Domino’s Increases Monthly Revenue by 6% With Google Analytics Premium and Google Tag Manager

Tuesday, August 04, 2015 | 3:21 AM

Domino’s is one of the world’s leading pizza purveyors, having delivered 76 million pizzas only in the UK and Ireland in 2014. That’s a lot of pizza. In these markets, online sales increased 30% year over year and currently account for almost 70% of all sales; 44% of those online sales were made via mobile devices in 2014 (as opposed to only 31% in 2013).

With such a large online presence, Domino’s is always on the cutting edge of technology, enabling customers to order pizzas from virtually any device and platform. To drive success, the team knew they must break down silos, connect data sets, and gain efficient reporting to get a more holistic and actionable view of customer behavior.

Domino’s partnered with DBi, a Google Analytics Premium Authorized Reseller, in order to make the most out of their online data. They worked together to create a unified marketing measurement platform, using Google Analytics Premium, Google Tag Manager, and Google BigQuery to integrate digital data sources and CRM data in an effective and scalable way.



Domino’s deployed Google Tag Manager across apps and websites, setting customized tags for all of the company’s Ecommerce tracking and reporting needs. Despite there being a large number of unique containers, data layer consistency made it easy to duplicate tags and rules - a significant time-saver and error preventor for Domino’s. 

Domino’s used the BigQuery Export feature in Google Analytics Premium to automatically export raw data to a BigQuery project on a daily basis. They also uploaded daily CRM data into BigQuery through a secured FTP location and the BigQuery API. Following the process described above, CRM data became easily merged with Google Analytics behavioral data via transaction IDs.
“Google Analytics Premium, combined with Google Tag Manager and BigQuery, has become an integral solution that gives us the technical agility and the analytics power we need to advance our marketing strategies. DBi has been fundamental in developing our digital strategy with Google Analytics Premium.” —Nick Dutch, Head of Digital, Domino’s
Below are the main outcomes from the implementations and analyses discussed above.
  • Realized an immediate 6% increase in monthly revenue
  • Saved 80% YOY in ad serving and operations costs
  • Increased agility with streamlined tag management
  • Obtained easy access to powerful reporting and customized dashboards
Read the full case study to learn more about how DBi and Domino’s worked together to create a unified data reporting and analysis platform.

Posted by Daniel Waisberg, Analytics Advocate

L'Oréal Canada finds beauty in programmatic buying

Wednesday, July 29, 2015 | 1:45 PM

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Cross-posted on the DoubleClick Advertiser Blog


While global sales of L'Oréal Luxe makeup brand Shu Uemura were booming, reaching its target audience across North America proved challenging. By collaborating with Karl Lagerfeld (and his cat, Choupette) and using DoubleClick Bid Manager and Google Analytics Premium, the campaign delivered nearly double the anticipated revenue.
Goals
  • Re-introduce and raise awareness of the Shu Uemura cosmetics brand in North America
  • Drive North American sales of Karl Lagerfeld’s Shupette collection for Shu Uemura
  • Grow the Shu Uemura email subscriber list
  • Approach
  • Organized website audiences with Google Analytics Premium
  • Used programmatic buying to lead prospects down the path to purchase
  • Leveraged a range of audience data in DoubleClick Bid Manager to buy paid media in display and social channels
  • Results
  • Drove almost 2X the anticipated revenue
  • Exceeded CPA targets and achieved a 2,200% return on ad spend (ROAS)
  • Increased web traffic and email subscribers
  • To learn more about Shu Uemura’s approach, check out the full case study.

    How To Setup Enhanced Ecommerce Impressions Using Scroll Tracking

    Tuesday, June 30, 2015 | 10:45 AM

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    A version of this post originally appeared on Google Analytics Certified Partner InfoTrust's site.
    by Nate Denlinger, Web Developer at GACP InfoTrust, LLC

    One of our specialities here at InfoTrust is helping ecommerce businesses leverage their web analytics to make better data-driven marketing decisions. This typically starts with installing Google’s Universal Analytics web analytics software and utilizing all of the functionality that is offered with Enhanced Ecommerce tracking capabilities.
    Enhanced Ecommerce provides you with a complete picture of what customers on your site are seeing, interacting with and purchasing.
    One of the ways you track what your customers are seeing is with product impressions (whenever a user sees an image or description of your products on your website).
    Normally, you track what products users see or impressions by simply adding an array of product objects to the DataLayer. These represent the products seen on the page, meaning when any page loads with product images/descriptions, data is sent to Google Analytics that a user saw those specific products. This works well.
    However, there is a major issue with this method.  Sometimes you are sending impressions for products that the user never actually sees. This can happen when your page scrolls vertically and some products are off the page or “below the fold”.
    For example, lets take a look at a page on Etsy.com:
    Sample page on Etsy.com (click for full size)
    Here are the results for the search term “Linens”. Currently, you can see sixteen products listed in the search results.  However, in the normal method of sending product impressions, a product impression would be sent for every product on the page.
    So, in reality this is what we are telling Google Analytics that the user is seeing (every single product on the page):
    Sample page of Etsy.com (click for full-size)

