Monthly Archives: October 2013

Easier recovery for hacked sites

Webmaster Level: All

We know that as a site owner, discovering your site is hacked with spam or malware is stressful, and trying to clean it up under a time constraint can be very challenging. We’ve been working to make recovery even easier and streamline the cleaning process — we notify webmasters when the software they’re running on their site is out of date, and we’ve set up a dedicated help portal for hacked sites with detailed articles explaining each step of the process to recovery, including videos.
Today, we’re happy to introduce a new feature in Webmaster Tools called Security Issues.
As a verified site owner, you’ll be able to:

  • Find more information about the security issues on your site, in one place.
  • Pinpoint the problem faster with detailed code snippets.
  • Request review for all issues in one go through the new simpified process.

Find more information about the security issues on your site, in one place
Now, when we’ve detected your site may have been hacked with spam or with malware, we’ll show you everything in the same place for easy reference. Information that was previously available in the Malware section of Webmaster Tools, as well as new information about spam inserted by hackers, is now available in Security Issues. On the Security Issues main page, you’ll see the type of hacking, sample URLs if available, and the date when we last detected the issue.

Pinpoint the problem faster with detailed code snippets
Whenever possible, we’ll try to show you HTML and JavaScript code snippets from the hacked URLs and list recommended actions to help you clean up the specific type of hacking we’ve identified.

Request review for all issues in one go
We’ve also simplified requesting a review. Once you’ve cleaned your site and closed the security holes, you can request a review for all issues with one click of a button straight from the Security Issues page.

If you need more help, our updated and expanded help for hacked sites portal is now available in 22 languages. Let us know what you think in the comments here or at the Webmaster Help Forum.

Posted by Meenali Rungta, Webspam Team and , Webmaster Tools Team

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Measuring Twitter with Universal Analytics

In between rolling out new features for Google Analytics, we also like to feature how users and companies are actually using our products. Matt Stannard of 4PS Marketing details how to easily measure Twitter using Universal Analytics. We’ve excerpted parts of his post below; read on to see the results, and don’t forget to click through to see the technical details!



How?
Step 1 – Create a new account
So firstly, we need to create a new account, very easy although the new look and feel of Analytics remember this is under Admin and then in the Account drop down. I made a new Universal Analytics account for my particular experiment – you then need to note the UA number.


Step 2 – Install PHP / MySQL
I downloaded a WAMP stack called XAMPP as I wanted to use PHP as my Twitter monitoring library. XAMPP includes Apache, PHP and MySQL. You can use any tool of your choose provided you are able to edit the code and add the necessary Measurement Protocol requests. The library I used is was from 140Dev.


Step 3 – Create Twitter Application
In order to use the PHP monitoring library you need to have a Twitter Application. You can create this by signing in at https://dev.twitter.com/. Click My Applications:





Create your application and after you’ve done this you will need to note the Consumer Key, Consumer Secret, Access Token, Access Token Secret.






Step 4 – Start Monitoring
So, now we’ve got our Twitter application we can begin monitoring, in the 140dev package you need to modify a few files, firstly the db_config.php. You can find the code here, on the original blog post.



Results
The reporting interface of Google Analytics is actually very effective at monitoring Twitter as you are able to look in Real Time, use Dashboards, or custom reports.



The Real Time Analytics is fantastic at showing how active the things your are monitoring on Twitter is. If you just look at the Real Time overview as this screenshot shows:




You can use Dashboards to report on key areas of interest and apply whatever filtering you need, the dashboard below just shows the key hashtags, users, users mentioned and urls shared:



Custom Reporting also allows us to produce charts such as what times of the day users were active:”



The full post can be found here.

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New AdSense Data in the Core Reporting API

Google AdSense is a free, simple way for website publishers to earn money by displaying targeted Google ads on their websites. Today, we’ve added the ability to access AdSense data from the Google Analytics Core Reporting API. The AdSense and Analytics integration allows publishers to gain richer data and insights, leading to better optimized ad space and a higher return on investment.


