few of our unique features – or put another way our vision for ‘The Bloomberg Terminal of the Newsroom!’ Hope to see you there.

Cheers,

Charlie :-)

When I first learned of this new development, I had quite a few questions. What do the Knowledge Graph snippets look like? When do the snippets show up? Where does the data come from? Why is Google doing this? Who cares? So I decided to find the answers… and share them with you.

What do the Knowledge Graph snippets look like?

When there are multiple meanings for a search query, Google may offer a choice, as in the first example. The specific types of information that are displayed in the Knowledge Graph snippets vary from query to query and certainly seem a bit random first. In many cases, Google does utilize the same snippet formats for certain groups of queries, but the specific information displayed may still vary. Google certainly displays relevant information types that people commonly search for. In particular, note the “People also search for” section.

When do the Knowledge Graph snippets show up?

According to Google, the following applies (for now) regarding when the snippets might be displayed:

• Only queries that are a “person, place, or thing” for…
• English-based users in the U.S. will trigger the snippets.
• This specifically includes, but is not limited to, queries involving a “book, movie, sports team, location, dog breed, roller coaster, or famous person”.
• However “companies, video games, and cars” are currently specifically excluded.

From what I can tell, the Snippets will also only show up for:

• Concrete nouns – as opposed to abstract nouns, or verbs, adjectives, pronouns, prepositions, etc…
• Major “head” key phrases – for example the query “Earth” triggers the snippets, but the query “Earth pictures” does not. The long tail does not apply here.

Where does the data come from?

According to Google, the Knowledge Graph is derived from an enormous pool of diverse data sources. Google literature has specifically made mention of the following:

• Wikipedia
• Freebase – incidentally acquired by Google nearly 2 years ago, and also the only source in this list linked to in Google’s own literature about the Knowledge Graph.
• Subject-specific sources such as Weather Underground, World Bank, and CIA World Factbook.
• Google’s own immense stores of search data.

Why is Google doing this?

Well, I have a few theories:

• Google wants to flex its muscles. Take that Bing!
• Google is playing around with what to do with that real estate on the right.
• Google continues to stay committed to improving its core product by evolving its search capabilities beyond mere recognition of “strings” of characters and into understanding of concepts (“things”) and semantics.
• Google wants to increase time spent on Google. Consider the following:
• Google is competitive with Facebook in most categories, but is being completely destroyed when it comes to how many total minutes are spent on Google versus Facebook.
• The information in the Knowledge Graph snippet alone will cause most search to spend a few extra seconds reading.
• Nearly all the links inside the Knowledge Graph snippet are to Google queries featuring Knowledge Graph snippets. This provides cause for people to become stuck in the Google loop.
• I’ll bet you everything in my pocket that there will be a huge increase in average time spent on site for queries involving Knowledge Graph versus queries not involving Knowledge Graph.

Who Cares?

You should care if you:

• want to predict the future of search.
• spend a substantial part of your average work day doing SEO.
• work in SEO with the following: “book, movie, sports team, location, dog breed, roller coaster, or famous person”. Or any major head key phrases that are nouns.
• have a vested interest in mobile search. The Knowledge Graph snippets are displayed slightly differently (and more prominently) in mobile and tablets – specifically for Android 2.2+ and IOS4+.
• are a nerd.

How can I learn more?

I got your back.
Resources from Google

• http://insidesearch.blogspot.com/2012/05/knowledge-graph-for-mobile-and-tablet.html
• http://googleblog.blogspot.com/2012/05/introducing-knowledge-graph-things-not.html  The “Official Blog announcement”
• http://www.google.com/insidesearch/features/search/knowledge.html “product page”
• http://support.google.com/websearch/bin/answer.py?hl=en&answer=2620861 Answers what you might see from knowledge graph and when you’ll see it.

Other Good Resources:

• http://news.cnet.com/8301-1023_3-57435114-93/google-bringing-new-smarts-to-search-with-knowledge-graph/ is a nice general overview with a helpful image slideshow in the middle.
• http://searchengineland.com/google-launches-knowledge-graph-121585 is a solid analysis by SEO expert Danny Sullivan.
• http://www.internetmarketinginc.com/blog/3-seo-opportunity-tactics-with-the-new-google-knowledge-graph/ is a smart discussion on the trend of search to becoming more about semantic understanding and less about specific words, and how adjust macro level SEO strategy accordingly.

Nerd Notes
Also below are some random musings from a certain SEO geek on the matter.

