Here are some of the highlights from this case study that showcase their success with YWA:

• Before Yahoo! Web Analytics was implemented:

“We were literally paying thousands of dollars every year for upkeep on websites that we were unsure of the contributions they made to our revenue, and their potential to drive even more,” says Jon Kennedy, President of GrandStay® Hospitality. “We needed to see the whole picture so that we could better spend our precious advertising budget on behalf of our stakeholders.”

• After the first solid month of tracking with Yahoo! Web Analytics, GrandStay® Hospitality realized that:
  • most of its revenue was being generated by the GrandStay® hotel chain
  • two-thirds of all traffic came from the microsites – not the main three corporate sites
  • most bookings occurred from organic SEO traffic
  • pay-per-click search advertising produced a huge return-on-investment, which resulted in an increase spend on that advertising vehicle

“We are so happy that this analytical mess is behind us,” says Jon Kennedy, President of GrandStay® Hospitality. “In the very near future, we should be able to spend our marketing budget based on actual performance, which was exactly what we were looking for and we can’t wait for what the next year will bring.”

To view the full case study, please click here to download the PDF.

The excerpt below is from a blog post by Shane Wiley (VP, Data and Privacy Governance at Yahoo!.  See the full post here.

Yahoo! Launches Global Support for Do Not Track

Yahoo! Web Analytics 10.3.22: related links:

Product Update

Resolved Issues

In today’s 10.3.22 release, you’ll see changes to the following pages (click on images to see full size):

Settings / Manage Campaigns

Changes:

• We’ve updated the look and feel
• We’ve moved the “Add new campaign” button from the bottom of the page to the top.
• We’ve collapsed the campaigns into groups of campaign types

Settings / Manage Campaigns

Changes:

• We’ve updated the look and feel
• We’ve moved the “Add new internal campaign” button from the bottom of the page to the top.

Other pages in which we’ve updated the look and feel.

• Settings / Manage Campaigns / Add New Campaign
• Settings / Manage Internal Campaigns / Add New  Internal Campaign
• Settings / Manage Internal Campaign Categories
• Settings / Manage Campaign Categories
• Settings / Manage Dashboards

Searching for Settings

We’ve also added a search box to the Settings page to make it easier to find the links you need.  Simply type the relevant phrase into the search box and matching links will be highlighted.

Here are some of the excerpts from this case study that highlight their success with YWA:

• “In one place, we see revenue, cost, unique clicks, repeat clicks and more for each campaign”
• “After analyzing and optimizing our campaigns for a couple of months, we were able to lower our cost-per- order by 38%”
• “We were also able to increase our number of orders by over 30% while spending less money”
• “Yahoo! Web Analytics gives us the complete picture on visit path, number of visits, demographics, search phrase and much more”

One vital advantage of online advertising is the ability to collect more precise and varied data on campaign performance than with other media. But collecting reams of campaign data doesn’t always translate into reams of knowledge about your campaign’s effectiveness.

This bothered Kathy Gould, founder and CEO of Cajam Marketing, a consulting firm that specializes in maximizing online and offline marketing campaigns through analytics.  After all, analytics uses computer technology, research and statistics to solve business problems.  For that, you need the right kinds of data – and Gould wasn’t getting what she wanted.

Enter Yahoo! Web Analytics (YWA), which Cajam Marketing began using to analyze campaign effectiveness for its clients, large and small.  YWA, a customizable, enterprise-level website analytics system, helped the firm increase sales and visitor satisfaction, reduce marketing costs, and gain new insights on its website customers

To view the full case study please click here to download the PDF.

Related posts:

• Online Video Analytics – An Introduction
• Online Video Analytics – Tracking Embedded YouTube Videos

In this blog post we will show how YWA can be used to see which sections of a video are the most popular. This can provide insights into your visitors’ engagement with your site’s video content. In our previous two articles (above) on online video analytics, we looked at how to capture active-user actions (such as pressing pause or sliding the slider from one position to another) and how to report on these user interactions using YWA.