In the past, accessing AdSense data using the Analytics Core Reporting API has been a top feature request. We’ve now added 8 new AdSense metrics to the Analytics Core Reporting API, enabling publishers to streamline their analysis.

Answering Business Questions
You can now answer the following business questions using these API queries:

Which pages on your site contribute most to your AdSense revenue?

dimensions=ga:pagePath

&metrics=ga:adsenseCTR,ga:adsenseRevenue,ga:adsenseECPM

&sort=-ga:adsenseRevenue



Which pages generate a high number of pageviews but aren’t monetizing as well as other pages?
dimensions=ga:pagePath
&metrics=ga:pageviews,ga:adsenseCTR
&sort=-ga:pageviews

Which traffic sources contribute to your revenue?
dimensions=ga:sourceMedium
&metrics=ga:adsenseCTR,ga:adsenseRevenue,ga:adsenseECPM
&sort=-ga:adsenseRevenue

Reporting Automation
By accessing this data through the API, you can now automate reporting and spend more time doing analysis. You can also use the API to integrate data from multiple sites into a single dashboard, build corporate dashboards to share across the team, and use the API to integrate data into CRM tools that display AdSense Ads.

Getting Started
To learn more about the new AdSense data, take a look at our Google Analytics Dimensions and Metrics Explorer. You can also test the API with your data by building queries in the Google Analytics Query Explorer.

Busy? In that case, now’s a great time to try these Analytics API productivity tools:
  • Magic Script: A Google Spreadsheets script to automate importing Analytics data into Spreadsheets, allowing for easy data manipulation. No coding required!
  • Google Analytics superProxy: An App Engine application that reduces all the complexity of authorization.

We hope this new data will be useful, and we’re looking forward to seeing what new reports developers build.

Posted by Nick Mihailovksi, Product Manager, Google Analytics API Team

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An Easy Way to Upgrade to Universal Analytics

Last year we launched Universal Analytics, a new technology that allows you to measure customer interactions across platforms and devices. As we announced at the 2013 Google Analytics Summit, we’ve been working on a solution to help you upgrade your existing properties to the new infrastructure without losing any historical data.

Today, we’re announcing the Universal Analytics Upgrade, an easy, two-step process to upgrade your existing properties from Classic Analytics to Universal Analytics.

Once you complete the upgrade process, you can continue to access all of your historical data, plus get all the benefits of Universal Analytics including custom dimensions and metrics,
a simplified version of the tracking code, and better cross-domain and cross-device tracking support.

Getting Started

You can upgrade your Classic Google Analytics properties into Universal Analytics properties following these two steps:

Step 1: Transfer your property from Classic to Universal Analytics.
We’ve developed a new tool to transfer your properties to Universal Analytics that we will be slowly enabling in the admin section of all accounts. In the coming weeks, look for it in your property settings.

Step 2: Re-tag with a version of the Universal Analytics tracking code.
After you completed Step 1, you’ll be able to upgrade your tracking code, too. Use the analytics.js JavaScript library on your websites, and Android or iOS SDK v2.x or higher for your mobile apps.

Universal Analytics Auto-Transfer

Our goal is to enable Universal Analytics for all Google Analytics properties. Soon all Google Analytics updates and new features will be built on top of the Universal Analytics infrastructure. To make sure all properties upgrade, Classic Analytics properties that don’t initiate a transfer will be auto-transferred to Universal Analytics in the coming months.

Upgrade Resources

To answer common questions, we’ve put together the Universal Analytics Upgrade Center, a comprehensive guide to the entire upgrade plan. This guide includes an overview of the process, technical references for developers, and a project timeline with phases of the overall upgrade.

We’ve also included many FAQs in the Upgrade Center, but if you need more information, you can also visit the new Universal Analytics Google Group to search for answers and ask more specific questions.

We’re excited to offer you this opportunity to upgrade, and hope you take advantage of the resources we’ve created to guide your through the process. Visit the Universal Analytics Upgrade Google Group to share your comments and feedback. We’d love to hear what you have to say!

