From Insights to Impact: Driving Value with Analytics
February 25, 2016
At eTail West this week we were thrilled to give a joint presentation with Chris Duncan, VP of Strategic Marketing for Kohl's, a $19B+ retailer making big strides in omni-channel analytics. Casey Carey, Head of Marketing for Google Analytics, kicked off the presentation with highlights from our new report with Harvard Business Review. Following Casey's introduction, Chris gave the audience a glimpse into the Kohl’s Greatness Agenda, launched in 2014 with the goal of becoming “the most engaging retailer in America.”
Kohl’s has seen the growing effect of micro-moments on their business in recent years and has used measurement and analytics to gain key insights:
We invite you to read the full report to learn how great companies like Kohl's are analyzingandacting to create value for their customers and for themselves.
Kohl’s has seen the growing effect of micro-moments on their business in recent years and has used measurement and analytics to gain key insights:
- They had more visits on digital devices last year than in all stores combined.
- Most of their sales are driven by people who have engaged with more than one marketing channel.
- Customers who engage online are spending more in-store.
The Google Analytics team is all about turning insights into action, which is why we commissioned a study with Harvard Business Review—we wanted to understand how great companies are using insights to drive customer value. The findings are compelling: some companies who capture the full customer journey with integrated data are generating up to 8.5x higher shareholder value.
We invite you to read the full report to learn how great companies like Kohl's are analyzingandacting to create value for their customers and for themselves.
Introducing Autotrack for analytics.js
February 18, 2016
The web has changed a lot since the early days of Google Analytics. Back then, most websites actually consisted of individual pages, and moving from one page to the next involved clicking a link and making a full-page request. With sites like this, it's possible to track the majority of relevant user interactions with a single, one-size-fits-all JavaScript tracking snippet.
But the web of today is much more complex and varied than it used to be. In addition to traditional, static websites, we have full-featured web applications. User interactions aren't limited to clicking links and submitting forms, and a "pageview" doesn't always mean a full-page load.
The web has changed, but analytics implementations have stayed pretty much the same. Most Google Analytics users copy and paste the default tracking snippet and that's it. They know there's more they can do with Google Analytics, but taking the time to learn is often not a priority.
Autotrack for analytics.js is a new solution to this problem. It attempts to leverage as many Google Analytics features as possible while requiring minimal manual implementation. It gives developers a foundation for tracking data relevant to today's modern web.Note: autotrack is maintained by the Google Analytics developer relations team and is primarily intended for a developer audience. It is not an official Google Analytics product and does not qualify for Google Analytics premium support.
Features
The autotrack library is built as a collection of analytics.js plugins, making it easy to use the entire library as-is or to pick and choose just the plugins you need. The next few sections describe some of the features autotrack enables.
Outbound link and form tracking
When a user clicks a link that points to another page on a site, that other page typically sends a pageview hit once the user arrives. Because there's a series of pageviews, Google Analytics can figure out on the back end where the user navigated to (and from). But if a user clicks a link or submits a form to an external domain, that action is not captured unless you specifically tell Google Analytics what happened.
Historically, outbound link and form tracking has been tricky to implement because most browsers stop executing JavaScript on the current page once a new page starts to load. Autotrack handles these complications for you, so you get outbound link and form tracking for free.
URL change tracking for single page applications
If you're building a single page application that dynamically loads content and updates the URL using the History API, the default tracking snippet will not suffice -- it only tracks the initial page load. Even if you're sending additional pageviews after successfully loading new content, there can still be complications.
Autotrack automatically detects URL changes made via the History API and tracks those as pageviews. It also keeps the tracker in sync with the updated URL so all subsequent hits (events, social interactions, etc.) are associated with the correct URL.
Declarative event tracking
Sometimes it's easier to declaratively add an event to the HTML than to manually write an event listener in JavaScript. Tracking simple click events is a prime example of this. To track click events with autotrack, you just add data attributes to your markup.
<button data-event-category="Video" data-event-action="play">Play</button>
When a user clicks on the above button, an event with the corresponding category and action (and, optionally, label and value) is sent to Google Analytics.
Media query tracking
Most sites today use responsive design to update the page layout based on the screen size or capabilities of the user's device. If media queries are used to alter the look or functionality of a page, it's important to capture that information to better understand how usage differs when different media queries are active.
Autotrack allows you to register the set of media query values you're using, and those values are automatically tracked viacustom dimensions. It also tracks when those values change. (Note that media query tracking requires you to set up custom dimensions in Google Analytics. The process only takes a few minutes, and the instructions are explained in themediaQueryTracker plugin documentation.)
These are just a few of the features you can enable when using Autotrack. For a complete list of all plugins and instructions on how to use them, refer to the Autotrack documentation on Github.