In this article we will be showing how to measure the number of users that watched particular fixed-length segments of any video or group of videos. In the example that follows, you will see that we can  define  video sections as either 10 percentage segments of the entire video playtime, or 10-second segments of the video playtime. The choice here depends on what you wish to report on, either relative 10% sections of video, or 10 separate 10-second sections of the video. I would suggest that in general and especially for long videos, the 10% segmentation scheme is more useful.

Below is an example of such a video engagement graph for a particular video.

Video Engagement Characteristic Graph

In the above we have chosen 10% subsections of the video numbered 1..10 corresponding to the 1 for first 10% , 2 for the 2nd 10%,  And so on

As can be seen from this graph the audience retention by the end of the video is fair in this case with 20,000 people getting to the last 10% of the video  out of the 40,000 who watched the first 10% .
To produce the report above we created a custom report with the 10% sections as group dimensions and an action on playing a video section as the metric.  We also filtered for a particular video

Once your report is created, you can start segmenting  by demographics like age range, sex, location etc in order to see how different segments of your audience are engaging with the video content you are providing.

Custom Report Wizard Setup for Video Engagement Characteristic Graph

So how can we go about doing this?

We can do this by using customized actions (Adding Customization to Actions in YWA).

Below is the Custom Field setup we can use to collect these video engagement characteristics.

Custom Field Setup for Video Engagement Characteristics

In the above setup table, we have highlighted in red the custom fields use for 10% segment playtime lengths in the example.

Additionally the blue highlighted Custom field can be used for the 10 second playtime length alternative example.

10%  Segment Time Length Example

Click here to see a demo of this code using 10% video sections

In this case we chose to use custom  fields to record such things as video title, video channel, which 10% segment was being played; and also an action number to record the act of starting to play a new 10% section of video.
We could add further custom fields to add extra categorization such as sub-channel, media-provider or any other relevant classification.

As an example, if a user allowed all ten 10% sections of a Beatles video from a music channel to be played in sequence, the events outlined below would be sent to YWA data collection..

Timeline Example of Messages Sent to YWA Data Collection

The table below is a list showing the video tracking code message sequence sent to Yahoo Web Analytics YWA Data Collection corresponding to the above timeline example.

If you are implementing this code you can check all is well by using a tool such as httpfox (see Tracking Code Testing) and checking the http message sequence’s query string for x as action number and cf_xx as segment number. These two will correspond to the example sequence in the above table with x in this case as 40,  and custom field cf29 counting 1,2,3,4..10.

If the video was 3 minutes or 180 seconds, then the gap between each message to YWA data collection being sent would be about 18 seconds. Each message would include the above 3 custom fields and one action.

Why do we do we send these data collection messages periodically rather than a single message at end?

The reason we do this is that if a user navigates away from the video we cannot be sure to get any data before the browser closes or the user navigates to a new site.  However, if we periodically send data beacons, we can be sure to collect data before the user leaves.

So how does the tracking code work to get this data collected?

Some nuts and bolts.
The code has a periodic monitor that is a bit like a man with a clipboard standing beside you and checking what section of video you are watching every few seconds.
The monitor man makes a note every time you start to watch a new 10% segment of video.

The code runs using a timer periodically every 3 seconds (shown in above timeline diagram using blue arrows).

In our example…

We’ve used the YouTube player API to get the current playtime position and other data.

video_position = getCurrentTime();
video_duration = getDuration();
video_chunk_size = video_duration / video_chunks ; // comment: video_chunks is = 10  (10 * 10%  segment chunks)
video_which_chunk = video_position / video_chunk_size; // comment: get segment chunk 0 .. 10.00
video_which_chunk=parseInt(video_which_chunk); // comment: convert to integer whole number
video_which_chunk = video_which_chunk + 1; //comment start at chunk number 1 not 0

The code then converts this playtime position into the corresponding 10% segment number. In the code example provided above the 10% segment number is called “video_which_chunk“.