Posted By Nick Mihailovski, on behalf of the Google Analytics Team

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Mind the Gap: Improving Referral Information with Universal Analytics

The following is a guest post contributed by Dan Wilkerson, marketing manager at LunaMetrics, a Google Analytics Certified Partner & Digital Marketing Consultancy.

A core issue with measuring social media is that due to the way that traffic mig… Continue reading

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Analyze Organic Search Engine Marketing with Google Analytics & Webmaster Tools Data

There are many ways to measure the effectiveness of organic search engine marketing. We’d like to explore various techniques in a series of posts here on the Analytics blog. Today we’ll talk about understanding organic using landing pages and Webmaster Tools data. 
Today, almost all marketers are investing heavily in creating high-quality content as a way to reach users with information about their products and services. The content can take many forms – from product specific content to brand specific content. The intent is to generate traffic and conversions from a variety of sources, one of the largest of which is often search.
One way to measure the effectiveness of content is to analyze its performance as a landing page. A landing page is the first page a user sees when they land on your site. If it’s great content, and if it’s ranked highly by search engines like Google, then you should see a lot of websites ‘entrances’ via that page. Looking at landing page performance, and the traffic that flows through specific landing pages, is a great way to analyze your search engine optimization efforts.
Begin by downloading this custom report (this link will take you to your Analytics account). This report shows the landing pages that receive traffic from Google organic search and how well the traffic performs. 
Let’s start at the top. The over-time graph shows the trend of Google organic traffic for your active date range. If you are creating great content that is linked to and shared then you should see the trend increasing over time.
When you look at this data ask yourself the question: how well does the trend align with my time investment? Looking at the data below we see that the organic traffic is increasing, so this organization must be working hard to create and share good content.
Organic traffic is steadily increasing for this site. An important question to ask is, “how does this align with my search optimization efforts?”
The table, under the trend data, contains detailed data about the acquisition of users, their behavior on the site and ultimately the conversions that they generate. This includes data like Visits, % New Visits, Bounce Rate, Average Time on Site, Goal Conversion Rate, Revenue and Per Visit Value. 
Using the tabular data I can learn how search engine traffic, entering through a specific page is performing. 
Each metric provides insight about users coming from organic search and entering through certain pages. For example, % New Visits can help you understand if you’re attracting a new audience or a lot of repeat users. Bounce rate can help you understand if your content is ‘sticky’ and interesting to users. And conversion rate helps you understand if organic traffic, flowing through these landing pages, is actually converting and driving value to your business.
Again, we’re using the landing page to understand the performance of our content in search engine results.
Remember, make sure that you customize the report to include goals that are specific to your account. You can learn more about goals and conversions in our help center.  
Another very useful organic analysis technique is to group your content together by ‘theme’ and analyze the performance. For example, if you are an ecommerce company you may want to group all of your pages for a certain product category together – like cameras, laptop computers or mobile phones.
You can use the Unified Segmentation tool to bundle content together. For example, here’s a simple segment that includes two branded pages (I’m categorizing the homepage and the blog page homepage as ‘brand’ pages).

You can create other segments that include other types of pages, like specific category pages (and then view both segments together). Here is the Acquisition > Keywords > Organic report with both segments applied. This helps me get a bit more insight into the types of pages people land on when visiting from Google organic search results.
Plotting two segments, one for branded content landing pages and one for non-branded landing pages, can help you understand your specific tactics.
Regardless of the tool you use, the analysis technique is the same: look at the performance of each landing page to identify if they are generating value for your business. And don’t forget, the best context for this data is your search engine marketing plan. 
Here’s one final tip when analyzing organic traffic. Whenever you create a customization in Google Analytics, like a segment or custom report, don’t use the keyword dimension. Instead use the Source and Medium dimensions. Set the Source to ‘Google’ and Medium of ‘Organic’. It provides the most consistent data over long time periods. 
In addition to using Google Analytics, you can also use the data from Webmaster Tools to gain an understanding of your search marketing tactics. You can link your Google Analytics account and your Webmaster Tools account to access some of this data directly in Google Analytics. If you’re not familiar with Webmaster Tools, check out their help center for an overview or this awesome video.

