analytics

One of the issues we focus on in our consulting practice at Web Analytics Demystified is the relationship between page performance and key site metrics. Increasingly our business stakeholders are cognizant of this relationship and, given that awareness, interested in having clear visibility into the impact of page performance on engagement, conversion, and revenue. Historically speaking tying the two together has been arduous, and, when the integration has been completed, possible outcomes have been complicated by the fact that site performance is usually someone else’s job.

Fortunately both of these challenges are becoming less and less of an issue. Digital analytics providers are increasingly able to accept page performance data, either directly as in the case of Google Analytics “Site Speed” reports, or indirectly via APIs and other feeds from solutions like Keynote, Gomez, Tealeaf, and others allowing the most widely used digital analytics suites to meaningfully segment against this data on a per-visit and per-visitor basis.

Additionally, thanks to Web Performance Optimization and the recent emergence of solutions that allow for multivariate testing of different performance optimization techniques, business stakeholders and analysts are increasingly able to collaborate with IT/Operations to devise highly targeted performance solutions by geography, device, and audience segment. Recently I had the pleasure of working with the team at SiteSpect to describe these solutions in a free white paper titled “Five Tips for Optimizing Site Performance.”

You can download the white paper directly from SiteSpect (registration required) or get the link from our own white papers page here at Web Analytics Demystified. If you want a quick preview of what the paper covers I’d encourage you to give a listen to the brief webcast we created in support of the document.

• Download the White Paper
• Watch the Webcast

If you’re thinking about how you can better measure and manage your site’s performance we’d love to hear from you. Drop us a line and we’ll walk you through how we’re helping clients around the globe get their arms around the issue.

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© 2012 Web Analytics Demystified | www.webanalyticsdemystified.com Looking for a new job in web analytics? Check out the Web Analytics Demystified Job Board!

Interested in learning how to use Analytics to make better decisions for your business? Here’s your chance; join us next week for two webinars.  We’re partnering with the Learn with Google team to present an introductory session on Getting started with Analytics, and a more advanced session covering one of the most requested topics - Digital Attribution & Conversion. Here’s a little more detail on what we’ll cover: Getting Started with Google Analytics Level of content: Beginner Covers the basics you need to get started with Analytics. Highlights the most helpful reports for ecommerce, bloggers/publishers, and lead generation businesses. Learn how to tag your campaigns and set up goals to measure if your marketing is a success. Presenter: Justin Cutroni, Analytics Advocate Date: Wednesday May 23rd, 2012 Time: 12 pm PT / 3pm ET / 8pm GMT Building Blocks of Digital Attribution Level of content: Intermediate/Advanced Learn what marketing attribution is and what it can do for your business. This webinar will cover the basics of how attribution works, and we’ll show you how to set up your Google AdWords and Google Analytics accounts to enable important attribution tools--Search Funnels and Multi-Channel Funnels. Presenter: Bill Kee, Product Manager, Google Analytics Date: Thursday May 24th, 2012 Time: 9am PT / 12pm ET / 5pm GMT These are free webinars, so be sure to register now and take a look here for more great webinars from other Google teams. Posted by Ian Myszenski, Google Analytics team

A lot of digital analytics focuses on direct response (conversions, leads, etc.). But there is an additional valuable, and sexy, focus of our marketing we don't give enough analytical love: Branding!

It is sad that we spend so little time on brand analysis, primarily because 1. there is such little accountability to brand marketing and 2. it is such a strategic part of any business.

So let's fix that problem in this blog post. Let's become BFFs with a lovely hidden gem that helps you leverage one of the largest source of data on the planet to understand the strength of your brand over time.

[Bonus One: Read: Brand Measurement: Analytics & Metrics for Branding Campaigns]

There are many different tools, both online and offline, that measure the elusive metric called brand strength. It's elusive because brand strength is, at its core deeply qualitative and none of us measurement types can really see inside your hearts and draw charts of the evolution of what's in your heart over time. So we use proxies, and we do the best we can.

One of my favorite tools to do that is Insights for Search which provides an incredible way to see how interest in your brand has grown over time and whether you are strengthening your brand over time.

Brand Strength via Unaided Brand Recall

Insights for Search sits on top of all of Google's organic search data from around the world. I believe it is one of the best possible ways to measure what humanity is thinking, and telling us via the queries they run on Google. I love using this tool to measure "unaided brand recall ."

The stronger your unaided brand recall, the more likely people recognize you, think of you, consider you when they need what you have to offer. I never search for a sports car. I search for the "best Nissan sports car."

You increase unaided brand recall by creating great products (its not called a tablet, they are all called iPads), delivering fantastic service ("their return process is as good as Zappos"), and of course online and offline advertising.

Sometimes it all works together. Recently I saw a TV ad by eBay for designer jeans. I typed designer jeans into Google (for that is what people do when they watch TV). The first ad was for Amazon. No eBay PPC ad or SEO listing showed up. Clever Amazon tying its online advertising with a competitor's offline advertising. Now I search for "amazon designer jeans." :)

For your brand Insights for Search provides an incredible way to see how your brand has grown over time, and whether you are strengthening your brand. If you strengthen it, you drive people to look for you (and not your competitors), and you can capture them more easily using Search (Organic or Paid). Brand queries, obviously, also convert better.

Leveraging Google Insights for Search

So over time, how's your brand doing?

Step 1: Type your brand name, and your direct competitor, into the Search Terms area of Insights for Search .

Step 2: Pick the right country, time period, and -this is important – high-level category in which your brand belongs.

Step 3: Click Search.

Step 4: In the middle of the resulting report you'll see a trend that looks like this:

This shows the number of searches for your brand, relative to the total number of searches done on Google over time (for the geographic region and time period you've chosen). The data you see is normalized and presented on a scale from 0-100.

This is interesting. You can see that eBay (green) rose for a while but has been essentially flat. During the same time period Walmart (red), Amazon (blue) and Target (orange) have done exceptionally well.

But (as every Analysis Ninja knows) competitive context (above) is good, but industry/category context is even better! So…

Step 5: Click on the tab that reads "Growth relative to the Shopping category" and boom!

This is a lot more interesting. [Click on the above image for a higher resolution version.]

The graph shows the change over time, starting in Jan 2004. On the right axis you can see how each brand has grown over time in terms of its brand strength, in context of the growth of the Shopping category.

It is pretty amazing to see that even as eBay has massively ramped up its offline (including big TV) advertising, at least in this context its growth (unaided brand recall) has actually lagged its competitors quite a bit.

eBay's green line is very close the performance of the category (and you'll see that often at peaks in the shopping category queries, eBay actually does worse starting holiday season 2009).