Who should use autotrack?
While anyone could use and benefit from autotrack, the library is primarily geared toward sites that do not customize their current analytics implementation and would like to take advantage of the features described in this article.
If you're just using the default tracking snippet today, you should consider using autotrack. If you already have a custom implementation of Google Analytics, you should first check the documentation to make sure none of the autotrack features will conflict and no data will be double-counted.
Next steps
To get started using autotrack, check out the usage section of the documentation. If you're curious to see what the data captured by autotrack looks like, the Google Analytics Demos & Tools site uses autotrack and has a page with charts showing the site's own Google Analytics data.
If you want to go deeper, the autotrack library is open source and can be a great learning resource. Have a read through the plugin source code to get a better understanding of how many of the advanced analytics.js features work.
Lastly, if you have feedback or suggestions, please let us know. You can report bugs or submit any issues on Github.
Enable better decisions with Data-Driven Attribution
February 17, 2016
Consumers see a lot of different ads as they make buying decisions. Some ads have a huge impact on the final purchase, others help the process along, and still others contribute absolutely zero. The trick, of course, is knowing which ad does what.
Today we’re introducing Data-Driven Attribution to all DoubleClick accounts. It's a new tool that helps you give the right credit to each and every advertising touch point ― and shows you the optimal combination for your marketing.
Powered by Adometry, Data-Driven Attribution uses a modeling methodology developed by Google engineers and grounded in advanced statistics and economic principles. It assigns credit accurately and automatically to all your digital media ads served through DoubleClick.
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Turbocharge your campaigns
DoubleClick Digital Marketing already has a strong attribution foundation with Multi-Channel Funnels and the Attribution Modeling Tool. Now it's even easier to make decisions about how to best allocate your digital media budget. Data-Driven Attribution is:
- Actionable: The contribution made by each marketing channel is clear (in both converting and non-converting paths), so you can make better data-driven marketing decisions.
- Accessible: Just choose your goals (such as e-commerce transaction or email signups) and Data-Driven Attribution will show you the contribution made by each of your digital campaigns.
- Comprehensive: No need for new tags, just turn on the feature and you’ll see data for your campaigns.
There’s no room for guesswork in attribution ― and when you’re not guessing, you’ll see greater ROIs and better performances.
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“Mindshare helps brands get the most of their digital marketing. To do that we need meaningful insights on the consumer path to purchase across both display and search. We have been testing Data Driven Attribution in DoubleClick and we have seen tailored recommendations that allow us to take fast action for greater impact and better ROI. In some campaigns we have been able to improve budget allocation and have seen CPA improve by 25%.”
-Karen Nayler, CEO, Mindshare Canada
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How to get started
You'll find the Attribution interface in the Reporting and Attribution section of your DoubleClick account. You can activate Data-Driven Attribution for all your floodlight tags and once you start collecting data, you'll see a new recommended model appear after seven days.
Measuring Super Bowl 50’s Top TV Ads with TV Attribution
February 8, 2016
Each year, hundreds of millions of us gather around TVs to watch America’s big game — the Super Bowl. And for many, the TV commercials are at least or maybe even more interesting than the game itself. Companies annually spend millions of dollars trying to entertain us or tug at our heartstrings. For these advertisers, it is straight up, unabashed brand advertising. Not that there’s anything wrong with that.
However, other advertisers are looking to accomplish something much different. The goal of their ads is to pique your interest, get you to find out more about the product, and yes, maybe even make a purchase. In a word, their success is based on creating “intent.” Unfortunately, understanding the impact of TV advertising based on consumer response has historically been difficult at best.
Enter the second screen. According to a recent report by Accenture, 87% of consumers use a second screen device (laptop, tablet, phone) while watching TV. The result is a direct connection between TV commercials and digital activity including search queries, search clicks, and direct website visits. Adometry TV Attribution uses machine-learning techniques to model this minute-by-minute response data and estimate the incremental impact of each unique TV spot at very granular level. In essence, it allows you to measure TV just like digital.
So, how did the TV ads from Super Bowl 50 fare when measured by Adometry TV Attribution? From a response perspective, this year’s top TV commercials are:
A much different list than that of AdvertisingAge’s top rated commercials based on creative. For a complete rundown of the TV Attribution results, check out the full article on Think with Google which includes a complete list of the top ten Super Bowl commercials, along with response volume by quarter and device.
The takeaway? For those investing in TV advertising with the goal of creating intent, you also need an effective strategy to capture and engage consumers on their second screens. In doing so, your consumers will have a much better experience and you’ll see even bigger ROI.
Reference - analytics.blogspot.in
Reference - analytics.blogspot.in
