Google Data » Parkie

Back to Basics: What’s in a profile setting?

Parkie — Mon, 28 Sep 2009 23:33:00 +0000

A little known link in your Analytics account is the key to unlocking extra ecommerce functionality in your Google Analytics account. In this post, we'll show you how clicking the 'Edit' link in your Main Website Profile Information box can open doors for your AdWords and ecommerce tracking purposes.

Once you click 'Edit' (highlighted in red above), you'll see a screen with editable fields like the image pictured below. The numbered list corresponds to the number next to each field so that you can learn how to set up a profile and enable the right features for your tracking purposes.

Enter an easily identifiable profile name.
Fill in the web property URL that you are tracking for this profile.
Enter the default page to which your server defaults to when no page on the domain is specified. This information allows Google Analytics to combine requests to www.yourdomain.com and www.yourdomain.com/index.html, which are in fact the same page. If Default page isn't specified, these would be reported as two separate pages.
If your account is linked to an AdWords account, your time zone country and time zone will default to the ones specified in your AdWords account. If your accounts are not linked, you'll see pull-down menus that display options for you to select for #4 and #5.
Same as #4.
If your site uses unique session IDs or other query parameters in your URLs that you are not interested in seeing in your reports, you can easily exclude these parameters by entering them into this field.
Enter the currency you want to see in your reports.
If you have linked an AdWords account, import your cost data so that you can get AdWords information pumped into your Google Analytics account. Once your cost data is imported, the information will appear in the Clicks tab of your AdWords report. Learn how to import your cost data.
If you're tracking e-commerce on your website, you must enable it to be reflected in your reports in this section. If you would like to set up e-commerce for your site, please read this Help Center article.
If you have a search engine on your site, you may want to enable this feature. Site Search contains reports about the visitors using the 'search' functionality on your website. Google Analytics Site Search reports deliver many useful pieces of information - for example, they can help you analyze how people use the search functionality on your site, and report its conversion metrics. Learn how to enable Site Search.

Posted by Christina Park, Google Analytics Team

Back to Basics: Tip for exporting rows

Parkie — Mon, 24 Aug 2009 21:56:00 +0000

As more and more people use Google Analytics to run reports for their advertising campaigns, we've had to come up with faster and easier ways for people to use Analytics for their everyday needs. One request that comes up quite often is to do away with 500 row export limitation for reports. Understandably, it's annoying to repeat your steps when you're exporting a report that has more than 500 rows.

We've found a helpful workaround that lets you export any number of rows in one go. We've listed the steps below so that you can bookmark this page whenever you need to export all the data listed in your reports.

Instructions

In our example Keyword report, you can see that there are over 3,000 keywords to export. This would mean that we'd have to hit 'Export' over six times!

To avoid the manual labor of exporting and then consolidating all your CSV reports into one, follow the steps below:

1. Go the report that contains the data you want to export.

2. Append "&limit=5000" (or however rows you need) to the URL displayed in your browser URL window, and hit enter to reload the report.

For example:

Before: https://www.google.com/analytics/reporting/keywords....2311
After : https://www.google.com/analytics/reporting/keywords?.................2311&limit=5000

3. After you've clicked 'Enter,' visually confirm that the URL displayed in your browser has the "limit" parameter appended to it. While there won't be any visible difference in the user interface, exporting will now yield more rows.

4. Select the Export tab, and click 'CSV' (not the option that says 'CSV for Excel').

5. The exported data should contain all the rows from your Analytics table.

We hope this added some precious time back to your Monday!

Posted by Christina Park, The Google Analytics Team

Back to Basics: Troubleshooting goals

Parkie — Mon, 17 Aug 2009 20:41:00 +0000

One of the easiest ways to make sense of your data and measure business objectives for your website (and even assign a monetary value to them) is to create goals. However, once you've correctly implemented your tracking code and identified the pages you want to create goals for, you may run into some common goal set-up problems. Below are some tips to help you solve some common issues first-time Analytics users run into so that you can get going on the road to taking useful action with your Analytics goals.

Incorrect goal URL

One of the most common goal set-up errors is to enter the incorrect URL. To confirm that you're entering the URL correctly, try reaching the goal page on your own site and copying and pasting the URL into the 'Goal URL' field.