The tussle between Wal-Mart and Target is interesting. It used to be cat and mouse, but over the last three years Wal-Mart is clearly leaving Target in the dust (just look at that spike during this past holiday season, omg!).

Amazon is an interesting example. It used to fall behind lag the other two in brand queries, but you can see how starting late 2009 (bad year for Target in this context) Amazon overtook Target and now (2011, 2012) is casting a big shadow over Target. For a real appreciation of how amazing this accomplishment is, consider the TV ads Target runs, the number of Saturday mailers it sends out, the number of billboards it buys, etc.

The above trend lines, when viewed in context of your category, helps you understand how well you are doing in terms of increasing your brand strength.

Do this analysis for your company.

Brand strength is important because when I type "ebay big screen tv" in the search field, I essentially eliminate everyone else. If I type in just "big screen tv", I'm going to Amazon (they just rank so well).

Brand strength is built over time using online and offline advertising. Brand strength is not built by playing a "let's bid on just our brand terms" strategy, but by complementing that strategy with a super-smart organic and paid "let's capture all our brand and category terms" strategy.

[Bonus Two: Video: Enhancing Brand Strength (and Avoiding Brand Destruction) via Social Media]

"Timing The Market"

One thing about Amazon looked particularly interesting to me.

You'll notice that Amazon's Christmas peak comes a few weeks after Walmart and Target. See if you can notice it here:

For Walmart (red) and Target (orange) this is not surprising. These are traditional retailers who have a fixed calendar of marketing execution with an overwhelming emphasis on Thanksgiving. After that, things ramp down.

Traditional retailers often have a fixed multi-channel schedule based heavily on past traditional media plans with less flexibility in being able to incorporate real time odd trends on the web.

But look at Amazon (blue), keep an eye on the highlighted time period above and look at this:

Notice they hit their peak exactly at a time when the Shopping category hit its peak! +25% in the first image above and +37% in one immediately above.

Amazon does such a great job that their brand queries also get an extra spike during that time, from +413% to +525%. You have to hand it to the Marketing folks at Amazon. When their competitors are ramping down (perhaps due to their inflexibility), Amazon can read the market much better (notice Christmas 2010 as well) and are well placed (thanks to Paid and Organic Search strategies) to grab all these new people who are coming into the market to shop.

And precisely at that time both their large competitors are rapidly ramping down their spend! You would think that with actual stores they would ramp up during December because Amazon is at a disadvantage having to use shipping!

Here's the link that should take you directly to the analysis in the images you've seen in this post: http://goo.gl/JbUzK

#rockbranding

Data? Check. Actions?

So what can you do with this data? How can you go and destroy your competitors? :)

I've written a comprehensive post with very specific guidance on how to leverage Insights for Search to identify actions. Please check out that post here: Competitive Intelligence Analysis: Google Insights for Search

In context of the above findings, I would focus on trying to identify the geographic locations in which unaided brand recall is stronger for my competitor(s) compared to me. I would use online and offline brand marketing campaigns to shore up my brand strength.

I would also focus on the very bottom of the Insights for Search report where you are able to see the cluster of search queries most closely associated with a brand (on the left), and the most statistically significant rising terms (on the right). They are full of specific insights you can use to optimize your online search campaigns.

Please check out the blog post above for more detailed guidance.

Five Caveats!

Life would be so much better if we did not have to caveat everything. But, sadly the life of an Analyst is imperfect. :)

Here are some caveats to keep in mind when you do this analysis…

As Google Flu Trends has proven, online behavior is a very strong predictor of offline reality. I hope you'll do this analysis for your brand, get context from other data sources, and get your company to take very smart action in moving the dial on brand strength.

As always, it's your turn now.

How does your company measure brand strength/unaided brand recall currently? How cognizant are you of how your competitors are doing? Have you tried to use online data, like Insights for Search, to do this important analysis? What other caveats would you add to the four I've listed above when using this data?

Please share your experience, critique, examples, ideas and feedback via comments.

Thank you.

Excellent Analytics Tips #20: Measuring Digital "Brand Strength" is a post from: Occam's Razor by Avinash Kaushik

1. It is easy to assess product popularity globally and by market. The user experience is seamless and there was no complex setup necessary.
2. Custom reports allow you to easily view complex information in one view. It dramatically reduces the time to summarize multiple reports, document it, and share it within the organisation.
3. Google Analytics gives them access to timely information, which allows for better decision making.

At the end of 2011 we announced the Google Analytics Core Reporting API as a replacement for the Data Export API. We also announced a 6 month deprecation period for the Data Export API version 2.3, after which all v2.3 queries will return a v2.4 response. Well, it's almost been 6 months since the announcement was made. If you haven't already moved to our shiny new APIs, and we know there are quite a few of you out there who haven't, we urge you to get movin' or risk your application not working come June. The good news is that we published a new, easy to follow migration guide to help you make the transition and ensure your application continues to work after we shut down the Data Export API sometime in June. If you are building a new application, we highly recommend using the Core Reporting API v3.0. For existing applications, we also recommend moving to v3.0 but it may be easier for you to migrate to v2.4 as an intermediary step, since it is backwards compatible with the Data Export API v2.3. The great news is that if you make the move to v3.0, you'll be able to take advantage of any new features, and the compact JSON format that reduces response size by 10x! To get started, check out the Migration Guide: Moving from v2.3 APIs to v2.4 & v3.0. Additional details and support:

• Core Reporting API Forum - for any questions you may have
• Core Reporting API Changelog - for details on the change

Posted by Pete Frisella, Google Analytics API team

Many developers save time by using the Google Analytics API to automate Analytics reporting tasks. For example, you can use the API to create a dashboard to report data across multiple profiles. The Google Analytics App Gallery includes many 3rd party solutions that do this. What if you want to build something quickly that’s custom-tailored  to your business? You would typically have to spend time learning the API, figuring out how to handle authorization, then deciding how to integrate this data with a visualization library. You could build a custom solution, but it took a lot of effort – until now, thanks to the Google Analytics Easy Dashboard Library. Four months ago we started a project with a team of University of California Irvine students to simplify all of these steps. As part of this project, together we built the Google Analytics Easy Dashboard Library. This library makes it easy to use the Google Analytics API by distilling the process into three easy steps: 1. Register with Google APIs Console. 2. Copy and paste the JavaScript code. 3. Configure this code to query your data and choose a chart type to visualize it. So now you can create custom Google Analytics dashboards very quickly, with minimal code. Here’s a quick example. Say you want to create a line chart plotting visitors and visits for the last 30 days. Besides including the library, the only code required is:

<div id=”chart1”></div>
<script>
var chart1 = new gadash.Chart({
  'type': 'LineChart',
  'divContainer': 'chart1',
  'last-n-days':30,
  'query': {
    'ids': TABLE_ID,
    'metrics': 'ga:visitors,ga:visits,ga:pageviews',
    'dimensions': 'ga:date',
    'sort': 'ga:date'
  },
  'chartOptions': {
    hAxis: {title:'Date'},
    vAxis: {title:'Visits'},
  }
}).render();
</script>

Using the code above will create this chart. It’s that easy! To find out more about using the Easy Dashboard Library, read our Getting Started guide. While the current library is very useful, we think we can add more features and make it even easier to use. To reach this goal, we’ve started working with another group of UC Irvine students, this time for three academic quarters. This new project’s main goal will be to further simplify the library. We want the students we’re working with to engage with you and implement your feature requests, if possible. If you use this library, we'd love to hear how you think it can be improved. Feel free to send any feedback to through our new GA-easy-dash-feedback google group. We hope this library saves you time and helps you get more out of Google Analytics. Posted by, Jeetendra Soneja and Nick Mihailovski, Google Analytics API Team

Did you know that 40% of mobile web users reported that they’ve turned to a competitor’s site after a bad mobile experience1? With about half of all Americans now owning a smartphone2, it’s time for businesses to meet user expectations by delivering a mobile experience as good as the desktop experience. In short, it’s time to step up to the plate and build a site optimized for the mobile web. Google can help. We recently teamed up with DudaMobile to release a free mobile site builder.  In three easy steps you’re able to get started with mobile: (1) enter your site’s URL, (2) customize your site and (3) redirect mobile users automatically to the new mobile-friendly version.  It’s free and takes just a few minutes to complete! Join us on Thursday, May 10th at 1pm EST/10am PST and watch as Google showcases how two businesses, Top Mast Resort in Massachusetts and Sava’s Restaurant in Michigan, go mobile and build mobile-friendly sites--live on air. You’ll see how Top Mast is preparing to take advantage of mobile travel purchase intent - which is five times higher than online travel purchase intent, according to InsightExpress.  You’ll also see Sava’s move ahead of 95% of restaurants that do not have mobile-friendly sites, according to a study by Restaurant Science. Finally, you’ll hear from the CMO of Dudamobile, Dennis Mink; he’ll talk about best practices when using the mobile site builder and walk through important questions to ask yourself when building a mobile-friendly site. Details on how to tune in 1. Sign into Google+ on Thursday, May 10th at 1pm EST/10am PST 2. Go to the Think with Google Google+ page 3. Look for the stream post and click to enter the live stream Be sure to set a reminder in your calendar! If you have questions before or during the Hangout, post them with the hashtag #GoMoSite as a comment on the Google+ page. Posted by Suzanne Mumford, Google Mobile Ads Marketing Source: (1) Gomez 2011 (2) Nielsen February 2012

If you follow me you know I’m a huge fan of digital measurement, analysis, and optimization. I’ve written books about it, I’ve given talks about it all over the world, and for the last five years I have been building a rapidly growing company around it. The Web Analytics Demystified brand, at least according to Google, has become more or less synonymous with the subject, and for that my partners and I are grateful.

What you may not know is that I’m also a huge fan of basketball.

This time of the year, when the NBA playoffs are in full swing, is my favorite time of the year. Spring is coming in Oregon, summer vacation is approaching for my kids, and some of the greatest athletes in the world are hammer the boards and performing acts of acrobatic magic, all in an effort to get to the next round.

During last year’s playoffs I started thinking about how similar digital analytics is to basketball and running a championship NBA franchise. Both require great owners, leaders, and coaches. Both depend heavily on star talent. And both have the potential to become transformative for businesses, shareholders, and customers.

A few months back I went with that theme and put together a short presentation. I had the pleasure of giving that presentation at our recent ACCELERATE conference, and I have embedded it below for your viewing pleasure. It’s only about 20 minutes long, so just in case you’re not a fan of the Chicago Bulls and Michael Jordan, well, you only have to listen to me extol their greatness for 20 minutes …

If you agree with me and think that analytics is a lot like basketball, but if you struggle in your company to meet some of the criteria I outlined, go ahead and give me a call. I’m always happy to talk about analytics and basketball, and who knows, maybe my company can help yours!

By the way, we just published all of the ACCELERATE 2012 Chicago videos for your viewing pleasure. If you’re interested in how ACCELERATE is different go ahead and watch a few. If you like what you see, sign up to join us on October 24th in Boston (it’s free!)

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© 2012 Web Analytics Demystified | www.webanalyticsdemystified.com Looking for a new job in web analytics? Check out the Web Analytics Demystified Job Board!

Have you ever wondered which other pages on the web link to your own? Wouldn’t it be nice to know which sites are talking about your content, and in which context? Well, a problem no more: now you can see all the backlink URL’s, post titles, and more right within the new Social reports. The concept of trackbacks, a protocol by which different sites could notify each other of referencing links, first emerged back in 2002. Since then, the blogosphere has grown in leaps and bounds, but the requirement for each site to explicitly implement this protocol has always stood in the way of adoption. If only you could crawl the web and build an accurate link graph. The good news is we already do that at Google, and are now providing this insight to Google Analytics users.     If you’re not familiar with Trackbacks, then think of it as automated Google Alerts for all of your pages: you publish new content, we scour the web for pages that link to it and build automated reports for you right within Google Analytics - simple as that. These reports provide another layer of social insight showing which of your content attracts links, and enables you to keep track of conversations across other sites that link to your content. Most website and blog owners had no easy mechanism to do this in the past, but we see it as another important feature for holistic social media reports. When you know what your most linked content is, it is then also much easier to replicate the success and ensure that you are building relationships with those users who actively link to you the most. To learn more about the new Social and ROI reporting, take a look at our announcement last month, and also take a look at in-depth example of how to use these new reports to measure your user’s engagement in Google+. Posted by Ilya Grigorik, Google Analytics team