In general the Webmaster Tools data will help you understand how well your content is crawled, indexed and ranked by Google. This is extremely tactical data that can inform many search marketing decisions, like which content to create, how to structure your content and how to design your pages. The reports are in the Acquisition > Search Engine Optimization section. 
Let’s start by viewing some data using the Acquisition > Search Engine Optimization > Landing Pages report.
Webmaster Tools data is available directly in Google Analytics. You can view the data based on landing page or search query.
Let’s review a couple of metrics that are unique to Webmaster tools: Impressions, Average Position and Click Through Rate. Impressions is the number of times pages from your site appeared in search results. If you’re continuously optimizing the content on your site you should see your content move up in the search results and thus get more impressions.
Average position is the average top position for a given page. To calculate average position, Webmaster Tools take into account the top ranking URL from your site for a particular query. For example, if Alden’s query returns your site as the #1 and #2 result, and Gary’s query returns your site in positions #2 and #7, your average top position would be 1.5 [ (1 + 2) / 2 ].
Click Through Rate (CTR) is the percentage of impressions that resulted in a click and visit to your site. Again, you can see both the impressions and the CTR for every landing page on your site. 
If we’re optimizing content then hopefully we should see our average position increase, the impressions increase and ultimately an increase in click-throughs. A very easy way to observe this behavior is by applying a date comparison to the Acquisition > Search Engine Optimization > Landing Pages report.

Use the Search Engine Optimization > Landing Pages report to understand if your content is getting ranked higher and generating clicks.
What happens if impressions and average position are increasing but you’re not getting clicks? You’re getting ranked better, but what is listed in the results may not get a response from the user. 
There are lots of ways to optimize your content and change what is listed in the search results. You could adjust your page title or meta description to improve the data that is shown to the user and thus increase the relevancy of the result and your Click Through Rate. 
We’ll be back soon with another article on measuring and optimizing organic search traffic with Analytics.
Posted by Justin Cutroni, on behalf of the Google Analytics Education team

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New Sample Size Control and Relative Dates Features in Google Analytics APIs

Our goal is for Google Analytics APIs to be as simple to use as possible – so we just released 2 new features that make it even easier to use our APIs.

Relative dates

All Core API and MCF Reporting API queries previously required a start and end date. In the past, apps that displayed recent data – like the last 14 days – would have to manually determine today’s date, determine when 14 days ago was, and format the dates so they could be used.


To make things easier, we’ve added support for relative dates! You can now specify NdaysAgo as a value of either the start or end date. So the date range of the last 14 days from yesterday can now be expressed as:

start-date=15daysAgo&end-date=yesterday

Using these values will automatically determine the date range based on today’s date, allowing apps to always display the data for last 14 days (or whatever time period you’d like!).

Sample size control

In certain cases, data may be sampled. To simplify setting and reporting the impact of sampling, we’ve added a couple new sampling related features.

First, we added a new query parameter to set the level of sampling. Developers can now specify whether reports should be faster or be more precise.

Second, we added 2 new fields to the API response:



  • sampleSize – The number of samples that were used for the sampled query.
  • sampleSpace - The total sampling space size. This indicates the total available sample space size from which the samples were selected.

     



With these 2 values you can calculate the percentage of visits that were used for the query.


For example, if the sampleSize = 201,000 and sampleSpace = 220,000 then the report is based on 91.36% of visits.



Together, these values allow developers to see exactly how much data was used to calculate the sample.

Getting Started

There are two easy ways to get started: you can read our reference guide on the new relative dates feature, or check out our docs on the new sample size control query parameter and sample size API response data. As always, you can stay up to date using our change logs.

