Webinar Video & Recap: Measuring Success in a Multi-Device World

Last Thursday, we held a webinar discussing how to effectively measure the customer’s journey in a multi-device world. We focused on high-level best practices and strategies, as well as how Google Analytics and other Google tools can help you measure and respond to the evolving customer journey.

Watch the webinar video here to learn more about:

• Holistic, full-credit, and active measurement
• Everyday strategies to improve your measurement and marketing performance
• Basic techniques for marketing attribution
• Google Analytics features and tools for measuring the full customer journey

During the webinar, we received dozens of great questions from viewers. Read on below for responses to some of the most common questions we received.

Questions and Answers

What other blogs would you recommend for advice on measurement best practices?

Avinash Kaushik is the author of Web Analytics 2.0 and Web Analytics: An hour a day. On his blog, he discusses how to use digital marketing and measurement to focus on the customer while maintaining your ROI.

Justin Cutroni is the author of Google Analytics, Performancing Remarketing with Google Analytics, and Google Analytics Shortcut. He uses his experience as a consultant to guide his blog topics. His blog provides readers with techniques for using Google Analytics to maximize their marketing strategies.

Where can I find the “Think Insights” website referenced during the webinar?

Visit www.google.com/think for access to all sorts of statistics and articles about the latest trends in customer behavior. To learn more about the customer journey to online purchase, view the interactive benchmarking tool here.

How does marketing attribution help with intra-channel optimization?

Marketing attribution can help you to optimize intra-channel campaigns by allowing you to see value for each of the specific moments in the customer journey that you may be addressing within that single channel. For example, if you are running a search campaign, you may think about the role that different types of keywords play at different moments to help generate awareness for your brand, move the customer to consider your product, or to help close the deal. Using tools such as AdWords Search Funnels, you can determine where in the customer path those keywords had an impact, and this can help you optimize your keyword mix.

What are first-click and last-click attribution models?

The first and last clicks are important parts of two  commonly used attribution models, the “first interaction” attribution model and the “last interaction” attribution model. Depending on which model you use, all credit for the sale (or conversion) is attributed to either the first or last click. In the “first interaction” model, the first touch point would receive 100% of the credit for the sale. In the “last interaction” model, the last touch point receives 100% of the credit. Historically, many businesses have relied on the last-click model alone, but since this model (like the first-click model) only addresses a single touch-point along the customer journey, it may miss other important marketing interactions.

There is no one specific model that will work for every business or every program within your business. Rather, you should explore different models and experiment to see which model or combination of models best fits your needs. Check out Google Analytics Multi-Channel Funnels and Attribution Modeling to get started.

What are some tips for measuring the customer journey with Universal Analytics?

Consider integrating Universal Analytics with all of your digital touchpoints (see some examples in this post). Here are a few use cases that our Certified Partners are already implementing to measure the customer journey beyond web:

• Integrated measurement and analysis of in-store POS systems along with desktop and mobile e-commerce platforms.
• Measuring offline macro and micro conversions through physical buttons or integration with CRMs.
• Measuring physical interactions -- for example at display booths at conventions or artworks at major exhibitions -- through to online engagement with associated websites.

Posted by Sara Jablon Moked & Adam Singer, Google Analytics Team

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Google Analytics Becomes A Robust Testing Platform With Content Experiments API

Our Analytics API enables marketers and developers to experiment and build new tools powered by Google Analytics. Over the past year, we’ve listened to your feedback and made improvements to the API such as expanding data points available and integrating with Apps Script. Our goal is to provide the most flexible and useful Analytics API on the web enabling you to do everything from build great apps to automate / expedite busywork. 

Today, we’re excited to share the launch of an API for Content Experiments — our tool for easily testing site content with programmatic optimization to achieve Analytics objectives. This API makes Google Analytics a full-blown A/B testing platform where developers of all types can leverage the power of Google Analytics to run their experiments. By utilizing our multi-armed bandit approach, you can maximize results by efficiently determining which assets on your site perform best to offer an improved experience for users. Multi-armed bandit experiments are powerful and efficient tools and with the new Content Experiments API, you can get even more from them.

The Content Experiments API allows you to pick and choose from all the testing functionality Google Analytics has to offer and to combine it into powerful solutions that best fit your particular needs:

Testing changes to content without redirects. 

The original Content Experiments JavaScript snippet made testing a breeze. To keep things simple and consistent for all publishers, the snippet causes a page redirect which may take away from the end user experience in certain cases. Now, with the new Content Experiments API, testing changes to content without redirects is both possible and easy to implement.

Testing items server-side such as the result set of a database query.

Major testing platforms typically offer changes on the client-side but not server side. With Content Experiments API you can now run tests on the server side and try things like implementing different recommendation or search algorithms to determine what works best for your site.

Testing with your own variation selection logic and use Google Analytics for reporting.

While the multi-armed bandit approach to experimentation is one of Content Experiments most powerful features, there are times where publishers and developers would prefer to decide for themselves how to serve variations - be it evenly or using proprietary logic. The Content Experiments API makes it possible for you to bypass our programmatic optimization while allowing you to continue to enjoy the powerful experiment reporting Google Analytics provides.  

Testing in non-web environments using measurement protocol.

For example, if you have a kiosk in your physical location (such as airline terminal or retail store) you can test different layout variations of content and features and determine what users can complete quickest or at highest value.

Developers are already putting the Content Experiments API to work and we’ve been hearing great feedback. Paras Chopra, Founder & CEO of  Visual Website Optimizer reports:

"We're thrilled about the possibilities opening up with the new Content Experiments API. This new API is specially designed to infuse the powers of Google Analytics into testing and experimentation domain. We're very proud to be one of the beta-testers with Google and soon we will start rolling out the integration of Visual Website Optimizer with Google Content Experiments across our joint customer base. When Google releases an API, it's a big move for the A/B testing industry and we're excited to be their launch partners."

Learn how to get started with our Content Experiments API on our developer site or if you’re still new to the platform, get an overview of Content Experiments in our help center.

Happy testing & experimentation! 

Posted by Russell Ketchum, Google Analytics Team

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Improving Google Analytics Dashboard Sharing

We’re happy to announce you can soon share and collaborate on Google Analytics dashboards!

Dashboards give an overview on how your properties are performing, and are even more powerful as you can create dashboards that you and your teammates can see and edit. Dashboard sharing is a nice complement to dashboard template creation: templates enable creating copies of dashboard configurations, and dashboard sharing enables you to collaborate with your team on a single shared dashboard.

You’ll be able to use this new feature as we roll this out in the coming weeks. At that time, start by creating a dashboard or viewing an existing one and then clicking on the “Share” menu. Look for the new “Share Dashboard” option:

This will make a copy of your dashboard that is available to everyone on the profile.  Private dashboards will be grouped together, and shared dashboards will be as can be seen in the report navigation on the left side of Google Analytics: 

Learn more about dashboard sharing.

Asset Sharing

This marks another enhancement in Google Analytics asset sharing, complementing the sharing capabilities of assets like annotations, advanced segments and custom reports. Google Analytics offers two forms of asset sharing today: creating asset templates, and collaborating on a single asset like we’re launching soon with dashboards. We are listening closely to user feedback on sharing, and planning more sharing features that you will see in the future.

Use dashboard sharing today to work more effectively with your team, and to enable richer reporting and data analysis.

Posted by Shailen Pandya and Matt Matyas, Google Analytics Team

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