Last week, we hosted a webinar on marketing attribution. We had a lively discussion about our recent attribution whitepaper, and we looked at Google’s solutions for attribution -- including Search Funnels in AdWords and Multi-Channel Funnels in Google Analytics, and the Attribution Modeling Tool in Google Analytics Premium. During the webinar, many of you wrote in with great questions, and we’ve provided answers below to some of the top questions. If you weren’t able to join us last week, you can view a recording of the webinar here. Questions & Answers: Q: How can I learn more about getting started with attribution using Google’s tools? A:This webinar was the first in a series on attribution -- please watch the blog for updates and registration information for our next webinar, “Building Blocks of Digital Attribution.” In the meantime, read on for some more tips. Q: Where can I learn more about setting up conversions? A: Setting up conversion tracking in Google Analytics is one of the most valuable things you can do to make your reports actionable and meaningful, and getting these set up properly will allow you to use Google’s attribution solutions. There are resources available in the help center to help you set up goals and ecommerce tracking. You can also view the recording of our recent “Reaching your goals with Google Analytics” webinar. Q: When should I use AdWords Search Funnels compared to Google Analytics Multi-Channel Funnels?  A: Both tools can give you insight into how your customers ultimately end up converting on your site. If you are using AdWords Conversion Tracking today, Search Funnels is available without any additional configuration. You can see the interactions your customers have with your search ads leading up to conversion, including both clicks and impressions. However, you can only see these interactions for paid search on Google AdWords. Multi-Channel Funnels in Google Analytics allows you to analyze traffic sources beyond search, including display, social, email, referrals, affiliates and more - putting your conversion path data in a broader context. Using these reports requires installing Google Analytics tracking code on your site, and setting up goals and/or ecommerce tracking (see links above) -- once these are set up, Multi-Channel Funnels reports work automatically. Note that you  are not able to analyze search ad impressions in Multi-Channel Funnels. Watch this blog for updates on future webinars in our attribution series that will provide more details on Search Funnels and Multi-Channel Funnels. Q: How much of an impact does the use of multiple devices have in skewing the numbers we see in these reports?  A: Mobile and other devices are becoming increasingly important. Multi-Channel Funnels will report on conversion paths that take place on a single device, but not across devices. For example, if a user visited your site on a mobile phone, and then completed a purchase in a desktop browser, those interactions would not be included in the same conversion path. Q: Can I report on both AdWords Keyword and Matched Search Queries in Google Analytics? A: You have the option to view either the AdWords Keyword or the Matched Search Query by choosing these dimensions in the data table. Multi-Channel Funnels and Attribution Modeling support a wide range of AdWords and non-AdWords dimensions for reporting and creating attribution modeling rules. Q: Can you add your own models to the Attribution Modeling Tool or they are all built in?  A: You can create and save custom models in the Attribution Modeling Tool in Google Analytics Premium. Custom models allow you to create rules that adjust credit based on attributes like the traffic source (e.g. search vs. direct), position (first, middle, last) the level of engagement driven (time on site and page depth), and timing (how much time prior to conversion). Q: How do advertisers take action on attribution data? A: Attribution data can help advertisers identify marketing efforts that may be undervalued or overvalued under models such as the last click, so they can adjust their marketing programs. For example, a general keyword like “shoes” may show fewer conversions compared to a more specific, branded term for a type of shoe on a last click basis. However, applying a model that gives some credit for searches prior to the last click may show that “shoes” is credited with more conversion value. When making optimization decisions around which keywords to invest in or cut, advertisers can look at multiple models, and then experiment with investing in keywords that show higher value under alternative models. Similar methods apply to channels like display, social, email, and affiliates. This can help identify areas of opportunity that are missed when using only the last click. Happy Analyzing! Posted by Bill Kee, Product Manager for Attribution, Google Analytics team

We’re excited to announce 3 upcoming Google Analytics User Conferences in Europe. The first will be in Brussels on May 3rd, the second will be in Stockholm on May 8th and the third will be in Barcelona on May 10th.

• Meet members of the Google Analytics team, experts, and other users like you
• Learn through tangible examples how to measurably impact your business
• Find out how others solve the challenges you are facing today
• Have your business questions addressed by Google and Google Analytics Certified Partners

Posted by Jon Day, Google Analytics team

As part of our mission to make the web faster, Google Analytics provides Site Speed reports to analyze your site’s page load times. To help you measure and diagnose the speed of your pages in a finer grain, we’re happy to extend the collection of Site Speed reports in Google Analytics with User Timings. With User Timings, you can track and visualize user defined custom timings about websites. The report shows the execution speed or load time of any discrete hit, event, or user interaction that you want to track. This can include measuring how quickly specific images and/or resources load, how long it takes for your site to respond to specific button clicks, timings for AJAX actions before and after onLoad event, etc. User timings will not alter your pageview count, hence,  makes it the preferred method for tracking a variety of timings for actions in your site. To collect User Timings data, you'll need to add JavaScript timing code to the interactions you want to track using the new _trackTiming API included in ga.js (version 5.2.6+) for reporting custom timings. This API allows you to track timings of visitor actions that don't correspond directly to pageviews (like Event Tracking).  User timings are defined using a set of Categories, Variables, and optional Labels for better organization. You can create various categories and track several timings for each of these categories. Please refer to the developers guide for more details about the _trackTiming API. Here are some sample use cases for User Timings

• To track timings for AJAX actions before and after onLoad event. 
• A site can have their own definition of “User Perceived Load Time”, which can be recorded and tracked with user timings.  As an example, news websites can record time for showing the above fold content as their main metric instead of onLoad time. 
• Detailed performance measurement and optimization of sub components on a page, such as time to load all images, CSS or Javascript, download PDF files and time it takes to upload a file.

Want to check out User Timings Report in your account? Go to the content section and click the User Timings report under Content section. There are three tabs within the User Timings report for you to review: Explorer, Performance, & Map Overlay. Each provides a slightly different view of user timings reported. The Explorer tab on the User Timings report shows the following metrics by Timing Category, Timing Variable, or Timing Label (all of which you define in your timing code).

• Avg. User Timing—the average amount of time (in seconds) it takes for the timed code to execute
• User Timing Sample—the number of samples taken

The Explorer tab also provides controls that you can use to change the tabular data. For example, you can choose a secondary dimension—such as browser— to get an idea of how speed changes by browser. To learn more about which timings are most common for user timings, switch to the Performance tab. This tab shows timing buckets, providing you with more insight into how speed can vary for user reported timings for selected category, variable and label combinations. You may switch to Performance tab at any point of navigation in the Explorer tab, such as after drilling down on a specific category and variable, to visualize distribution of user reported timings.  The bucket boundaries for histograms in Performance Tab are chosen to be flexible so that users can analyze data at low values ranging from 10 milliseconds granularity to 1 minute granularity with addition of sub-bucketing for further analysis. The Map Overlay tab provides a view of your site speed experienced by users in different geographical regions (cities, countries, continents). -  Satish Kambala & Mustafa M. Tikir, Google Analytics team

The following is a guest post contributed by Daniel Waisberg, Owner of Conversion Journey, a Google Analytics Certified Partner, and Founder of Online Behavior, a Marketing Measurement and Optimization portal.
Google Analytics has recently launched a new set of reports called Social reports, which can be used to analyze on-site and off-site interactions with social networks in reference to your own website content. The reports’ ultimate goal is to enable brands to measure the return on investment for social media activities and make more accurate, data-driven decisions about social. 