Posted by Nick Mihailovski and Srinivasan Kannan, the Google Analytics API Team

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Using a permanent URL to share Custom Attribution Models & Custom Channel Groupings

The need to customize and fine-tune your marketing measurement solutions becomes a key discriminator in unlocking additional value which might have been missed when applying out-of-the-box views on your data. For this reason, the Multi-Channel Funnel Analysis within Google Analytics Attribution provides the ability to configure content based channel groupings, as well as customized attribution models. This allows you to better reflect how partial credit is assigned to the marketing efforts driving your conversions. Having the ability to develop these customized assets is great, and now you are able to easily share them with your organization, your customers, or your audience. Here is how sharing a custom channel grouping, or custom attribution model works: 
Step 1 – Build a Custom Attribution Model
Building a custom model is easy. Just go to the Model Comparison Tool report in the Attribution Section of Conversions. In the model picker you can select ‘Create new custom model’, which opens the dialog to specify rules which can better reflect the value of marketing serving your specific business model. As an example, we can develop a model to value impressions preceding a site visit higher within a 24 hour time window. We also set the relevant lookback window to 60 days, as we know our most valuable users have longer decision and decide cycles:
Click image for full-sized version
Ensure you opt-in the Impression Integration, enabling Google Display Network Impressions and Rich-Media interactions to be automatically added to your path data through the AdWords linking. Don’t forget to also check out the recorded webinar from Bill Kee, Product Management Lead for Attribution, providing more details on how to create a custom model.
Step 2 – Access the Model in Personal Tools & Assets Section
In the admin section you can now look at your personal tools & assets. The newly created model will show up in the ‘Attribution Models’ section. You can find custom channel groupings you created under Channel Groupings.


The table shows all assets available, and a drop-down allows you to ‘share’ these assets through a link.


Step 3 – Share the Link – Done!
From the drop-down Actions menu select ‘Share’, and a permanent link to the configuration of this object is generated. This link will point to the configuration of the shared asset, allowing anyone with a GA implementation and the link to make a copy of the asset config, and save it into their instance of GA. You maintain complete control over who you share your assets with. 


Include the link to your brand-new attribution model asset in an email, IM message, or even a Blog Post, such as this one.
Happy Customizing!
Posted by Stefan F. Schnabl, Product Manager, Google Analytics

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Posted in Attribution, Conversion, Features, Multi-Channel Funnels | Comments Off

No Code Required: Auto-Event Tracking with Google Tag Manager

We’re excited to announce that Google Tag Manager has publicly launched Auto-Event Tracking, which lets you measure events happening on the page without writing HTML or Javascript. Those of you measuring events in Tag Manager today will already have minds racing with the possibilities – skip ahead to the screenshot. Everyone else, read on.






As sites become more dynamic and want to understand users’ site experiences in more detail, business owners need to know more: how long are visitors staying on a particular page? How are they interacting with interactive elements like image carousels? How many are clicking the Contact Me button? How many are clicking outbound links? Increasingly, site analytics are incomplete without answers to questions like these.
Unfortunately, until now, answering these questions required adding custom Javascript code to your website to tell Google Analytics when the event occurred. Google Tag Manager users also needed to modify the HTML of each page where they wanted to track an event. That means every time you want to track something new, or change the way you track something, you need to modify site code directly (or, in some cases, ask another colleague to do it for you.) And slower deployment of measurement campaigns directly impacts your ROI.
With Google Tag Manager’s launch of Auto-Event Tracking, we’re excited to announce a solution that provides the power of event tracking without needing to write code. By using the new Event Listener tag, you can tell Tag Manager when you want to listen for events, and then write detailed rules for what to do when an event happens. See an example of listening for form submits here:


Once you have your event listener set up, you can have tags fire based on form submits using a rule that looks for the event gtm.formSubmit. (Of course, Tag Manager supports more than form submits: it also includes clicks and timer events.) You can also make sure you’re getting the right form by using our Auto-Event Variable macros that let you narrow things down with attributes like the element ID and the form target.
The end result: you can deploy event tracking to your site and send event tracking data to Google Analytics without adding any code to your site. You can deploy measurement campaigns faster, and not writing custom code makes your solutions more robust.
Of course, it’s easiest to see the whole picture by walking through a full example. Check out the following resources for more:
We’re looking forward to getting your feedback – let us know what you think!
Posted by Lukas Bergstrom, Google Tag Manager PM

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