Unmask (Not Provided) Goal Completions in Google Analytics As of late, the SEO blogosphere has been rich with posts from authors seeking to diagnose seeming declines in branded organic traffic. The common culprit (or deceiver, if you will) is Google’s grand obfuscation – (not provided). In the technology industry, the presence of (not provided) in keyword reports has proliferated drastically. In September, LunaMetrics saw nearly 65% of our organic search keyword data veiled in uncertainty. That’s right; more data is hidden than is available. Are you comfortable extrapolating from 35% of organic search visits? Comfort is a commodity, after all – a commodity granted to those who haven’t seen such a stark increase in (not provided). Reporting on (Not Provided) In looking at overall goal conversions from organic search traffic, we might be tempted to postulate that the conversion keywords that show up in our reports are distributed similarly across the (not provided) segment. As SEOs and analysts, we love granularity. 1. 2. 3.
Custom Reporting Using Google Analytics and Google Docs The author's posts are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz. Realtime Google Analytics data inside a Google Doc—a panacea! Don't believe me? Google Analytics is my favorite analytics product. But, despite all the flexibility that Google Analytics offers, sometimes you want to access data in a spreadsheet and create a truly custom report. This blog post is going to show you how to create a custom report by connecting a Google Spreadsheet directly with your data from Google Analytics. Analytics geeks: hold onto your seats! It all started with the Data Feed Query Explorer (Those who want to start accessing data in Google Docs should jump right to the next section.) Before we dive in, a little background. I first discovered Google's excellent Data Feed Query Explorer. The Data Feed Query Explorer is a great way to explore the Google Analytics API, and to understand what data is available. Now you're all set!
Split Testing With Google Analytics Experiments In today's tutorial, we're going to be looking at one of Google Analytics' most recent additions to its feature set; Experiments. Using this tool, I'll be showing you how to serve up different variations of a page to determine which one is the most successful in converting visitors to the site. Preamble If you've ever created a website, you'll almost certainly be familiar with Google Analytics. From small personal projects to enterprise level sites, Google Analytics has established itself as the market leader for very good reasons; it's free, simple to implement and is suitable for the casual user or even the most battle-hardened marketer. Ready to get started? A Brief Introduction to Split Testing We've covered split testing before as part of Ian's thorough roundup on conversion and online marketing, but let's take a brief look at split testing in the online arena. Variations must be run all at the same time. The Scenario Here's an image of the third page variation: Step 3: Create a Goal
URL Builder - Analytics Help Generate custom campaign parameters for your advertising URLs. You can add parameters (such as utm_source, utm_medium, and utm_campaign) to a URL to capture reporting data about the referring campaign. For example, the following link would allow you to identify the traffic to example.com that came from a particular email newsletter, as part of a particular campaign: You can create your URLs by hand or you can use a URL generator. the Google Analytics Campaign URL Builder for generating URLs to websites the Google Play URL Builder for generating URLs to apps on the Google Play Store the iOS Campaign Tracking URL Builder for generating URLs to apps on the Apple App Store A/B Testing with Google Analytics Content Experiments Google Analytics has announced a new A/B testing feature called Content Experiments. This is a pretty significant evolutionary step for Google Analytics in making it an analytics and optimization tool. Think of this as Google Website Optimizer being baked right into the Google Analytics interface. Using Content Experiments in lieu of GWO will allow you to easily define content URLs and goals for your experiments, analyze your reports more efficiently and will eliminate the need for all those extra GWO tracking codes on your site. I want to review the basics of A/B testing and running GA Content Experiments, as well as discuss some important technical details and advanced considerations. What is A/B Testing? A/B testing takes a lot of forms. A/B testing is very easy (and free) with Google Website Optimizer. How to Setup a Content Experiment Prepare. After you’ve completed an experiment, start the process again with another page and keep trying to make incremental improvements to your site!
Local Video Marketing - Get Emotionally Involved with Your Online Video Marketing Upgrades To Google Analytics Content Experiments A few weeks ago Google Analytics launched Content Experiments, a new testing functionality that can be used to create A/B/N tests to optimize campaigns and overal website experience. Last week Google announced 3 upgrades that will make testing with the tool significantly easier and more powerful. Below I discuss each of the upgrades and how they can enhance testing with Google Analytics 1. Ability To Copy Experiments This new functionality is valuable as it allows marketers to perform additional tests to the same page without modifying the codes, which makes the process much shorter. On the settings page, on the bottom-right corner you will find the “Copy experiment” button, as seen below: After clicking the button, you will get the following message: “Copying an experiment will copy the current settings into a new experiment—where you can adjust as you desire. 2. Relative URLs offer more flexibility in defining the location of the variations. 3. Closing Thoughts
Location extensions, a new way to run local ads Today, we'd like to tell you about a new way to run your local ads – location extensions. Location extensions allow you to "extend" your AdWords campaigns by dynamically attaching your business address to your ads. This new feature will be fully available in the coming weeks, with some advertisers having access to the feature starting today. If you're a business owner, you can set up extensions by linking an AdWords campaign to your Local Business Center (LBC) account. If you're not the primary business owner of the locations you're advertising, you can manually enter addresses directly into AdWords. Once extensions are set up, we'll dynamically match your business locations to a user's location or search terms and show the address with your text ads. With the introduction of location extensions, local business ads will no longer be a separate ad format.
Google Analytics Content Experiments - A Guide To Website Testing | Testing & Usability [Last Updated on November 2013] In this article I discuss Content Experiments, a tool that can be used to create A/B tests from inside Google Analytics. This tool has several advantages over the old Google Website Optimizer, especially if you are just starting the website testing journey. Content Experiments provide a quick way to test your main pages (landing pages, homepage, category pages) and it requires very few code implementations. Here is a quick overview of the most prominent features that will help marketers get up and running with testing: Below is a step-by-step guide on how to use Content Experiments to create A/B tests. Creating Content Experiments In order to create a new experiment, navigate to the Behavior section and click on the Experiments link on the sidebar. Once you define all the information above, click on it you will reach the following page. In this page you can add all the URLs of your original page and the variations you would like to test. Click Next. Yay!