1. Page Analytics: leads to more information regarding traffic that was resulted from the post.
2. View Ripple: leads to the post Ripple, an interactive visualization of the public shares of the post
3. View Page: leads to the website page that was shared
4. View Activity: leads to the actual publicly-shared post on Google+ 

 Yes, data is important. Helps make marketing better. Makes for smart organizations. Blah, blah, blah.

You know the drill: Measure. Find insights. Take action. (Or die trying.) Ascend to corporate heaven.

While there is a great deal of appreciation for the power of metrics/data, I've come to realize that Sr. Leaders don't quite appreciate the deep, and often corrosive, consequences of choosing metric x over metric y as a key performance indicator (KPI).

[Sidebar] A key performance indicator is a metric that helps you understand actual performance against preset business objectives. [/Sidebar]

The metric you choose communicates to your organization what's important to you (the POWERFUL person). It communicates to them how their personal success will be measured. That translates directly into what they prioritize when it comes to your digital initiatives.

Choose the right metric and they'll create the most glorious digital experience in the universe, the perfect acquisition campaign, the most amazing customer service channel. And they will shock you with the profits they deliver.

Choose the wrong one and they'll create self-serving, sub optimal, non-competitive, tear-inducing outcomes that will, slowly over time, bleed the business to death.

It really is that stark. Simply because it all comes down to the incentives you create.

Don't believe me?

Let's look at six corrosive metrics and their angelic twins, which illustrate this challenge – and magnificent opportunity – quite vividly.

1. Page Views vs. Visitor Loyalty

Is there anything easier than measuring Page Views? This metric has been in every tool since we started torturing web server logs to measure hits (!).

What does Page Views measure? It kinda sorta measures consumption. It is hard to know if a lot of Page Views per visit is a good thing ("The visitor loved our site so much that they read 23 pages of content!") or a bad thing ("Our site is so horrible that it took 23 pages for the visitor to find what they were looking for") or a horrible thing ("After 23 page hunt the visitor gave up, cursed us, abandoned the site, and went on to tweet to 23,000 followers that we stink").

When you look at 23 Page Views, how do you know which of the above three was the outcome?

But it gets worse.

Most content sites are currently monetized using display advertising, most commonly on a Cost Per Thousand Impressions (CPM) basis. When you are paid on a CPM basis the incentive is to figure out how to show the most possible ads on every page ("mo ads mo impressions!") and…. ensure the visitor sees the most possible pages on the site ("mo ads mo impressions mo page views mo money!").

That incentive removes a focus from the important entity, your customer, and places it on the secondary entity, your advertiser.

It does not take a degree in rocket science to see what happens next. The web is littered with examples of this awfulness.

Here's one simple example.

Photo slideshows are a great way to engage and delight customers. Yahoo! News has them. Except that they neither engage nor delight. Monetization on content websites, including likely Yahoo!, usually is on a Page View-driven CPM-incentivized mechanism.  The way this model manifests itself is that every time you click on the Next Photo button (arrow thingy) they load a new page. The new page has the next photo and lots of new ad impressions. Even on a pretty fast connection that means waiting, often for seconds. Every photo should deliver delight. Instead, every time you click on the Next Photo button, all you remember is the pain of waiting. [I'm ignoring the fact that in this day and age the photos themselves are tiny.]

Would it cause you to think positively of Yahoo! News? Or Business Insider? Or Forbes? Or all these other sites that impose a Page View-driven CPM-incentivized experience on you? More importantly: Would such a poor experience cause you to go back to these sites?

In that single session Yahoo! News made some of its Page Views quota and some of its CPM earnings. But it failed from a macro perspective. Short term gain; long term loss.

Now consider photo slideshows on (my beloved) news site, the BBC.

Just like Yahoo! News, the BBC site uses display advertising to monetize its content (outside the UK, at least). But when you click Next Photo on the BBC’s slide show, there is no page reload. In fact, all the content gets loaded (most likely asynchronous) when the first photo shows up on your screen. This means when you click Next Photo, the content loads blazingly fast. It also means the BBC photo slideshows can use a beautiful fade transition that makes for a lovely presentation.

The BBC photo slideshows don't deliver small doses of pain every time you click the next button. Instead, they deliver small moments of joy.

In that single session the BBC created fewer Page Views for itself, smaller CPM earnings. But it created joy and delight from a wonderful user experience. That directly translates to me using the words "my beloved" every single time I talk about the BBC website, visiting the site a lot more often (5x a day at least), consuming a lot more content, and in the long run actually seeing (and clicking on) a lot more ads. Short term loss; long term gain.

The metric the BBC is focused on is not Page Views, it is Visitor Loyalty.

Visitor Loyalty is not in every single report in your Digital Analytics tool. But it is there. It is a standard metric. And it measures not what happens inside a session (short-term incentive), but rather behavior across sessions (long-term incentive). It forces the designers, editors, merchandisers, IT team, and everyone in between to trade tawdry sensational stories delivered via slow-loading, pain-inducing pages, for a focus on customer (not advertiser) delight.

Ironically, that actually means more ad impressions in the long run. It means becoming big.

Take a look around you. Most content sites, be they thesun.co.uk, xinhuanet.cn or nydailynews.com, have home pages that are (and I'm being kind here) link pukes. On average these sites have 500 links on their home page. Why?

If the web analytics dashboard prominently measured Visitor Loyalty, would they still create link pukes?

Would they not think: "Even my mom hates our site, how can I earn her love, the thing that has eluded me all my life?"  Would they then not focus on relevance and not generic link puking? Would they not buy simple behavior targeting solutions to use past behavior to customize some of the experience to deliver delight?

Would they not buy a solution like JumpTime  to, in real time (!), look at the FloPower of every link and economic value it is delivering (still in real time!) to go from 500 to just 200 links? Would they not obsess about speed because both mom and dad despise waiting?

I believe the answer to every single one of those questions is yes. Yes, they would.

All from anointing the right metric, Visitor Loyalty, as your KPI. It forces a focus on the long term and on the right entity (the customer and not the advertiser).

Friends don't let friends measure Page Views. Ever.

2. Revenue vs. Economic Value

Ecommerce/lead gen type websites are typically incessantly focused on one-night stands. "Hello, so nice to see you, now take off your clothes and jump into bed with me!"

Of course they don't say that exactly. But the "buy now, buy now, buy now, buy now" design and merchandising on their websites makes that amply clear. Just try visiting orbitz.com or macys.com or petsmart.com. Sometimes this one-night stand obsession is subtle, sometimes it is obvious in what is presented to you when you land, but it always becomes more transparent as you go deeper into the site.