You can remove the domain name entirely from the field and Google Analytics will still track the page as a goal. For example, if your goal is http://www.mysite.com/1/thanks.html, you can safely use '/1/thanks.html' as your Goal URL.

Duplicate final goal step

When you have steps leading up to your goal, the last step you specify in the Goal Funnel Settings should be the final step prior to reaching your goal. The goal itself should be placed in the 'Goal URL' field and does not need to also be included as a last step.

Goal value error

It is possible that the Goal value entered includes non-numerical characters. If the goal value is set to $2,560, the error message is displayed because the value contains the characters "$" and ",". In this case, only the value 2560 will suffice.

Historical data not relevant

If you've recently applied a new goal, it will only apply to data processed after the goal was implemented, and not to historical data in your account. This is why you might not see data for your website if you haven't had anyone convert on a goal after you created one.

To read the full list of reasons why your goal creation failed, read this Google Analytics Help Article. For an in-depth explanation about goals and how to set them up, please read this previous post.

Posted by Christina Park, Google Analytics Team

Back to Basics: Direct, referral or organic – definitions straight from the source

Parkie — Mon, 10 Aug 2009 23:23:00 +0000

In your Analytics reports, you'll see some of the same entries come up again and again in your data tables. In the last Back to Basics post, we learned about 'not set' entries -- this week we'll learn what it means when you see 'direct,' 'referral' and 'organic' under the Sources column in your reports.

(direct)[(none)] - Visitors who visited the site by typing the URL directly into their browser. 'Direct' can also refer to the visitors who clicked on the links from their bookmarks/favorites, untagged links within emails, or links from documents that don't include tracking variables (such as PDFs or Word documents).
[referral] - Visitors referred by links on other websites. (Links that have been tagged with campaign variables won't show up as [referral] unless they happen to have been tagged with utm_medium=referral. )
[organic] - Visitors referred by an unpaid search engine listing, e.g. a Google.com search.

Once you learn where the traffic to your site is coming from, you can start analyzing the information to make intelligent decisions for your website. For example, the Referring Sites report shows you which websites have been most effective at driving people to your site -- and which ones haven't been effective. Furthermore, if you have defined as goals the key pages you want visitors to see, you can see the percentage of visits from each referral during which the visitor saw these pages. (Just click Goals tab to see your conversion rates for each goal.)

To learn more about how to spot quality traffic from your Goals tab, please refer to this earlier Back to Basics post.

Posted by Christina Park, Google Analytics Team

Back to Basics: Free Google Analytics Tools

Parkie — Tue, 30 Jun 2009 00:02:00 +0000

We've picked two free tools that anyone can use while setting up Google Analytics for your site. The tools below are pretty basic but are applicable to anyone tracking a campaign with an Analytics account.

URL Builder

The first tool we want to introduce our beginners to is the URL Builder. In order for Google Analytics to track your marketing campaigns effectively, you'll need to tag your online ads with the right information (e.g. campaign, medium and source) so that Google Analytics can track your marketing campaign and show you which activities are paying off. To help the the tagging process goes smoothly, you can use the URL Builder from our Google Analytics Help Center.

Tagging your campaign links will consist of a URL address followed by a question mark and your campaign variables. But, you won't need to worry about link syntax if you fill out the URL Builder form and press the Generate URL button. A tagged link will be generated for you and you'll be able to copy and paste it to your ad.

SiteScan

The Google Analytics SiteScan tool, created by EpikOne, a Google Analytics Authorized Consultant, is a very handy tool to verify that all pages on your site include the tracking code.

SiteScan picks up on some classic signs indicating that your site has improperly implemented tracking code like:

1. No data in your account. (The tracking code was either never implemented or has the wrong account number)

2. You're seeing a high bounce rate even though your site isn't a blog and has more than one page. (If you've only tagged your homepage, your Google Analytics account will be unable to identify any other pageviews from your site. )

SiteScan then reports each page in an easy-to-read CSV file after you've installed the tool. This makes it easy for you to isolate the pages with tracking problems, fix them, and effectively manage your Google Analytics Tracking Code installation.