    Obviously, no one's screen looks like this, but by sending all products as an impression, we are effectively saying that our customer saw all 63 products. What happens if the user never scrolls past the 16 products shown in the first screenshot?
    We are greatly skewing the impressions for the products on the bottom of the page, because often times, users are not scrolling the entire length of the page (and therefore not seeing the additional products).
    This could cause you to make incorrect assumptions about how well a product is selling based off of position.
    The solution: Scroll-based impression tracking!
    Here is how it works at a high level:
    1. Instead of automatically adding all product impressions to the DataLayer, we add it to another variable just for temporary storage. Meaning, we do not send all the products loaded on a page directly to Google Analytics, but rather just identify the products that loaded on the page.
    2. When the page loads, we actually see what products are visible on the page (ones “above the fold” or where the user can actually see them) and add only those products to the DataLayer for product impressions. Now we don’t send any other product impressions unless they are actually visible to the user.
    3. Once the user starts to scroll, we start capturing all the products that haven’t been seen before. We continue to capture these products until the user stops scrolling for a certain amount of time.
    4. We then batch all of those products together and send them to the DataLayer as product impressions. 
    5. If the user starts to scroll again, we start checking again. However, we never send the same product twice on the same page. If they scroll to the bottom then back up, we don’t send the first products twice.
    Using our example on the “Linen” search results, right away we would send product impressions for the first 16 products. Then, let’s say the user scrolled halfway down the page and stopped. We would then send product impressions for products 18 through 40. The user then scrolls to the bottom of the page so we would send product impressions for 41 through 63. Finally the user scrolls back to the top of the page before clicking on the first product. No more impressions would be sent as impressions for all products have already been sent.
    The result: Product impressions are only sent as users actually navigate through the pages and can see the products. This is a much more accurate form of product impression tracking since it reflects actual user navigation. 
    Next steps: for the technical how-to guide + code samples, please see this post on the InfoTrust site.

    Remarketing Lists for Search Ads, Powered by Google Analytics

    Thursday, June 25, 2015 | 8:33 AM

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    Today we’re excited to announce you can use audiences (previously remarketing lists) created in Google Analytics to reach your customers on Google Search, with no tagging changes required. 

    Remarketing Lists for Search Ads (RLSA) allows you to tailor your search ads and based on your visitors' past activity on your website. Now you can leverage more than 200 Google Analytics dimensions and metrics to create and activate your audiences for remarketing, then use those audiences to reach and re-engage your customers with a consistent message across both Google Search and Display.

    TransUnion cuts CPA in half with RLSA

    In order to find more customers while reducing waste in their search campaigns, TransUnion, a leading financial services provider, used the audience creation capabilities in Google Analytics to spend more efficiently on Google Search.

    TransUnion started by creating two audiences. The first was for new customers―those who had visited the site and started, but not completed a credit application. The other included customers who had already converted. Splitting the audience between new and existing customers allowed TransUnion to bid higher on Google search ads for new customers and spend less on converted customers.

    The new RLSA capabilities in Google Analytics yielded impressive conversion rates and cost efficiencies for TransUnion's search campaigns. RLSA visitors had a lower bounce rate and viewed twice as many pages per session compared with regular visitors. 

    By using more tailored text with their remarketing lists, TransUnion increased their conversion rate by 65% and average transaction value by 58%. Meanwhile, CPCs for existing customers dropped 50%, resulting in a roughly 50% drop in their cost per transaction. Read the full case study here

    How to get started

    Getting started with RLSA is easier than ever before thanks to Instant Activation. Within the Admin tab, simply click Property, then Tracking Info, and finally Data Collection. Ensure that Remarketing is set to ‘ON.’


    Once you’ve enabled this setting, all your eligible audiences will begin to populate for RLSA.

    Building Audiences

    If you’d like to create new audiences, there are three ways to get started. 

    First, you can create a new audience using the Audience builder in the remarketing section of the Admin tab. Make sure you select the relevant AdWords account to share your audience with for remarketing.




    If you have an existing segment you’d like to turn into an audience, simply click on the segment options and select “Build Audience” right from within reporting. This option will take you directly to the audience builder as above.  


    Finally, you can get started quickly and easily by importing audiences from the Google Analytics Solutions Gallery.

    Activating audiences in AdWords

    Once you have shared an audience with AdWords, it will appear instantly in your AdWords Shared Library and will show eligible users in the column List size (Google search).  Keep in mind that an audience must accumulate a minimum of 1,000 users before you can use it for remarketing on Google Search. To get started, follow the instructions in the AdWords Help Center

    Support for RLSA with Google Analytics is part of an ongoing investment to provide powerful ways to activate your customer insights in Google Analytics, along with recent features like Cohort Analysis, Lifetime Value Analysis, and Active User Reporting. Stay tuned for more announcements!