That is a reflection of a deep obsession on Revenue. It is reflected in the obsession with Conversion Rate. Every web analytics tool in the market measures single-session conversion rate, so if visitor, your potential customer, does not convert in that single session (i.e, refuses the one-night stand), the visit is marked as a failure!

Guess what that encourages? An ever-harder obsession about getting better at scoring more one-night stands.

The problem?

Most people don't want one-night stands. I know, I know, you are super cute and awesome. Still.

Most people want to visit your site, do some research, go away, visit other sites, come back to yours, get more confidence about your brand, go back to Google and compare reviews/prices, come back to your site and add the product/service to the cart, go and ask their spouse/boss for permission, come back and buy from you (or the other site).

That was 7 dates.

When your KPI is revenue, you are focused on trying to get as many single-session conversions as possible. You make bigger Buy Now buttons. You pimp product specs (ugh!). You do sub optimal things. You ignore delivering what's expected on the first six dates.

Sure, some people will have a one-night stand with you. But most won't. Then how you do grow your business? How do you move beyond the standard conversion rate of less than 2%?

Shift to caring about Economic Value.

Economic Value is the sum of Revenue plus the Business Value created by the macro- plus micro-conversions on your website.

So when someone visits your site and signs up to receive email, and does not buy anything, that is not a failure. That is a micro-conversion because that first date will lead to a second, a third and a seventh (if you play your cards right!).

When someone comes to your site and watches a video, that is a micro-conversion.

When someone clicks on the product reviews tab, that is a micro-conversion.

When someone clicks on the "Send Page View Email" link (to get permission from wife/spouse), that is a micro-conversion.

Etc., etc., etc.

Every micro-conversion creates economic value for your business. It engages in the awareness, consideration, comparison, purchase slow dance. It delivers higher macro-conversions (revenue!) over multiple visits by the same person by incentivizing you to behave optimally, in sync with your customers and at their speed. It gently encourages everyone in your company to obsess about the micro-conversions by saying they are of business value, to create better designs, more prominent placement of content/images/stuff customers want.

Over the long term it shifts your company from the corrosive single-session, conversion obsession (for that is what Google Analytics, SiteCatalyst, WebTrends measure) to a pan-session, way-beyond-a-one-night-stand experience that delivers higher Economic Value.

Rather than just focusing on 2% success, and 98% failure, you are now focused on 100% success!

Do please note that I'm not saying don't worry about Revenue. As you saw above, the definition of Economic Value includes Revenue. I just want you to obsess about macro plus micro as THE way of being massively profitable. And as in the first case above, by delivering delight.

Pick Economic Value, your parents will be proud of you.

3. Time on Site vs. Task Completion Rate

Over time (ironic, right?) I've developed distaste for the time on site metric.

Some of the reasons are the same ones outlined in the good, bad, and horrible scenarios for measuring page views. With time on site the problem is compounded because our web analytics tools (unless you implement special extra javascript gyrations):

1. Can't measure time spent on the site if you only see one page, and 2. Can't measure the time spent on the last page of the visit

These sad realities make that metric even more suspect. Maybe suspect is too strong a word. The above two make it very difficult to infer exactly what the performance is reflecting.

Is 7 mins time on site awesome? And should we assume that the visitor spent zero seconds on the last page, or 28 minutes? What is the implication?

[Bonus] How are Time on Page and Time on Site calculated? [/Bonus]

It is not completely valueless. But it is not worthy of being crowned a KPI.

So, what are we actually trying to measure when we use Time on Site?

We are trying to infer whether the visitor had a great experience ("Wow, they spent 92 mins on the site! Man we rock!"). We are trying to infer if they consumed enough of our content (to make them happy and make us money). We are trying to figure out where they had problems ("What? The avg time on site is only 2 mins? Golly we suck!"). We are trying to figure out if our latest redesign was a success ("Look, time on site moved from 3 mins to 900, awesome!"). We are trying to…

This is the operative word: Trying.

The reality is that there is a vacuum there. We are not (yet) sitting inside the brain of the visitor. So we take our biases (also called experience :)), our opinions, our psychological issues, and all that and try to fill that vacuum.

We have no idea who Kim Watkins is and what her 6.3802146 time on site means. So we say: "Look, the average is 2 and Kim spent 6.3802146 mins so that was an 'engaged' visit." Hurray.

Why infer? Why be so arrogant as to believe that our biases, sorry experience, will interpret Kim's visit accurately?

Why not just ask Kim?

Towards the end of her visit let's just ask: "Ms. Watkins, why did you come to our website? And were you able to complete the task you were here for?"

Two simple questions. The first gives primary purpose. The second is a yes or a no.

Kim will let us know she was there to buy a pair of Manolo Blahnik pumps. And no, she was not able to complete her task after 6.3802146 frustrating minutes because neither your navigation nor your internal site search engine got her to the right page.

And no, it was not a very "engaging" experience.

When you choose time on site as your KPI you are encouraging your organization to apply inference, and make changes that are, at best, wild guesses with a 1/100,000 chance of fixing the core problem.

When you choose task completion rate as your KPI you are encouraging your organization to put their ear directly next to the horse’s mouth, listen, feel the breath, then go fix the problems the horse has identified.

You'll agree that only one of these methods improves business profitability, results in customer-centric experiences and reduced losses from failed expeditions to chase mirages identified as issues.

And no, Ms. Watkins is not a horse. She is fine young woman. :)

Don't infer. Ask.

4. % of Search Traffic vs. Share of Global Search Volume

This one is more subtle. It is a matter of which lens you want to look at your performance.

% of Search Traffic: This measures the percentage of traffic you receive from search engines, in context of all other traffic sources.

How do you get it? You log into Baidu Tongji  (or Yahoo! Analytics) and create a little pie of your Search, Campaign, Direct, Referral and Other traffic sources. That shows you that 45% of your traffic is from Search. [Given how people use the web to seek information, at least for now, around 50% seem to be about the optimal number.]

You feel proud because you started with just 5% of the traffic from search engines. You've worked on a robust search engine optimization and pay per click programs to steadily grow your search traffic. Bonuses have been distributed.

This is a cause worth celebrating and, unlike other metrics in this blog post, given the deep importance of search this metric can be promoted to a KPI. It will incentivize the right behavior. Working ever harder on understanding your content, CMS and business strategy to do ever better SEO and PPC. It will drive the % of Search Traffic graph to go up and to the right (bigger piece of the pie). That 45% is now 500,000 visits a month from search! It is pretty good.