• Wikipedia data shows up a lot. The flames of Google’s love affair with Wikipedia continue to roar.
• I have yet to see any ads on knowledge base articles. I’m just guessing, but I doubt this will last. I have read that the ads already exist. I wonder if they will incorporate sponsored results directly into the snippets?
• I’m very curious to see how and if Google is utilizing “rich snippets”- microdata, microformats, and RDFa – to assist in the Knowledge Graph. There appears to be plenty of conjecture, but no definitive statements yet. Personally, I would be surprised to see the rich snippets completely ignored here.
• Knowledge Graph data is being integrated into Google Docs via the optional “research pane”.
• I think the incorporation of the Knowledge Graph snippets will work to Google’s advantage. It’s a helpful and interesting feature already. Further, the ability for the Knowledge Graph to increase time spent on site can be very lucrative, as long as Google can manage to smoothly incorporate advertisements and quality snippets without upsetting users. Certainly, Google’s first priority is ensuring users’ smooth adoption of the Knowledge Graph.
• “The people also search for” section is fun to play around with. Boy, would I love to get a hold of the raw data used for that feature.
• Expect a noticeable impact on the search volume trends for many search terms influenced by the Knowledge Graph snippets.
• It’s really, really worth playing around on Google with queries related to your website(s). You may find some interesting discoveries that you could take advantage of, and it will help you understand how and when Google incorporating the knowledge graph into search.
• It is interesting to note what happens when there is a choice for “See results about”. Example: search “cats”, then click on “cat” the animal, and note that Google automatically queries “all about cats.” As you can see, such default queries could really benefit the pages that happened to be optimizing those longer tail terms.
• For a while now, search has been becoming less about the matching of words and more about matching the predicted meaning of the searchers queries with what the content of a web page/site means. I believe the Knowledge Graph is a distinct milestone in this evolution.
• For a while now, thriving search engine optimization firms have been focusing less on the matching of words on the pages and anchor text with high volume queries and focusing more on delivering content that people want. I believe the Knowledge Graph represents a distinct milestone in this evolution as well.

The OECD's Better Life Index which debuted last year to much fanfare has been updated with some great new features by Moritz Stefaner.

The concept and beauty of the original piece remain intact. However, the experience is made better by the ability to compare to different demographics. For instance, after I adjust my Better Life settings, I can see how my settings compare to other women my age in the US, or to French men. It's fun to compare to different people around the world and watch the flowers readjust themselves to the various comparisons. It invokes a sense of global community and humanity.

It also has better sharing. It offers the usual suspects, plus you can embed your index on your site. Equality between men and women is always a big issue, so that's addressed in the new version as well. You can select to see the split, and it also shows both gender and social inequality per indicator when you drill down to the specific country level.

This is an excellent update to an already great tool. I'm glad the OECD sees the value and continues to invest in it.

[via @jcukier]

Why Analysts Should Understand URLs

URLs are fundamental to the internet. And, while web sites are having their digital dominance chipped away by social media and mobile apps, URLs remain a core component of the Language of Digital.

For analysts, there are two key reasons that a solid grasp of URLs matters:

• Web analytics tools — Google Analytics, Adobe/Omniture Sitecatalyst, Coremetrics, Webtrends, and the like all pack a wheelbarrow’s worth of data into a customized URL every time a user takes a tracked action; you can see a 4-minute video on that subject or read a much more detailed explanation as to the mechanics of that process
• Pages on the site (and hackery therein) – some web analytics platforms use the URL (or some part of the URL) as the core means for reporting “Pages” data (Google Analytics, for one); some don’t (Sitecatalyst); either way, understanding the different components of a URL and how that affects the data feeding into your analytics tool (and how you can occasionally tweak a URL to get some supplemental data without doing a single lick of development on your site), is important!

Lengthy preamble complete… Let’s dive in!

The Anatomy of a URL

Although each URL is a single string of numbers, letters, and special characters, each URL has four distinct components:

• Protocol — always present
• Hostname — always present
• Path or Stem — always present…but sometimes is, basically, null
• Parameters — optional (but this is where some of the real fun can happen)

Below is a fictitious URL with each of these components identified:

When a URL is “executed,” a couple of things happen:

1. The magic of the internet occurs (browser mechanics, DNS resolution, etc.)  to actually get that request routed all the way through the interwebtubes to a web server somewhere; the mechanics of this are beyond the scope of this post.
2. That web server interprets the request (the URL plus some other information that invisibly — and equally magically — comes along with it) and figures out what information needs to get sent back to the requestor

In that second step, the URL gets broken up into its four distinct components. And, if you actually start digging into web server logs, you will find that each of these components is stored in a separate “field” in each log entry. If you actually enjoy digging into web server logs, then, well, you’re not alone. You officially have one of the markers used to identify career digital analysts!