    Happy Analyzing,
    Lan Huang, Technical Lead, Google Analytics,
    Xiaorui Gan, Technical Lead, Google Search Ads

    Learn to optimize your tag implementation with Google Tag Manager Fundamentals

    Wednesday, June 24, 2015 | 9:00 AM

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    We're excited to announce that our next Analytics Academy course, Google Tag Manager Fundamentals, is now open for participation. Whether you’re a marketer, analyst, or developer, this course will teach you how Google Tag Manager can simplify the tag implementation and management process.

    You'll join instructor Krista Seiden to explore topics through the lens of a fictional online retailer, The Great Outdoors and their Travel Adventures website. Using practical examples, she’ll show you how to use tools like Google Analytics and Google AdWords tags to improve your data collection process and advertising strategies.


    By participating in the course, you’ll explore:
    • the core concepts and principles of tag management using Google Tag Manager
    • how to create website tags and manage firing triggers
    • how to enhance your Google Analytics implementation
    • the importance of using the Data Layer to collect valuable data for analysis
    • how to configure other marketing tags, like AdWords Conversion Tracking and Dynamic Remarketing
    We're looking forward to your participation in this course!

    Sign up for Google Tag Manager Fundamentals and start learning today.

    Happy tagging!

    Post By: Lizzie Pace & The Google Analytics Education Team

    BT Increases Sales Volume and Efficiency Using DoubleClick Bid Manager With Google Analytics Premium

    Tuesday, June 02, 2015 | 8:00 AM

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    Cross-posted on the DoubleClick Advertiser Blog

    Modern marketers live in a world that’s dominated by data. Advancements in programmatic buying enable marketers to leverage data and analytics to connect precisely, in real time. Advertisers who are smart about organizing, segmenting, and acting on this data are realizing the benefits of more personalized marketing. BT, a leading telecommunications firm in the UK, did just that and saw fantastic results.  

    BT wanted to increase the relevance of their remarketing campaigns by creating more precise audience lists. With the help of their media agency Maxus, BT found that using Google Analytics Premium with DoubleClick Bid Manager offered the ideal solution. 

    Google Analytics Premium gave BT the ability to create granular audience segments based on site behavior metrics such as recency, frequency, referral source, and stage of cart abandonment. Once these audience lists were created, the native integration between Google Analytics Premium and DoubleClick Bid Manager meant they could be shared with the platform to make more precise media buys in just a few clicks.

    Using Google Analytics Premium with DoubleClick Bid Manager put Maxus and BT in the driver’s seat of their media campaigns. They not only gleaned full transparency with a single customer view and de-duplicated metrics across all channels, but also saw better measurement through unified reporting, and the ability to optimize based on the results.



    ”Our goals were to build up ‘best practices’ of programmatic display remarketing techniques with a focus on driving post-click sales,” says Alison Thorburn, Head of Digital DR Media at BT. “The DoubleClick suite of products enabled us to do this quickly and efficiently as audience data can be easily organized and utilized.” 

    The new analytics-driven approach produced a 69% increase in post-click sales and an 87% reduction in post-click cost per acquisition compared to the previous year’s remarketing activity. It also compared favorably to the remarketing activity that ran simultaneously outside of DoubleClick Bid Manager; post-click sales were 30% higher and post-click cost per acquisition was 42% lower. BT has now consolidated its display remarketing through DoubleClick BidManager.
    Read the full case study here.

    Posted by-
    Kelley Sternhagen, Product Marketing, Google Analytics
    Kelly Cox, Product Marketing, DoubleClick

    Daily Data-Informed Decisions With Google Analytics Premium and Google BigQuery

    Friday, May 29, 2015 | 7:45 AM


    The American Precious Metals Exchange (APMEX) is the leading purveyor of precious metals, serving millions of customers worldwide. The company partnered with E-Nor, a Google Analytics Premium Authorized Reseller, to better understand the customer journey and gain insights to improve marketing initiatives.




    The first challenge they tackled was to integrate various data assets by exporting Google Analytics Premium data to Google BigQuery. This was accomplished using both the BigQuery export and the User ID features to connect website behavioral data to the company internal customer profiles. This enabled APMEX to use data more effectively to interact with different types of customers.

    In addition, by bringing Google Analytics data into the company’s Customer Relationship Management (CRM) system, they empowered their internal teams to make data-informed decisions on a daily basis. For example, when customers call, site usage information is now available to the customer representative talking them. 
    “We have found BigQuery data to be immediately actionable. It focuses our marketing efforts, personalizes our onsite experiences, and improves the effectiveness of our sales department. When used in conjunction with our current data systems, there is seemingly no question about our customers that cannot be answered. It’s that powerful.”Andrew Duffle, Director FP&A, Analytics & Optimization, APMEX, Inc.
    As a result of the work mentioned above, APMEX has decreased the average cost per acquisition (CPA) by more than 20% while maintaining the same level of new customer orders. 

    They have also used Google Analytics Premium data to build a statistical model to target valuable customers earlier in their life cycle. For customers identified in the model, the company has increased email open rates by 58%, email conversion rates by 62%, and revenue per email by 163% as compared to the overall business. 

    To read more about how APMEX and E-Nor used Google Analytics Premium along with BigQuery in order to make more informed decisions, download the full case study.


    Posted by Daniel Waisberg, Analytics Advocate.