The problem is that we can often get stuck just looking at our own data, and in doing so we miss a chance to understand the real opportunity. We might completely miss the boat even as we celebrate what looks like huge success (moving from 5% to 45%).

Share of Global Search Volume: This measures % of search queries on a search engine that result in visit to your website.

You received 500,000 visits from Google.com. There were 209 million searches in your category (say pets) on Google.com originating from the US.

So Share of US Search Volume = 500,000/209,000,000

Gives you a different perspective right?

Some questions are simple. "OMG we have such a tiny share of the visits, what do we need to grab an ever bigger share?" Sure, not all 209 million will end up on your site, but you define the pets category! You have to get more than that tiny number of referrals. This will have huge implications on your paid search strategy, your valuation of clicks you get from Google and Bing. You might have to go out and hire new people, get a new agency, experiment with the long tail, buy some behavior targeting solutions, so much more. Sure we went from 5,000 to 500,000, but that will simply not do. The opportunity is too large and too relevant to ignore.

Other questions will be much harder. "OMG we spend mmm millions on TV, Radio and Magazines trying to create demand by interrupting people. For the most part we don't even know if they care about us, our products or our ecosystem. And here are millions of people behind 209 million queries a month who are raising their hand to say they want our products and services, they are interested in our ecosystem! We are spending ttt thousands on search. Should we rethink the balance between 'interrupting to possibly create demand' and 'welcoming with open arms people who want to hear from us'?"

This is a very, very hard discussion to have. Egos, politics, years of doing the same things, opinions, and genuinely believing that the current path is the best one … all come into play.

But if you want to be an agile, nimble competitor, it is a discussion you have to have. Even if in the end the TV budget stays 5,261% higher than digital. The debate is important. Making deliberate choices is important (even if you make the wrong choice). Because deliberate choices can be revisited. Data can be analyzed. Course changes can be plotted.

If you never deliberate, you slowly silently reach the point of no return and file bankruptcy protection.

Perhaps you'll get lucky and that won't happen to your company.

But changing the lens through which you view success can ensure that you watch the right thing, you debate and deliberate, you choose to slowly experiment, you shift budget. Step one? You use a metric like Share of Global Search Volume to incentivize the people in your company to look at the right thing and then power the right discussion.

Like everyone else, I love TV. I'm not advocating that the TV budget above should be 0%. But it is profoundly sub optimal to have this mismatch: Let's spend all our money on a channel where we, at best, kinda sorta feel users with the right intent are and let's ignore the one where 100% of the users with the right intent exist (and are looking for us!). That is a unsustainable life threatening strategy for everyone. Unsurprisingly it results in a weakening of your brand and profits. Yes, even for you.

Go change your lens.

5. # of Followers (or Fans or +1s) vs. Conversation Rate

One of my most retweeted quotes about social media goes like this: "Social media is like teen sex. Everyone wants to do it. No one actually knows how. When finally done, there is surprise it’s not better."

That probably says it all.

And how do we compound the problem? As major brands we proceed to measure one of the most useless measures of success: The number of Likes we get on Facebook.

Or the number Fans or Followers or +1s on Twitter, Google+, RenRen, Vkontakte and other lovely social channels.

When your digital dashboard measures Likes/Followers/+1s, what are you incentivizing your Agencies to do?

Use every legitimate and illegitimate technique out there to beg/cajole/lead/mislead people into pressing that button. Very little thought given to what happens after the button press (no incentive!).

What is the medium or long term strategy to engage with the audience? Where is the plan to ensure your social contributions score higher on Facebook's EdgeRank algorithm? Where is the structure that will ensure you build out a real credible asset for your company?

You have a lot of Likes, but you never get to creating a robust Earned media channel for your company. [An optimal inbound marketing portfolio will have balanced Owned, Paid and Earned channels.]

To seekers of Likes and Followers, social media "strategy"ends up being something lame, like sweepstakes, polls and pimping your latest press release. That barely works in the real world. Why would it work in an ADD environment like social media?

So how do we incentivize the right behavior? Look beyond the +1s, Followers and Likes, and leverage social channels to build out a community of like-type and like-sized :) people around you, a community that converses, shares, amplifies and, over the long term delivers economic value to the company. Leverage what the channel is really, really good at, close one too many connections based on conversations and value.

I've defined four metrics (Best Social Media Metrics) that incentivize the right behavior.

In context of this blog post, you should use Conversation Rate as an alternative to # of Likes.

I've defined Conversation Rate as: # of Audience Comments Per Social Contribution

You can compute it for every social channel on the planet.

With TV you don't know who your audience is or if they are interested in you or what they care about., In social channels, you know all of those things. You can use that knowledge to participate in and initiate conversations. You can build a better connection (social equity? :)) and you can deliver value (by sharing valuable tips, answering questions, linking to good deeds by your competitors, creating special unique content, etc., etc.).

Conversation Rate incentivizes you, or your proxies (agencies), to really understand what social contribution is causing your audience to add their voice, to have a conversation with you. That will help you optimize your contributions, force you to understand your audience, and deliver value to your audience and your company.

Get zero replies per post/tweet/status update?

Your million Likers/Followers are telling you something. Stop. Reboot.

As your agency/company moves away from a Likes quest, you'll be astonished at the incentive Conversation Rate provides your employees. That in turn, slowly but surely over time, create a credible Earned media channel for your company.

So do the right thing. Converse. Don't shout. Don't pimp. Don't sweepstake.

6. # of Installs vs. 30 Day Actives

I was advising a stealth mobile application company (hello future one billion Facebook dollars!) and this example comes from that experience.

If you've ever created a mobile app you know that from version 0.1 all the oxygen in the room is taken up in trying to figure out how to get your first 100,000 installs, how to score the Editor's Pick etc.

That is understandable. There are fifty million apps in iTunes and Play.

So naturally, # of Installs becomes the KPI that goes on top of the dashboard.

The problem with # of Installs is that it does not provide deeper insights about the value of the app to the users. It does not say anything about what the engineers got right or wrong. There is nothing in # of Installs that drives an obsessive understanding of the customer, the app experience/value, product development and all those other more valuable strategic parameters.

My advice to the team was: "Let's keep # of Installs as a metric we track, but let's make 30 Day Actives as our key performance indicator – the thing we really, really focus on."

There are so many amazing incentives from a focus on 30 Day Actives.

First, the company deemphasizes short term win — installs — and emphasizes the long term win — retention.

Second, employees care a little less about hundreds of new installs and start to care about 50% of people who uninstall the app in the first 24 hours.

Third, the company comes together to focus on the customer in every facet of their execution.