Component 1: The Protocol

The protocol is pretty fundamental, but it’s also the least interesting to a digital analyst. It’s simply an indication of what overarching framework is being used to transmit data back and forth:

• Far and away the most common is http, which stands for (did you know this?) “Hyper Text Transfer Protocol.”
• When people started buying stuff and accessing sensitive information over the internet years ago, a more “private” version of http came into being, which was https. What’s the “s” for? Well, “secure,” of course! When sites are accessed using https, it’s tougher to get at some data, but that protocol exists for a reason, so don’t start trying to hack your way around that. https was actually at the core of Google’s decision to start encrypting keyword search data for users who were logged into Google when they did searches, if you’ve been following or are affected by that kerfuffle.
• FTP is another fairly common format, which is used more for “file”-related data; FTP stands for “file transfer protocol.”

That’s really all there is to the protocol. It’s good to know what it is, but it’s not super interesting.

Component 2: The Hostname

The hostname is a bit more interesting than the protocol, and is, basically, the “domain” to which the URL is referring. The main hostname for this site is “gilliganondata.com.” But, “www.gilliganondata.com” also works, and the fact that both exist for the same content is where things start to get a little interesting.

The hostname can actually be broken down into several parts:

• .com (or .edu or .net or whatever) — this is actually the “TLD” or “top level domain.”
• “gilliganondata.com” is often referred to as the “domain” for the site, but that is not, strictly speaking, correct. Technically, “gilliganondata.com” is a subdomain of “.com.” But, almost no one talks about sites that way, so let’s just say that the domain is “gilliganondata.com”
• “www.gilliganondata.com” is actually a subdomain of “gilliganondata.com.” I could have multiple subdomains all hosted on different servers — search.gilliganondata.com, recipes.gilliganondata.com, etc. The “www” is something of a throwback convention and, usually, set up to work exactly the same as the base domain. BUT, every few months, I come across a site where <sitename>.com doesn’t load, but www.<sitename>.com does. This is purely a configuration miss on the part of the site owner that is easily fixed.

That last bullet was getting really long, wasn’t it? Subdomains do matter:

• If you’re not careful, “www.<yoursite>.com/” will get treated as a different page than “<yoursite>.com/” by search engines and/or your web analytics tool. That’s not good.
• If you have content hosted on a totally different system than your main site (a jobs board, a store locator, a discussion forum, etc.), a best practice is to create a new subdomain for that site but keep it under the same domain. This is usually very, very easy — do a Google search for “CNAME record” and you’ll be totally set on that front.
• There are cookie (visit and visitor identification) implications when it comes to the domains and subdomains in use on a site, but this post is going to be long enough without me diving into those. Trust me. Fewer domains is better.

So, even though the hostname is a pretty small part of the overall URL, it’s important, and there is interesting stuff that goes on with that component.

Component 3: The Path

The path (or stem) in the URL is analogous to the file path for a file on your computer. It often has an inherent drilldown/tree structure that uses “/”s in some organizing fashion. The path includes the filename, if there is one: index.htm, products.php, about.html, etc.

The path is somewhat static. That doesn’t mean you can’t have a content management system (CMS) that generates new paths like crazy, but, typically, each unique path represents either a core “page” of content or a core content template (that then uses parameters — which we’ll get to next — to update the actual content).

For news sites and blogs (including this one), you will often see “date” data built into the path structure (that’s what the “/2012/05/22/” in the URL of this post is — it’s showing that the post was originally published on May 22, 2012). For any site that cares at least a half of a whit about search engine optimization, you will see keywords relevant to the content as part of the URL (thus “the-anatomy-of-a-url-protocol-hostname-path-and-parameters” being in the path of this post).

There is a lot of flexibility in the path component of the URL, but the path ends — and this is an always-always-ALWAYS statement — when a question mark appears in the URL. A “?” in the URL is a demarcation that denotes the end of the path and the beginning of…

Component 4: The Parameters

Not all URLs include parameters. And, for web analytics campaign tracking purposes, parameters often get added to URLs for pages that were developed without giving parameters a second thought. That’s what makes them fun!

Parameters are nothing more than a list of variables in the URL. There is no limit (well, there are overall URL length limits, but lets not go there) to the number of parameters that can be included in a URL. But, there are a few hard-and-fast rules about parameters:

• They must be separated from the URL’s path using a “?”
• They must be separated from each other (when there are multiple parameters involved) using a “&” (this “must” is a little squishy — you can put subparameters inside of a single parameter using a little developer legerdemain…but that, too, is beyond the scope of this post)
• They must be structured as a “key-value pair.” The “key” is the name of the variable, while the “value” is the actual, well, value of the variable. The key goes on the left side of an “=” sign, and the value goes on the right side.

