I just wrote a guest post about cause, effect and split testing (and a bit about measuring the value of content).
I just wrote a guest post about cause, effect and split testing (and a bit about measuring the value of content).
The past couple of months I’ve been seeing more and more discussion about breaking into web analytics as a career.
There are plenty of articles out there with great career advice.
Jim Sterne recently put together a list of resources and links for starting a career in web analytics.
I don’t want to repeat what others have already said, but I do want to add some fodder for thought that I don’t seem to be seeing other people mentioning.
As I mentioned in my previous post about selling web analytics, web analytics is just a tool.
A means to an ends.
Think of a carpenter’s tool box – hammer, saw, screwdriver, drill, etc.
Yes, you need to be proficient using these tools to be a good carpenter, but the point is that you’re using these tools to make something!
Which brings me to my point.
In order to be successful in web analytics, you need to “make something with your tools”.
You should be using web analytics in order to provide value, specifically providing actionable information.
In order to provide information that is actionable, you need to have a good understanding and some real world experience in the realm you’re trying to improve.
While many online activities can be optimized using web analytics, here are some categories that are commonly optimized using web analytics.
Each of the above topics can and should be using data in order to improve the results.
A common “life-cycle” using web analytics to improve something is:
The bounce rate on our homepage is 68%. Domain experience tells you that this is abnormally high and can/should be reduced.
Why it happened (analysis of the data together with domain expertise)
Looking at the homepage I see it’s way to busy. Two column layout with equal size columns makes it hard know what to focus on. No clear headline and multiple competing calls to action.
What’s next (domain expertise on how to make improvements)
Split test different layouts, calls to action, headline, amount of content.
Ideally you should be able to provide recommendations for the actual variations to be tested, and not just say you should test this.
So, if you want a career in web analytics, you need to become proficient in one or more of the above topics so you’ll know how to answer the questions “why it happened” and “what’s next”.
It’s not enough to just tell people what’s broken –
You need to tell them how to fix it.
As always, comments are greatly appreciated.
I just noticed a tweet from analyticspros:
Jeff gillis from @googleanalytics announces new updates to adwords search funnels: up to 90 days back, actual query, unique paths #emetrics
This is GREAT news!
Previously search funnels only showed data back 30 days, which is adequate for many sites, but if your conversion event often happens after 30 days (which is often the case with large item purchases and B2B) you weren’t getting the full picture.
I have not see this mentioned anywhere else, so it’s probably hot off the “press” at eMetrics.
Update [Oct 6]: I just noticed that the official adwords blog has this update
I’m looking to move AnalyticsImpact.com from wordpress.com to a different managed solution. WordPress.com is very limited in terms of plug-ins or themes.
So I come across a page with a big red button to sign-up:
Screenshot from http://pressceo.com/wordpress-hosting/
Overall it looks fine, but clicking on the button simply leads to a larger version of the image! Clicking on the button literally leads to http://pressceo.com/wp-content/uploads/signup.jpg
I laughed and thought I’d share :)
In all fairness, the rest of the site does seem a very professional and I’m guessing (hoping) they fix this soon.
How to Sell Web Analytics
While I was at the Google Analytics Certified Partner summit this year, someone came up to me and asked:
How do you sell web analytics?
This is a question I deal with quite often, both internally within the agency I work for and when trying to convey the value of web analytics to clients.
The short answer is that you shouldn’t be trying to sell web analytics.
Web analytics is a tool, a means to an ends.
It has no inherent value by itself. It’s only through the analysis of data and providing actionable insights that it creates value.
You should be selling the value that can be gained by a proper web analytics implementation and actionable analysis.
Marketing people talk about selling the benefits, not the features.
Web analytics is a feature.
Improving the bottom line is a benefit.
A simple analogy is HTML (the code used to create web pages).
Imagine if you tried to pitch HTML services to a business. They would probably be scratching their heads as to why they need your services.
Now imagine pitching web site creation services, providing real world examples on how businesses have improved their bottom live with their web site.
Now they’re listening.
When selling services that include web analytics, try starting with the end result and then work your way backwards. If you start with the prize, people will usually pay more attention.
Here’s an example:
The problem is that many web analytics businesses start their pitch with step 10 and then work their way to step 1.
When people ask me what I do for a living, the answers have changed over the years, but now I usually answer along the lines of:
I help web sites do better at whatever they’re try to do.
Specifically, I learn the business objectives and then do some detective work, finding issues that can be improved and then I improve them.
As always, comments and suggestions are appreciated.
I’d like to share an “a-ha” moment I recently had while viewing an online video.
As part of my job as a web analyst, I often do site audits.
This entails analyzing the web analytics data (usually Google Analytics, Omniture or WebTrends) in conjunction with viewing the site itself.
While the numbers tell the story of what happened, I try to figure out why it happened by also examining the site and it’s contents.
For example, a site might be tracking video views with data on how many people started viewing each video, how many people viewed at least half of the video and how many people saw the entire video.