We're constantly working on developing tools to diagnose problems associated with your account or increase the usability of Google Analytics. We hope that you find the above two tools useful and leave us a comment about any other diagnostic tools you would like to tell us about on this blog!

Posted by Christina Park, Google Analytics Team

Back to Basics: Filtering out your own IP address

Parkie — Mon, 08 Jun 2009 22:55:00 +0000

If you have a team of people on your marketing team constantly checking the website you're tracking with Google Analytics, filtering out specific IP addresses is one of the ways you can make sure you're not tracking irrelevant visits to your site. Excluding these IPs may help you get more accurate numbers for metrics like average time on site (since your marketing team probably spends the most time on your site every day), your visitors' geographic locations, etc.

To start filtering out IPs, follow the steps below:

Collect IPs from anyone in your office (including yourself) that you don't want to track. If they don't know what their IP addresses are, an easy way to figure it out is to go to http://whatismyipaddress.com/.
Then, sign in to your Analytics account at http://www.google.com/analytics.
If you have more than one account, select the account that has the profile you want to apply the IP exclusion filter to.
Once you're on the Profile Overview page, click 'Edit' from underneath the Actions column.
From under the 'Filters Applied to Profile' section, select 'Add Filter.'
Select 'Add new Filter for Profile.'
Enter an easily identifiable Filter name (i.e. 'My IP address,' or 'CMO's IP address).
Select the filter type labeled 'Exclude all traffic from an IP address.' The IP address field will auto-populate with an example IP address. Enter the correct value. Remember to use regular expressions when entering any IP address. For example, if the IP address to filter is:

176.168.1.1
then the IP address value will be:
176\.168\.1\.1
You may also enter a range of IP addresses. For example:
Range: 176.168.1.1-25 and 10.0.0.1-14
IP address value : ^176\.168\.1\.([1-9]|1[0-9]|2[0-5])$|^10\.0\.0\.([1-9]|1[0-4])$
Click ‘Save changes’ to finish.

Posted by Christina Park, Google Analytics Team

Back to Basics: Graph mode

Parkie — Mon, 18 May 2009 23:04:00 +0000

One way Google Analytics can help you quickly spot trends and anomalies is through the 'Graph mode' feature. This feature lets you compare multiple metrics on your graph to see if there are any obvious correlations. You can graph by one metric, compare one metric to another (e.g. visitors versus average time on site), or compare a metric to your site average. Once you graph your selected metrics, you can roll your mouse over the graph to see the actual values of the two metrics you're comparing.

For example, let's say your site saw a sudden surge in traffic from an search engine optimization effort. You can use the 'Graph mode' option to graph 'visits' and '% new visitors' on the same graph. This will show you whether the SEO campaign successfully reached new visitors or whether it was more successful in driving repeat visits.

To use graph mode, click the pulldown menu in the top left of the graph of a selected report. Then, select the graph view you'd like to see. To finish, click the pulldown menu tab one more time.

Posted by Christina Park, Google Analytics Team

Back to Basics: Emailing reports

Parkie — Mon, 11 May 2009 21:34:00 +0000

Usually reports are mailed out to marketing managers or directors to measure any change in progress from week-to-week. With Google Analytics, you can make the process completely automated -- you can schedule your reports to be emailed daily, weekly, monthly, or quarterly. To start emailing your reports in PDF, CSV, XML, and TSV format, just click the 'Email' icon above all your reports:

This Help Center article has comprehensive instructions on how to schedule your reports or email them on the fly.

If after scheduling reports you want to delete them, you can do so at any time by going to the 'Manage Scheduled Emails' dashboard. This may be a little hard to find since you have to click a separate 'Email' icon in the reports page.

To delete a scheduled email, please follow these steps:

1. Find the other 'Email' icon on the left hand side of the reports page. Look at the image below to get an idea of where it's located.

2. After clicking the icon, you should see a list of scheduled reports. Click the icon that looks like a trash can in the upper right hand corner to delete them forever.

Hopefully after reading this post, you've automated sending out reports and have one less thing to worry about on Mondays!