Key-value pairs are pretty simple to understand. You see them all the time as you browse the internet. Just look for “=” signs in URLs. All that the Google Analytics URL Builder for campaign tracking does is tack a series of key-value pairs on to the end of a protocol + hostname + path URL that you provide.

The order of parameters almost never matters!

Let’s say I had a URL that looked like this:

http://yoursite.com/index.htm?source=twitter&content=socialwelcome

We have two parameters in this URL: “source” and “content.”

This URL would generally produce the exact same resulting content for the visitor:

http://yoursite.com/index.htm?content=socialwelcome&source=twitter

All I did was change the order of the parameters. And, since they’re just a list of variables, sites typically won’t care about the order one whit.

Also (and I alluded to this earlier), you can generally add parameters to a URL without affecting the functionality of the page or what content gets displayed.

Let me repeat that, because it’s one of the keys to how web analytics tools capture traffic source data:

You can generally add parameters to a URL without affecting the functionality of the page or what content gets displayed.

When you add campaign tracking to a URL, you are doing something that the original developer of the content to which you are linking likely did not give a single thought. Try it on this page if you want to. Make up a key-value pair or two and tack them on the end of the URL for this page and see if the content changes. It won’t. Depending on what you tacked on, you’re probably introducing some squirrely data into my web analytics tools…but that’s okay. I’ll survive.

Parameters get used for lots of things:

• For web analytics campaign tracking
• To customize and personalize content that is presented to a visitor
• To drastically update the content shown on a page by using a parameter value to give the key piece of information as to what content/products/information should be displayed (this used to be much more prevalent, but it tends to have undesired SEO ramifications)

A single URL can include parameters that get used for many different purposes. As I noted, the order doesn’t matter. And, as I implied, most sites simply ignore parameters that they don’t recognize.

One caveat: occasionally, I come across a site where a developer took a shortcut in the implementation of the site such that unrecognized parameters do break the page. To date, I have never tracked down any of the handful of developers who have done this, so my desire to flog them has gone unfulfilled. “Extraneous” parameters should never break a site.

One more note: web analytics packages handle parameters in different ways:

• Sitecatalyst – since Sitecatalyst relies on pageNames rather than URLs, extra parameters don’t cause any web analytics issues
• Webtrends – historically (this might have changed), Webtrends stripped ohf all parameters in URLs by default and just used the hostname and path to identify pages; usually, this works fine, but there can be cases where you find you need the parameter to distinguish between different unique pages, and Webtrends has the ability to add those parameters back in through the configuration of the profile
• Google Analytics – by default, the only parameters that Google Analytics strips off of URLs are the Google Analytics campaign tracking parameters (utm_medium, utm_source, utm_campaign, etc.). But, you can go in and tell the tool to strip other parameters off as well.

Managing parameters effectively in your web analytics platform is one of those things that keeps your reports cleaner. If your site has, say, 300 basic pages, but your web analytics Pages report is maxxing out with 10s of thousands of rows, the chances are that you have a parameter management issue.

– when a question mark appears in the URL. A “?” in the URL is a demarcation that denotes the end of the path and the beginning of…

Bonus Component: #

I don’t know that I would consider the hash sign (or “fragment identifier”) as a core component of the URL, but it’s worth a mention. Hash signs — #s – at the end of URLs refer to locations within the main page. Most commonly, these get used as intra-page “bookmarks” of sorts. Both Wikipedia and FAQ pages tend to use these quite bit. For instance, if you view the source of this page, you will see the following in the HTML right at the beginning of this section:

<a name=”bonus_component”>…</a>

And, if you tack “#bonus_component” onto the end of the URL for this page, the page will load and jump right down to this section.

Pretty Simple, Right?

I hope you found this helpful. URLs are key to the workings of the internet, and understanding their component parts and how you can both decipher them and manipulate them is one of those things that comes in handy when you least expect it!

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Data visualization certainly matters when it comes to conveying information effectively, but when it comes to sharing, the answer is no: having data to represent is not a critical ingredient in infographics. More than half, or 53%, of the top 30 graphics do not contain data visualization. And by data visualization, we mean visual objects that are sized, colored, or positioned to represent numerical values.

I think what they actually mean is that data visualization is not the sole factor of a successful visualization. Since they are only analyzing the top 30 infographics, the minority 47% that had data visualization are still very successful. It would be a different story if the 53% of infographics without dataviz were the top successes and the 47% with dataviz were the bottom losers.

My hunch is that the successful infographics posted on Visual.ly are popular because, like other viral content, they strike a nerve, are of the moment, are humorous yet relevant, or have some other je ne sais quoi.

