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I just thought I would fire off a quick post and share my experiences with "Advanced Segments" functionality in Google Analytics.
Imagine this scenario, you are granted "read" access to a client's GA account. Yes, "Read" access will allow you to view all reports. Missing within "read" access (amongst a several other capabilities) is the ability to filter data - in this case, traffic associated with your physical location as well as your client's location. You're stuck, and must ask the admin of this account to grant you "admin" access, ehh?
Enter "Advanced Segments". Using this functionality it is extremely simple to segment (or in this case, parse) out unneeded metrics.
At the left, you will notice "dimensions" and "metrics". If you are not familiar with the two data types, "dimensions" are the types of data you are looking to analyze while "metrics" are the values you would find within these dimensions.
 For this example, assuming you are met with the same situation I have mentioned above, log into your account and click "advanced segments" within the navigation on the left.
First, choose a dimension or metric to segement. For this example, choose Visitors > City. Drag the green "City graphic" into the dotted line area that says "dimension or metric".
Next, choose a condition. Since we are looking to segment out test data derived from a particular location or locations, our condition needs to be set to "Does not match exactly". The "Value" drop down will then be equal to whichever City you do not wish to record within your reports.
Repeat this with as many cities that you are wishing to remove from your reports. Just make you you follow the above-mentioned instructions and do not drop your metric/dimension within the "or" but rather the "and" location on the list.
Lastly, choose a name for this custom segment and click "Save Segment". That's it!
Back on the main page of your GA profile, you simply need to enable the segment. Click on the "Advanced Segments" button in the upper right of your screen. Next select the segment's name. Lastly, click "Apply."
Pretty simple, huh?Labels: Advanced Segmentation, Google Analytics, metrics, web analytics
"What's the difference between hits and visits?" I took a deep breath before attempting to explain the answer to this million dollar question to a group of board members during a client pitch this past week.
Explaining web metrics in a clear and concise way is nothing new to me. Especially since many clients do not take the time to consider analyzing their own data and instead focus on throwing money away on endless paid-per-click search campaigns without any sort of knowledge. I learned early on in my career, if you could explain things in an easy method, breaking down information into bite-sized chunks, chances are much greater that you could close a sale. Any salesperson will tell you that a client buys into you more than the product or service you are selling. Therefore I always made it my number one goal to educate my clientele instead of trying to pull the wool over their eyes.
Pre-dot com bust everyone focused on getting their business online and paid no attention to any web reporting (despite the fact that reporting was also in it's infancy.) Fast forward to today and I question if really anything has changed.
Clients often times clamor to get online without first considering web metrics, and in turn their own audience at all. Fortune 500 clients still do not employ web metrics into their routine. Those that do, are often times paying hand over fist to simply know the amount of hits they receive from a website. The problem that any analyst will tell you is that the number of web hits mean extremely little when it comes to metrics.
I will go one step further and suggest that a number of visits to a given website can mean very little as well. In the case of individuals within a niche marketplace it is acceptable to believe that the desired demographic is going to be more finite than a website that can pander to an extremely wide-ranging audience. Therefore it's important to pay more attention to time spent on the site, page views and bounce rates.
For example, I would much rather 100 people spending 6 minutes or more on my website, thumbing through every page vs 1,000 people spending 10 seconds and going through 1 page (or even leaving directly from the homepage.)
So back to my introductory statement and the answer I gave the group of board members for a luxury retail client... "There is a huge difference between hits and visits, but neither of which should be of a primary concern to you..."Labels: metrics, web analytics
In the old days of the internet (approximately 2 years for you traditional marketing folks), data was measured in terms of one or two primary metrics. If you said "hits" please exit my site immediately. Thank you, now that I have your attention, let's continue...
Primary success metrics of a given online campaign were routinely measured by leveraging total visits with the average number of pageviews per visit. This was a gold mine. I could create seemingly limitless reports based on this most elementary data. Of course that was in the days of synchronously loading page data - before scripting methodologies such as AJAX had to complicate matters.
Fast forward to today, page views are still a main stay within analytics programs such as Google Analytics however I question whether or not they should be. This belief can still be summed up within a few short accronyms and one syllable words: AJAX, PDFs, and Flash.
This method of scripting, a document type and multimedia application have been causing havoc for web analysts for some time now. And Adobe, you still have not convinced me that Flash is completely queriable. Especially given the fact that so many people still use Flash within a timeline. That is instead of it's one frame object-oriented routines with simple "getURL" linking structures found within this said frame. (And this is just one example of Flash 'issues' with regards to analytics, I have several more). Like text that is broken apart or part of a graphic instead of dynamic text instances.
The point is creating 'fake' pages that only have the responsibility of being logged within analytics programs (to aid with AJAX and PDFs) is a tedious process.
So... What metrics do I particularly like to use when providing reports to clients? Every vertical marketplace is going to be different however if I had to pick two to replace the above two metrics in terms of equal importance it would most likely be "Bounce Rate" and "Average Time Spent on Site".
AJAX can have many calls to varying pages occurring within the same HTML based document. PDFs can have text that has been converted as an outline (and is essentially speaking, merely a graphic). Neither of my above-mentioned two metrics are clouded by AJAX, PDFs, and Flash.
With "Bounce Rate" I can see definitively that someone came to a given site and left immediately thereafter. If this rate is unusually high I can then monitor that cluster of users against a series of other metrics (visitor loyalty, and traffic sources) more effectively than I could have done with a "pageviews" metric on a site predominantly coded using a series of AJAX calls.
With "Average Time Spent on Site" I can still see that a given user spent (X) amount of time on a given site. Since I can correlate this data across a series of given days, I can analyze why time on site may have been so very much higher on Monday, June 23, 2008.
At the end of the day, the one quote I will always repeat is 'the only thing constant is change.' Within the area of internet technology this could not be more true as I have seen entire methodologies completely change online within 12-18 months.
That being said, as the fundamentals of a more engaging Web 2.0 are starting to be realized it becomes more important than ever that web analysts provide clean and accurate data to web strategists so that they can react with a proper course of action for a given web campaign.Labels: metrics, web analytics, web marketing
I measure the success of any web initiative though clear use of metrics. I love analyzing "the numbers" because it gives me further incite into user data that as a marketer I may not have otherwise understood yet alone considered.
In my travels I came across a post by Rachel Happe. In this post she highlights methodologies for measuring social media success.
What I like the most about her proposed series of metrics is that for different individuals there are different types of metrics that should be analyzed. Great post Rachel!Labels: measuring success, metrics, ROI, social media, web marketing
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