Posted by Christina Park, Google Analytics Team

Back to Basics: An easy way to spot quality traffic

Parkie — Mon, 04 May 2009 23:08:00 +0000

Your site may be getting a lot of traffic from referring sites, but which websites refer visitors that actually convert to a goal? There’s a basic report that can show you where your quality traffic is coming from: the Traffic Sources report.

To spot which website links are referring visitors that convert to your goals, follow these steps:

1. On the main ‘View Reports’ screen, choose Traffic Sources in the lefthand navigation.

2. In the same area you'll now see a list of subset of reports. Click on 'Referring Sites.'

3. Now you'll see a report of all the top sites that refer traffic to you ("referral" = the user clicked a link on the sourcesite). Click on the Goal Conversion tab.

4. Now you'll see the top 10 referral domains. In the bottom gray section, choose a larger number for 'show rows' in order to see them all.

5. You'll get a breakdown of goal conversion percentages for every referral. Right above the data table, you'll see a score card listing your site average's data so that you can compare it to the information coming from specific sources.

Of course, for this report to actually show goal conversion data, you’ll need to have created goals for your website. You can either read a quick how-to from our Help Center, watch a video, or view a GA IQ learning module on it.

If you run an ecommerce site and would like some more information on identifying valuable referrers, you may want to check out this post written by one of our Authorized Consultants.

Posted by Christina Park, Google Analytics Team

Back to Basics: Using Motion Charts

Parkie — Mon, 27 Apr 2009 22:48:00 +0000

The Motion Charts feature seems like an advanced tool, but it's actually designed for Analytics users at all levels. It's useful for spotting trends and relationships amongst individual variables when your visits may look flat as an aggregated set of data. Today, we'll illustrate how Motion Charts can graph and compare several keywords over time.

For example, let's say you want to graph traffic over time for each of the top keywords in the report below. You can easily do so by going to the Keywords report under the 'Traffic Sources' section.

Of course, you can click each keyword to see a graph over time, but this doesn't allow you to make comparisons.

However, Motion Charts allow you to graph and compare individual keyword performance over time. To access Motion Charts click the "Visualize" button at the top of most reports, such as the "Keyword" report located under "Traffic Sources."

You can now see that, except for a dip in traffic between Mar 23 and Mar 30, "google store" sent more traffic every day than the other keywords. "google downloads" sent the least amount traffic each day.

But this graph also provides a bonus. If you set the size of the dots to represent revenue, you can identify the days during which traffic actually paid off in revenue. For example, "google store" doesn't generate revenue every day (even when it sends lots of traffic). "google shop" and "google software" frequently generate revenue, but not as much as "google store".

Generating this graph is easy. Just follow these steps:

Go the Keywords report (or any other report with table data) and click 'Visualize.'
Select "Time" for the X-axis and "Visits" on the Y-axis. For Size, select "Revenue" (or any other metric you want to track).
Now, select the keywords you want to graph (use the 'Select' box below the 'Size' menu) and select Trails. Press 'Play' or drag the slider across to the end of the time period.

After following these steps, a graph like the image above should appear. If you've selected a lot of keywords, your labels may bunch together, but you can drag and reposition the labels to see parts of the graph that are obscured.

Of course, you can use this technique on any report which has a 'Visualize' button. If you discover a new use for this technique, please post a comment and share your best practice with us.

Posted by Alden DeSoto and Christina Park, Google Analytics Team

Back to Basics: Pressing the right buttons

Parkie — Mon, 20 Apr 2009 16:52:00 +0000

One of the many ways Google Analytics keeps its reports dynamic with interesting data is to add buttons and other interactive features for you to analyze your reports with. Almost every report has over ten clickable features for you to jigger with, so this can get overwhelming for beginners -- especially if they've always seen their reports as flat pie charts or data tables.

Below are a few examples of how you can use these features and implement them as a part of your report analysis routine.

1. The 'Graph by' button

Beneath the date range selector for your graphs, there is a 'Graph by' feature that lets you graph your data by day, week, or month so you can analyze trends according to the selected view. Some Visits reports have an additional hourly view you can graph by if you really need that extra granular level of data. Get more details about each graph view here.

2. 'Views' button

The 'Views' buttons underneath the graph gives you the option to view your top content data by a variety of criteria - either by data table, pie chart, bar graph, or comparison view.