According to Internet Week’s nifty new map, Visual Revenue is just one of hundreds of tech start-ups in New York. When I attended a VentureBeat event in October, I met local entrepreneurs looking to disrupt everything from online retail customer service to taxi cabs. I have friends building online clipboards and music discovery apps. You can’t help but be impressed by the wealth of ideas this town attracts (the best of which, of course, is ours :) ). We’ve recruited engineers and sales people from Pennsylvania, Argentina, India and The Netherlands, all of whom have joined us here in New York to help us realize our vision.

VR is located on the Associated Press newsroom floor, which goes nicely with my journalism degree and our goal of becoming the Bloomberg Terminal of the newsroom. We walk past editors and reporters on our way to lunch and the giant red New Yorker sign looms over our rooftop basketball/pizza sessions. With media giants and copious talent in our backyard, we couldn’t have asked for a better place to build our company. I’m sure our CEO mentioned it when he was gallivanting with the mayor in February.

New York isn’t just a melting pot of cultures and backgrounds, but of industries and ideas as well. Oh and food carts. Visual Revenue is predictably made in NYC!

I'm a sucker for anything cute and bubbly, and the U.K. Energy Consumption Guide created by Epiphany is no exception. It combines a vertical scrolling site with a lot of data visualization about different types of fuel and how they've been used historically. Most of the charts are solid and the interaction adds an even higher level of clarity and understanding.

While I like this circle packing chart, I'm sure there will be doubters. It's very similar to McCandless' natural gas visualization that received a lot of flack. But generally speaking, anything that is engaging and welcoming garners a little extra time from the visitor to make sense of it.

You may even be thinking, “My website doesn’t sell anything, so I can’t measure conversions.” I beg to differ.

Every website is selling something.

And therefore:

Every website can measure conversions.

Figure out what you’re selling, and you’ll move from counting to optimizing, from recording history to creating opportunity – by collecting and taking advantage of conversion data.

What are you selling?

If you have an e-commerce website, or a site designed to generate leads for sales, you already know what you’re selling. The easiest conversion to track is one tied to revenue… or donations, for non-profit sites.

But what do other sites sell? What about university sites or hospital sites, blogs or content-heavy sites, tech support or help forum sites, government agency sites – what are they selling? And if you have an e-commerce or lead gen site, isn’t there more to what you’re selling beyond the obvious products or services?

To answer the question “what are you selling”, let’s consider an even more basic question.

When I go to a client’s offices to do analytics training with their team, I begin with a big slide that bluntly asks: Why do you have a website? After some nervous laughter, they realize I’m not going to give them the answer. Then a couple folks get the ball rolling, and we’ll end up filling a whiteboard (or two or three).

The point of the exercise is that there are many ways to think about the value of your website. And when it comes right down to it, they all involve “selling something”… whether it’s directly related to revenue or not.

Measure the value of your website

Think about selling as “persuading” or “convincing” your website visitors of the value you have to offer. Then think about the ways your visitors demonstrate that you’ve convinced them. Those are your conversions!

Visitors who’ve been convinced of the value of a blog will subscribe, become regular commenters, share your content on social media. If you have other types of content, visitors may interact with your site by viewing videos or downloading files or using custom tools or widgets you’ve created.

Similarly, a high level of user interaction shows that visitors are finding value in tech support or help forum sites. Is there evidence of a user community, i.e., are visitors returning to ask more questions or search for answers? Are they rating articles as helpful? Do they regularly contribute answers?

University websites serve diverse audiences from prospective students to alumni, from university staff to the surrounding community. Visitors may show they value your university site by making use of the online application process, participating in the alumni career center, or reading and sharing university news, to name just a few examples.

Hospital sites may offer everything from patient services to community health information to news about academic research. If your hospital site has integrated resources for managing appointments, or insurance and account payment, or even creating personal diet and exercise plans, are visitors taking advantage of those resources? Are visitors in the academic and medical communities, or the community at large, accessing and sharing your news content?

And think of all the things you might do on a government website: pay your taxes, apply for licenses or benefits, look up real estate assessments, read pending legislation, contact your representative… the list goes on and on.

When you’ve “sold” a visitor the value of your website, “conversions” like the above activities happen. They all demonstrate the value of your website and they’re all behaviors you can measure.

Steps for getting started

The next step is collecting conversion data so you can start to take full advantage of goal-related features like multi-channel funnels and attribution modeling. In future posts, I’m going to show you how to set up goals and measure these “not e-commerce” conversions in Google Analytics.

Which types of goals are you most interested in setting up for your website? Are there others you’ve considered that I didn’t mention? Let me know in the comments.

