Weighted sort in Google Analytics

by Michael Whitaker on August 31, 2010

Weighted Sort has got to be one of my favorite new features in Google Analytics. There is a nice demo for using weighted sort with bounce rate, but I thought I’d suggest another metric on which to use this new ranking algorithm.

Let’s start by asking a simple question:

What are my most valuable pages?

As a proxy for “valuable”, we’ll use the $ Index metric in the Google Analytics Top Content report. $ Index measures the e-commerce revenue divided by the number of pageviews. The problem with sorting by $ Index is that you’ll see very large $ Index values because the pages only have one or very few pageviews.

In other words, the top page only had one measly pageview out of 3.5 million and it happened to have been during a visit that resulted in one sale. Not exactly optimization material, so let’s try and find pages that are doing a bit more work by using weighted sort. Just click and look at the results:

Don’t you just love it when the data you look at tells a great story? The first few results are all checkout pages, and this of course makes perfect sense as every visitor has to go through the checkout to place an order.

But now we can go down the list and look at other pages and get a sense of their true importance. Note the relationship between pageviews and $ Index: low pageviews and high $ Index being equivalent to high pageviews and low $ Index.

What weighted sort does beautifully is put data into context. You see, I don’t care about $ Index or Bounce Rate or e-commerce conversion rate per se, I am more interested in the impact on business and prioritizing my optimization efforts.

So a logical follow-up question to the first one might be:

Which page should I optimize?

The one with a bounce rate of 60% or the one with 50%? The answer of course is: it depends. If both landing pages have the same amount of traffic I’d pick  the one with 60%. However, if landing page A has a bounce rate of 60% and 1,000 views and landing page B has a bounce rate of 50% and 10,000 views, the impact of reducing the bounce rate of B will be higher even though its bounce rate is already better than landing page A.

I really appreciate the fact that weighted sort bubbles up this valuable data with a simple click, unlike some other approaches. And once you know your most valuables pages, guess which pages make great candidates for AB or Multivariate experiments?

The only downside of weighted sort is that you don’t know it exists unless you sort in the first place. A visual cue might be nice to indicate whether a column is weight-sortable, but I definitely know where to look for it and I hope you do too.

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There are a few reasons why clicks and visits from Adwords campaigns will likely never be same in your Google Analytics reports (or indeed any other web analytics tool), but you should of course make sure that you have a correct implementation as Adwords is a paid campaign…

But how can you tell if everything has been implemented correctly? If you have lots of Adwords campaigns driving traffic to lots of landing pages any errors might be hard to spot.

First of all, I would expect there to be fewer clicks than visits. If a visitor clicks multiple times on an Adwords ad during the same session you would see multiple clicks but only one visit in Google Analytics. Also, clicks are counted even before the visitor lands on your site, so if the tracking code does not execute in time on the landing page before the visitor navigates away you’d also lose visits.

In any case, even if there is a normal discrepancy you’d expect that discrepancy to be consistent. So if your normal percentage of visits to clicks is 90%, a percentage of 20% in one of your campaigns would not be normal.

You could of course look at the numbers directly in the reports table and look for unusually large differences between visits and clicks, but if you have lots of data to look at you might not spot any unusual patterns.

That’s why I like two visual approaches.

1) Using Compare Two Metrics

Pull up a new Adwords campaign report and click on the tab above the graph and select Compare Two Metrics. Choose Visits and Clicks. Data look OK to you and are clicks and visits in line?

You can then repeat this approach to drill down into Campaigns and Keywords. Unfortunately you’ll have to select those two metrics again every time you pull up a new report.

But fortunately, there is a sexier way…

2) Using Motion Charts

Pull up your Campaign or Keyword report and click on Visualize in the top half of the screen.

Motion charts allow you to see how several dimensions move over time in a graphical way. Visits should already be selected on the Y-axis. Select Clicks for the X-axis. Now you can see how visits and clicks behave over time. As I said earlier, you should expect clicks and visits to be correlated, but the motion chart should allow you to spot any outliers pretty easily.

As with all web analytics, you are looking back in time, but this is a pretty cool and powerful way to spot any errors.

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SEO Analytics in Google Analytics using Page Title

July 22, 2010

Seeing Page URLs and Page Titles in the same report is like the gift that keeps on giving. Not only can you easily track 404 error pages in Google Analytics without having to change the tracking code on your site, but it also makes it very easy to optimize your Title Tags. The Title Tag [...]

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Track 404 error pages in Google Analytics reports the simple way

July 20, 2010

Great tip by John at Lunametrics on how to show Page URL and Page Title side-by-side in a Google Analytics Contents report.
Here is a little background. Out of the box in Google Analytics, you can see Page URLs in the Top Content report and Page Titles in the Content by Title report:

but you can’t directly [...]

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Visits to Purchase revisited in Google Analytics

July 12, 2010

I still like the Visits to Purchase report in Google Analytics even though it may be sub-optimal.

At first glance you could be led to believe that 77% of transactions occur in a single visit. If  almost 80% of your transactions come from single visits then why bother with attribution management? There are many other things [...]

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Using web analytics to optimize checkout forms

June 25, 2010

Although I tend to be skeptical of best practices – they might be a starting point, but I prefer doing testing to find out what works or not – there are some things that are always better than others. A fast-loading site always beats a slow-loading one,  working links are always better than broken links, [...]

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I like to test with CSS

May 28, 2010

I can’t think of a more elegant way to do AB or Multivariate testing than with CSS (Cascading style sheets). The whole idea behind CSS is to separate presentation from content, where CSS handles the presentation (font, colors, layout) and content is all your HTML (text, links, product descriptions, images). If you are testing the [...]

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Yahoo! Store trackable links and web analytics

May 10, 2010

(This post applies only to Yahoo! Store merchants).
If you are using Trackable Links you can make a small change in the trackable link URL that allows you to track it directly in web analytics too.
When you set up a trackable link it looks something like:

http://store.yahoo.com/cgi-bin/clink?yhst-12345678910+VQASpg+index.html+testit
When you click on a link like this one (which is [...]

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Onsite personalization example with Google Analytics

April 28, 2010

I have had quite a few requests to confirm that you can read custom variables so I thought I’d just show a quick demo. I also recommend you take a look at the video from the Google Analytics team that describes this feature (fast forward to around minute 29:00).
As the name implies _getVisitorCustomVar() only reads [...]

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Unique visitors, 0 visits and pages in web analytics

April 23, 2010

It’s always good to pause and ask yourself if the data you are looking at makes sense. Particularly with the awesome powers of advanced segmentation in Yahoo! Web Analytics and Google Analytics you are likely to come across cases where the data looks weird when you set up custom reports. The likely explanation is that [...]

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