In a scenario where there is a large drop-off from people starting to view the video to people viewing half of it, there are several factors which could account for the drop-off.
It could be content related (the video doesn’t hold the viewer’s interest) or it could be technical (the video was stuttering or took to long to start playing) people should know that in order to catch everyone’s attention the video needs to be made by video production companies phoenix or a similar company.
I’ll usually check the minimum bandwidth required to play the video smoothly to see if I think it’s a load time issue, but that’s just circumstantial evidence.
Today, while viewing a video that was constantly buffering (and annoying to watch) I left the page and then realized:
Buffering events should be tracked as a metrics
The following numbers should be tracked
This information will help you get from what happened to the why it happened, conclusively telling you if the viewing was abandoned due to load times or something else!
A few months ago Google Analytics released an awesome new feature – Custom Variables.
If you’re new to custom variables, you should read the official Google help page:
And check out the webinar they did recently:
While custom variables are great – you only get 5 of them, or so Google says. There is an undocumented feature that basically gives you as many custom variables as you want. It’s as simple as setting the number of maximum custom variables as you want to use. Here is the Google Analytics function to use:
[important update July 2, 2010]
Omar brought to my attention that when drilling down via the standard GA interface, when you pick a custom variable after the 5th one (in order that is was set, not in the order on the interface) you get an error saying:
Recently I’ve been using the Google Analytics API to automate some of the report generation I’m doing.
After some serious hair pulling I finally realized that there is a bug in the API when one of the metrics you request is adCost.
Specifically, when requesting adCost with other specific metrics, the results for adCost are always zero.
After some research I found this post which confirms that Google is aware of the adCost issue.
Unfortunately the post doesn’t really help much in terms of finding out which combinations trigger the bug, so I tried out some of the combinations myself found that using any traffic source dimension with these metrics will trigger the bug:
If you are aware of other metrics that trigger this bug, please let me know and I’ll add them to the list.
I should add that this bug also affects custom reports!
If you’re using any traffic source dimension and adCost together with any of the above metrics in a custom report you’ll get zero for the adCost data.
Hopefully this saves someone else from some major hair pulling.
I started using web analytics software back in 1996, before it was even called web analytics. At the time we were measuring mostly “hits” and page views.
Basically, every web page was a more or less a static page with no on-page interaction.
Now, almost 15 years later, the web is a different place. The “lets measure page views” model for tracking and measuring online activity crumbled a long time ago.
A few years ago Google Analytics added event tracking in order to address the shortcoming of trying to measure everything as a page view.
While this is better than nothing, the problem is that it’s too generic to label everything other than a page view as an event.
Every type of user interaction has it’s own characteristics, and should be measured accordingly.
For example: Forms.
Forms are an entire world in terms of tracking user interaction: Was the form submission successful? What fields were filled out? How long did the user spend on each field? etc.
http://www.ClickTale.com actually does a great job of measuring all of this, but my point is:
We need a new standard dictionary for what elements we can measure and what attributes each element has.
eCommerce transactions are already standard in all web analytics solutions. Most of the higher end analytics solutions are already addressing the overall issue by adding dedicated event types for video views, downloads, or outbound links.
I’d like to see dedicated events for things like clicks, scrolls, even a “still on the page” event (this is for more accurate time on page measurement)
There will always be always be room for a generic type of event, but in order to reach the next generation of web analytics adoption, we (the industry) really need to expand our horizons beyond page views and events.
A couple of weeks ago user experience guru Jacob Neilson wrote an article about user attention above and below the fold.
In a nutshell he says:
… users will scroll below the fold only if the information above it makes them believe the rest of the page will be valuable.
I totally agree.
On the other hand, a few people have pointed out to me a recent article by CX partners in the UK that states the fold isn’t very important anymore. They say:
We see that people are more than comfortable scrolling long, long pages to find what they are looking for. A quick snoop around the web will show you successful brands that are not worrying about the fold either.
I was thinking about the two articles which seem to be contradictory. After digesting all of the data, I have to say that both parties are right – they are just missing a crucial piece of information – the context in which the visitor is viewing the page.
If I’m on Amazon.com viewing a list of products, of course I’ll scroll because I know the information I want is below the fold.
If I just clicked on an ad and have landed on a site or page that I have never viewed before, my first internal question is “am I in the right place” and only after my internal dialog says yes, will I think “do I need to scroll to find what I am looking for”.
In the second scenario, it’s crucial to have above the fold all of the information the visitor needs in order to know they are in the right place.
So, in summary, if we combine the two opinions and add the missing ingredient – context, we get this (my version):
People are more than comfortable scrolling long pages only if the information above the fold, or their existing knowledge, makes them believe the rest of the page has what they are looking for or will be valuable.
On a side note, the CX partners article does indeed address the issue of bad design leading to a user not scrolling due to them not realizing there is more information below the fold, but that’s a different scenario.