I warned Nathan that I was going to drop a pie bomb on Flowing Data. Well, here it is; it's labeled by its creator as a "feather chart." I really hate to pick on people. I truly think Jon made a valiant attempt to use pie charts innovatively. However, this chart is not effective.

The chart uses 11 million ACT records (for international readers, that's a standardized test in the US). It's trying to show the relationship between ethnicity and test score and income and test score.

I created the y-axis as the ACT composite score, and then used self-reported income bands as the x-axis. Both are discrete, categorical values, even though ACT is numeric. ACT increases bottom-to-top, and income bands increase left-to-right. At the intersection of each variable is a pie chart, sized by the number of students in that group, and colored by ethnicity

The only problem is that the overlapping pie charts occlude one another. Unless one section of the pie chart dominates and allows the other sections to peek out over the top of the previous pie, then the chart is useless. For instance, in the first feather, there's no way to know if the orange section is 40% or 60% for most of the chart.

This chart has really good intentions, but the data would be better served with a bean or violin plot. If you're a subscriber, you can check out Nathan's great tutorial from last week about visualizing distributions.

In preparation of my UCI Extension course next month, and later on, Rutgers Social Media and The Arts in the fall, I tested out PowerPoint and various other software, such as Camtasia, to record presentations.   In the process of doing so, I saw I could make my presentation into a video and place on YouTube.

The video is 40 minutes long, hope you get a chance to listen to it, or parts of it.

Gundega Strautmane, a Latvian textile artist and designer, visualizes social and physical networks in a show called Relational Ornaments. The networks are created using various sized pins to depict nodes and threads connecting them to show relationships. Bringing visualization into the tactile world lends it a weight not able to be achieved on a computer screen. It allows the viewer to pause, spend time with the information, feel it, sense it in a more holistic way. The placement of pins and threads is imprecise because they are placed by hand giving the work a very natural, organic feel rather than the rigidity of the exact calculations of programming.

[via The Network Thinkers]

This Wall Street Journal graphic shows who's selling (or sold) a percentage of their Facebook stocks and who's holding steady.

This graphic is the perfect example of why I'm a proponent of the pie chart. First, they stuck to two values per pie chart. That makes it easy to read. Next, they used the size of the pie to denote the number of shares. Finally, they used small multiples to easily compare both the shares owned by each entity as well as change in percentage of shares being sold.

I'm sure bar charts would be fine too, but WSJ really used all aspects of the pie chart very effectively.

[via Barry Ritholtz]

There are as many definitions of data visualization as there are definers, but at the root of this term that has been around for many years is the goal that data be visualized in a way that leads to understanding. Whatever else it does, it must inform. If we accept this as fundamental to the definition of data visualization, we can judge the merits of any example above all else on how clearly, thoroughly, and accurately it enlightens.

By data art, I’m referring to visualizations of data that seek primarily to entertain or produce an aesthetic experience. It is art that is based on data. As such, we can judge its merits as we do art in general.

Either one, done well, is worthwhile, assuming that it fits the task at hand. If the task is to help a particular group of people understand something, then data art is not appropriate, no matter how well it is executed. If the task is to entertain or engage an audience in a particular emotional experience, then data visualization probably isn’t appropriate. If the situation requires that both objectives are achieved, then a deeply informing and aesthetically beautiful visualization would be in order. Although it is quite easy to make any data visualization aesthetically pleasing, it takes a great deal of skill as a visual designer and information communicator to make one beautiful.

People make better decisions when they’re based on understanding. For information to be understood, it must often be presented in visual form. This is because patterns, trends, outliers, and a sense of the whole as opposed to its parts require a picture for the human brain to see and comprehend. Data visualization is essential. Visualizing data effectively is vital. Anything less is frivolous, costly, and harmful.

How in particular is data art—visualizations that strive to entertain or to create aesthetic experiences with little concern for informing—harmful when it masquerades as data visualization?

1. It suggests that data cannot be visualized without training in the graphic arts. As such, it works against the democratization of data. In fact, anyone of reasonable intelligence and a little training can present data effectively. It’s vital that this ability spreads more broadly across the population, because it can play a role in making a better world.
2. It features ineffective practices as exemplars of data visualization. It encourages people to present data in ways that are difficult to perceive and understand simply because they are prettier or more entertaining, which is rarely relevant to the task.
3. It keeps the practice of data visualization spinning its wheels, never able to progress beyond the mistakes of the past. Best practices of data visualization have emerged through many years of research and experience. “Those who cannot remember the past are condemned to repeat it” (Santayana).

I am personally and painfully acquainted with each of these problems. For this reason, I try to differentiate data art from data visualization and encourage others to do so as well.