For the Top Content report, the 'Comparison' view is very useful to spot which pages outperform or underperform the site average. In the Comparison view shown above, we've sorted the pages based on the number of pageviews they each received and are comparing the bounce rate for each page to the site average. We can instantly see that the page that received the most page views also underperformed the site average in terms of bounce rate. But the second and third pages out performed the site average bounce rate.

Read some tips about keeping your visitors on your site and improving your site's conversion health.

3. Dimension segmenting pull-down menu

The 'Dimension' pull-down menu lets you segment one report within Google Analytics by one variable, giving you further context about your visitors. For the content detail reports, you can see how people came to a particular page by changing the dimension to 'Source,' or see what kind of traffic has been referring people by clicking 'Medium.'

If your site is seen in multiple languages, try selecting 'languages' for the dimension. Once you see an unusual spike in visits for a particular language or country, try modifying your site to serve your customers (i.e. translating certain pages or adding country-specific products) and see if your conversions grow, like this guy's. You never know if Mexicana music is enjoying a new revival in Venezuela!

4. Graph mode option

Visualize and compare two metrics at a time for a selected report by selecting from the 'Graph mode' pull-down menu in your reports. Comparing two metrics can show trends you may not have been able to spot solely from within your data table. Although there isn't much actionable insight this feature may give you, you can use it to raise some educated guesses about your traffic patterns and test them out.

To learn how to use the multi-line graphing feature, please read this article.

Hopefully this post has you starting out your week by pressing all the right buttons in your reports!

Posted by Christina Park, Google Analytics Team

Back to Basics: Quick tracking code fixes

Parkie — Mon, 16 Mar 2009 21:39:00 +0000

While browsing through some of the entries in the Google Analytics Help Forum, I found a useful thread on how to troubleshoot tracking code errors. Borrowing heavily from the conversations in the thread, I've summarrized the top ways to fix your tracking code here on the blog. Hopefully, after reading this post, you'll never have to return to work after the weekend to find that you have no data in your Analytics account!

· Make sure you have your Google Analytics Tracking Code installed on your site by checking your site's page source. I know, it seems obvious -- but it's actually one of the most common implementation errors our users encounter.

· Remember to enter the code somewhere between the and tags, preferably towards the tag.

· Get rid of unnecessary line breaks in your code. Copy the tracking code exactly as it's generated from within your 'Instructions for adding tracking' page. For example,

document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js'

type='text/javascript'%3E%3C/script%3E"));

should be:

document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));

· Having more than one Include filter in a profile may cancel out data collection for that profile. Try removing extra Include filters so that you've only assigned a maximum of one to your profile.

· Try adding the "{}" after the "catch(err)" in your code. Although modifying the tracking code with this new addition is optional, doing so adds the benefit of removing a JavaScript error message for visitors who unintentionally have JavaScript messaging enabled on their browsers. For those visitors who have enabled messaging, the try and catch will have the effect of halting any messages from the Google Analytics tracking code snippet.

An example of the try and catch block is below:

If you don't believe in the wisdom of crowds, hang out in our Google Analytics Help Forum and you may change your mind. Try asking a question on it or browse through other posts answered by our community of savvy Analytics users (we love you guys!).

Posted by Christina Park, Google Analytics Team

Back to Basics: New Getting Started Guide for Google Analytics

Parkie — Mon, 09 Mar 2009 22:54:00 +0000

Hot off the presses, the Google Analytics Help Center has published yet another informative online resource - the Getting Started Guide. The guide's purpose is to walk new users through the basics of having an Analytics account, and it also picks out must-know definitions like goals and funnels. It also has a diagram of the reporting interface so first time users can follow along and learn about the various reports and features. Finally, the guide also provides practical set-up and implementation instructions in the 'Installing Analytics' section, as well as tips on how to set up your reports and interpret the data once you start receiving it.

If the Getting Started Guide is too basic and you're ready to get started on more advanced code customizations or look through videos on tips and tricks, you can browse through the 'Other resources' section at the end of the guide.

We hope you find the guide useful - feel free to bookmark the Getting Started Guide for your own reference or share it with others!

Posted by Christina Park, Google Analytics Team