What promises are our sales/marketing programs making? What does the post-install process look like?" "Is the app instrumented to collect the right usage data? What is the optimal number of ads in the app that causes fewer 30 Day Actives? When people cancel, what does that experience look like? How do we go about releasing updates to ensure higher retention? Do we need a loyalty program? What can do to empower our customers to spread their stories about us? 

And so much more.

When the focus is on the # of installs it is not hard to imagine that there is no overt incentive to consider the above questions, or to assign a high priority to getting those answers.

So change.

Use 30 Day Actives as your KPI. Build a stronger profitable business.

Summary

It is important to point out that I'm not advocating that you stop measuring page views, revenue, time on site, % of search traffic, # of Likes, or # of installs. They are all fine metrics. You'll most likely use them as diagnostic measures when you analyze the metrics I do recommend you shift to.

I'm advocating that you not make them KPIs, don't crown them God, don't allow your employees to solve just for the primitive six. Because none of these six metrics incentivize optimal behavior or business outcomes.

You become what you measure, so why not solve for what actually matters?

Let me close with a quote on incentives, from the inimitable Steve Jobs…

"Incentive structures work. So you have to be very careful of what you incent people to do, because various incentive structures create all sorts of consequences that you can't anticipate. Everybody at Pixar is incented to build the company: whether they're working on the film; whether they're working on a potential direct-to-video product; whether they're working on a CD-ROM. Whatever their combination of creative and technical talent may be, we want them incented to make the whole company successful."

No one could have framed it better than Steve.

Incentive structures are not a web analytics problem. They are an organization design problem. But in choosing the optimal metrics to crown as heroes we can use data to incentivize the right behavior, value creation for a company, and deliver happiness to customers.

Good luck!

As always it's your turn now.

Do you use the primitive six as KPIs in your company? Have they incentivized you, your peers, to solve for optimal business and customer outcomes? Do you have other suggestions for primitive metrics? How about suggestions for metrics that incentivize optimal focus? Got a favorite "OMG I'll die if we can just measure metric x"?

Please share your feedback, suggestions, critique, huzzahs via comments below.

Thank you.

You Are What You Measure, So Choose Your KPIs (Incentives) Wisely! is a post from: Occam's Razor by Avinash Kaushik

Please join us next Thursday for a webinar on marketing attribution featuring Bill Kee, our Product Manager for Attribution, and Stefan Tornquist, VP for Research at Econsultancy. Stefan will talk about insights from the recent Attribution whitepaper by Econsultancy and Google Analytics, and Bill will discuss Google’s approach to attribution and some of the tools we offer, including Search Funnels in AdWords and Multi-Channel Funnels in Google Analytics. Plus, he’ll demo the Attribution Modeling Tool in Google Analytics Premium. We'll also provide a few tips for how to get started with attribution. This webinar will be the first in a series on attribution -- so please stay tuned for future installments! Date: Thursday, April 26 Time: 10:00am PT / 1:00pm ET Click here to register We hope you’ll be able to join the live webinar, but for those who can’t make it, we’ll be sharing a recording after the event. Posted by Sara Jablon Moked, Product Marketing Manager, Conversion and Attribution

The first step in optimizing any process is to establish and obtain an accurate set of measurement data. In the context of optimizing the user experience on the web, it means that we need to measure the speed of a page as seen by your real users: users network, device type and speed, geographic location, cache sizes, and a dozen other factors all come into play.  Mobile internet is growing at an incredible rate and as we can see from the data above, mobile experience is about 1.5x slower than desktop experience. That’s a very big difference, and that is even taking into account that many popular sites are already optimizing for the mobile visitor: fewer resources, smaller resources, and smarter caching strategies. The following interactive world map presents the page load times in seconds for the complete list of countries with enough samples for accurate measurement: Finally, let’s take a look at relative page speeds across some of the popular verticals:   How does your site stack up? Posted by Mustafa Tikir and Ilya Grigorik, Google Analytics team

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Today, we’re sharing some research on marketing attribution that we conducted in partnership with Econsultancy, a leading digital market research firm. The insights -- Marketing Attribution: Valuing the Customer Journey -- provide a snapshot of how marketers and agencies are conducting attribution, the impact it has, and the barriers holding them back. If you’re not familiar with digital attribution, it’s about distributing credit to all of the elements of your digital marketing program, so you can gauge the impact of customer marketing interactions on your sales results and make more accurate investment decisions. Here are a few snippets from the report that we found interesting: It’s still a new craft, but early results show positive impact Although digital attribution is still relatively new -- 83% of practitioners we surveyed have been using it for less than 2 years -- it clearly has a positive impact on businesses that employ it. 72% agree that it leads to better budget allocations, 63% gained a better understanding of how digital channels work together, and 58% had clearer insights into their audience:  Last click attribution dominates; agencies are leading the way in experimentation Most digital marketers run multiple campaigns, each with different strategies and objectives. For instance, display campaigns that are designed to generate awareness will have a different impact on sales than paid search campaigns designed to bring in buyers. Yet most marketers today still use attribution models that do not account for these differences in strategy. Although only 14% of respondents consider “last click” attribution to be “very effective,” it remains common; most likely because marketers haven't yet found or mastered the right attribution tools. Digital marketing agencies have done more with sophisticated attribution methods and technologies: Robust attribution leads to confident digital decisions For organizations that use attribution, it often leads to greater confidence in marketing choices: if you know the impact of your programs, it’s easier to budget for them. As one online retailer commented, “Attribution was the missing piece to our campaign analysis. Now we don’t run a campaign without learning something about how our marketing affects the buying cycle, and then testing to see whether it applies in the long run.” Performing marketing attribution with Google Here at Google we spend our time building intuitive tools to make measurement easier, so that you can really use your data to make smarter decisions. That’s why we provide several important tools for marketing attribution, including Search Funnels in AdWords and Multi-Channel Funnels in Google Analytics. And check out our Attribution Modeling tool in Google Analytics Premium, which includes five standard attribution models plus a custom model builder, so you can create and customize attribution models in minutes, and see data instantly. Learn more in our Attribution Playbook. Join us for an Attribution Hangout If you’re available this Friday, April 6, at 9:00am PDT, please join Bill Kee, Product Manager for Attribution, and Justin Cutroni, Analytics Advocate, for a Google+ Hangout. Bill will talk about the research and give a demo of the Attribution tool in Google Analytics Premium, as well as discussing Multi-Channel Funnels and AdWords Search Funnels, two complementary features. To watch the Hangout on Air, tune into Justin’s Google+ Page on Friday. If you have a question that you would like us to discuss, please enter it in this this form -- and we’ll invite five of you to join the Hangout live to ask your questions. We look forward to seeing you at the Hangout on Friday! Posted by Sara Jablon Moked, Product Marketing Manager, Conversion and Attribution