Take care,

Internet Week NY

I was at Internet Week events at the #IWNY headquarters Wednesday and Thursday; the yearly event was quite packed and there were several good sessions.  I was there mostly for networking and to listen for ideas from which to build my own ideas on top of (which is usually what happens when I go to events, since the information is usually a pony show of brands showing how great they are in using Social Media).  To get anything much out of #IWNY, I almost have to take the taking points of the speakers (or the responses they provide to questions) and build my own answers (because most of the speakers don’t provide much of anything that would be remotely to an answer).

For example, today I listened to a session How to Make Videos that People Will Watch (fully expecting to learn something that I might pass on to Rutgers students next time I teach Social Media and The Arts (this fall).  Instead, I ended up listening to a discussion on how brands could predict what content would be viral (in order to invest in it’s development).  Of course the people on the panel said it was impossible to fully predict what was viral, but it was possible to develop your relationships and presence, which you could use, later on, to help spread content that might suddenly go viral.

I, listening to this back and forth between speakers and audience asking questions, saw a solution of combining the distribution network with certain algorithms that would suggest the potential for surfacing content to be viral, based on a few different ideas that are circulating around, such as congruency, emotive strength, network involvement and “paired meme synergy”.  The panels tend to be about brands strutting out their ideas, though I have tended to feel less interested in what Coke or Oreo is doing, and more in the potential methods one could use, irrespective of what kind of brand or organization one is taking about.

Or it could be the sessions I listened to in the public areas, was confused, at least in my mind, with sessions going on in the corner room, as what I was hearing as the last session on viral marketing techniques was also about brands strutting, all over again.    It’s almost as if, no matter what I listened to, it was mainly about what brands are doing with social media that they wanted to talk about.

Of more interest was the first meetup of the NY Mobile Startups group at OMGPOP/ZYNGA headquarters in NYC that I stumbled onto tonight where Dan Porter, CEO of OMGPOP along with the OMGPOP designers and engineers spoke about how to make it in mobile.   The organizer, Chieh Huang started out by telling the packed office suite to consider Founder Dan Porter’s words as someone who speaks his mind freely, no matter what is on it.  Well it was certainly interesting to hear Dan speak about how he arrived at the place he is in his life today, his company just being bought by Zynga.

Dan Porter spoke about the rise of Facebook games and Zynga, which follow each other (see below), and that does seem to be the case.

Dan talked about how to get exposure for a mobile app, and when it makes sense to develop one -

• Thought the idea of developing websites was come and gone and mobile apps are where all the action is
• Mobile apps can be shared in ways that websites can’t
• Mobile apps are better at promoting brand awareness because the app is on the device (like a perm book mark) and can be seen over and over, plus it much easier to share with others and gain viral spread  than websites.
• Technical improvements in app performance translate directly into more game sales, even down to the millisecond (this was confirmed from Zynga’s own data) which Dan talked to.
• Mobile is based on short sessions, things have to happen quickly, its a different mindset and approach than websites.

If I had to do it all over again, I would have recorded the entire session tonight.

Montreal

The conference I spoke at was pretty good, and my session was moderated by Patrice Leroux  (though most of the sessions were in French, mine was one of the few in English) – it was a quick trip there, unfortunately, as I left I lost my iPhone, had to get a new one.  Oh well.

Interesting Thoughts and Links

• Interesting discussion on how most presentation software sucks, especially for what people use it for.
• NY Mayor Bloomberg shows a Made in NYC Tech Job Map.
• Interesting article in the Google Analytics Blog on the Next Generation of Measurement which includes some interesting findings such as on average, customers interact with a brand 4.3 times over a two day period before they finally make a purchase, and mobile is now 8% of all conversions in Google Analytics, and mobile conversions have grown by  180% in just the last year.  The biggest challenge for brands deploying analytics is picking the right attribution model.
• Community Managers using Facebook should know how to generate and talk to these 5 reports.
• GM drops out of Facebook Advertising (it’s not working for them) but Ford swears by Facebook Ads….hmm.
• Have to check out Easel.ly to generate Infographics.
• Ballonduck launches – got interesting press, requested to try it out.
• BuddyMedia released this infographic showing the abundance of different platforms out there for social – but left off several names that should have been in the list – still, an interesting collection of tools and categories.

That’s it for tonight – have a bunch more posts to do, hope to have more shortly.

It is very common to see the mobile homepage of a news media site mirror the story order and arrangement of its desktop counterpart – and this seems irrespective of whether a native or web app is in place. We have unique audience and front page data available at Visual Revenue that proves this a suboptimal strategy.

With that said, there are many reasons for replicating homepage programming across channels – whether that be technical restrictions or a desire for consistency. Both very valid reasons. However, technical handicaps should rarely be used in defense of an optimal user experience and a consistent editorial tone might not be a warranted concern, given that other channels such as RSS, email and social are already different editorial experiences to that of the desktop homepage. Further to this, consumption data suggests that the audience does not consume content on both channels, desktop and mobile, at the same time, adding additional ammunition to the concept of separate programming.

A great example and very fine news destination in its own right is the local Bergensavisen newspaper [1]. Find below an exciting visual of the above described challenge, or optimization opportunity, if you will.

As you can see, the desktop homepage is replicated on the mobile homepage. The performance, where front page CTR was chosen as a proxy for success, simply does not replicate.

Here lies the opportunity and we encourage all publishers we work with to take advantage of this. Remember, this might be as simple as introducing one feature story on top of the mobile edition that is programmed manually by editors.

Cheers :-)
/ Dennis (@dennismortensen)

[1] Bergensavisen owner, media conglomerate A-pressen, (a Visual Revenue customer) kindly allowed us to show the above screenshots. Without a doubt, they are, one of the more sophisticated publishers we know and their platform integration across 65 newspapers, websites and mobile destinations is simply impressive. Don’t believe that they are not working this angle as well.

This is a topic that a lot of you are interested in, judging by the amount of traffic and shares that post got. So I decided build on Robbin’s post by creating a template that you can all use for your own attribution modeling needs. The Attribution Modeling Tool is a Google Doc spreadsheet that has all the formulas you need built right in. It will do the following types of modeling:

• First touch
• Last touch
• First and last touch
• Linear

(Click to enlarge)

Get your copy of the Attribution Modeling Tool here. Once it’s open, go to File > Make a copy so you can edit it.

The second sheet (MCF Data) is where you paste in the data that you export from the Top Conversion Paths report in GA (refer back to Robbin’s post if you need more details). Specifically, you’ll need to copy the first three columns of data, starting at row 8 (the first row of actual data below the headings Basic Channel Grouping Path, Conversions, and Conversion Value). Don’t copy the last row of data, which is just the totals.

* TIP: Before you export your Top Conversion Paths report from GA, make sure to show 500 rows, or as many rows as you need to get all of the paths and data. The Attribution Modeling Tool can accommodate up to 500 rows of data.

The first sheet (Attribution Models) gives you the numbers and graphs of the value of each channel using each of the above models. The remaining sheets (which are hidden) do all the heavy lifting. There are around 14,000 formulas in this spreadsheet, so it may take a few seconds or longer to fully load or update.

Insights from attribution modeling

Remember, attribution modeling let’s us divvy up the conversion value to various channels that led up to that conversion. For example, look again at the graph above (click to enlarge). This shows us that Direct visits are worth nearly $85,000 with a last touch model, with Organic Search and Paid Search being worth about $26,000. But look at how things change with the first click model. Now Direct, Organic Search and Paid Search are each worth around $44,000.

If you’re only looking at the last touch attribution, you may be tempted to put less money into your search marketing and SEO efforts. You may be foolishly thinking that the people who purchase all come to you directly, so why should you pay? But as you can see above, a lot of people who come to you directly and buy were introduced to your site from a paid or organic search. Otherwise, they may have never come back directly and purchased.

 Your Turn

Go get the Attribution Modeling Tool and play around with it. Do you find it useful or a waste of time? Anything surprise you? Bugs or other unusual quirks (Google Docs are know for those)? Let us know in the comments!

Fortunately both of these challenges are becoming less and less of an issue. Digital analytics providers are increasingly able to accept page performance data, either directly as in the case of Google Analytics “Site Speed” reports, or indirectly via APIs and other feeds from solutions like Keynote, Gomez, Tealeaf, and others allowing the most widely used digital analytics suites to meaningfully segment against this data on a per-visit and per-visitor basis.

Additionally, thanks to Web Performance Optimization and the recent emergence of solutions that allow for multivariate testing of different performance optimization techniques, business stakeholders and analysts are increasingly able to collaborate with IT/Operations to devise highly targeted performance solutions by geography, device, and audience segment. Recently I had the pleasure of working with the team at SiteSpect to describe these solutions in a free white paper titled “Five Tips for Optimizing Site Performance.”

You can download the white paper directly from SiteSpect (registration required) or get the link from our own white papers page here at Web Analytics Demystified. If you want a quick preview of what the paper covers I’d encourage you to give a listen to the brief webcast we created in support of the document.

• Download the White Paper
• Watch the Webcast

If you’re thinking about how you can better measure and manage your site’s performance we’d love to hear from you. Drop us a line and we’ll walk you through how we’re helping clients around the globe get their arms around the issue.