The code then checks if this 10% segment number has changed since the last time that this repeating periodic code checked the player position 10% segment number. If it has changed from the previously checked segment number value, then the code reports to YWA data collection that a new 10% segment of video has started playing (shown in the above timeline diagram using red arrows).

This repeated periodic looping of the code is  similar to what we described in Online Video Analytics – Tracking Embedded YouTube Videos where the periodic code regularly checks for slider bar movement.

(If we were interested in recording 10-second segment start events then we would set the boundaries as 10 seconds instead of 10% of total playtime.)

In the sample code we are using the actual YouTube video_id as its video title. Alternatively you could separately setup another custom field to store a preset video title and store this separately from the YouTube video_id.

Putting it all together

With this code, and combining the slider bar recording/reporting, and player button user interaction code from our previous posts , you will be able to gather data on many user video engagement characteristics.
For example if the user watches the first two 10% sections and slides the slider bar to a new section, this can be reported on using the appropriate segment filtering.

Volume event tracking

It is also possible to detect users interactions with the volume and mute/unmute controls.

Click here to see our sample code which has volume slider reporting and volume mute/unmute reporting, and stores these events.

Alternative version: 10-second sections

Almost exactly the same style of code can be used.

Here is a demo of this 10 second of playtime segmented code.

In the case of the 10-second segment length,  video_time_chunk_recording_flag is set to 1

video_time_chunk_recording_flag = 1;

Further event correlation possibilities

The data collected can be further enhanced by  having, say, buttons,links or adverts on the same webpage as the player. You can then add the current video playtime segment number to the button/link/ad event tracking code if you wish to correlate the time in a video with a user click on some screen element.

Flags in demo code to select 10% segments or 10-second segments

The sample code here has two flags that can be used to select whether you are interested in 10% of playtime segment lengths, or 10second intervals.

These are called:

video_percent_chunk_recording_flag

for 10% segments, which is enabled by setting it to 1.

video_percent_chunk_recording_flag = 1;

and for 10 second length:

video_time_chunk_recording_flag

which is enabled as follows:

video_time_chunk_recording_flag = 1;

Don’t send messages to data collection more often than every 10 seconds

When using the 10% of playtime segmentation, care should be taken to not try to send more than about 1 message every 10 seconds to data collection. A higher rate than this when used over variable bandwidth internet and along with other web page http requests may not always be 100% reliable.

If the media length is less than 100 seconds and % segments are desired, the code should be altered to change to larger % of playtime, e.g 20% or 33%, to make sure messages are not being sent more often than recommended.

Other Video Players

The type of video segmentation discussed in this post is not limited to just YouTube embedded player, but can also be applied to any player that has a Javascript API function to get the player ‘current play time’ position. This is the only function that is necessary to be able to collect data on video segment engagement..

Enjoy!

We hope this example has shown how you can further leverage the power of YouTube’s open API along with YWA’s versatile tracking code to generate user video engagement curves. The full code for this sample is available here, which includes both the 10% segmented version and the 10 second segmented version.

Note: This change impacts data collected from February 2nd 2012 onwards and will not change historical data.

Tracking Mobile Device & Carrier

Version 10.3.18 of Yahoo! Web Analytics has added the ability to track, customize reports, and filter/segment based on device type. These options are available as dimensions for visitor, session, or tracking scope metrics, which should enable users to better understand and optimize the traffic received across the following four device types:

• Mobile
• Tablet
• TV
• Desktop

Additionally, as a Yahoo! Web Analytics user, you can now track, customize reports, and filter/segment based on specific carriers, makes, and models of devices.

Sample carriers and makes might include:

• Carrier: Verizon, Vodafone, China Mobile Hong Kong
• Make: Apple, HTC, Motorola
• Model: iPhone 3G, Droid, iPad 2

Tracking Mobile Operating System and Version

Yahoo! Web Analytics now supports tracking versions of the Android or iOS operating system.
These values have been added to the existing Operating Systems field (which already reflects desktop operating systems for Windows or Macintosh platforms.

Sample operating system and version combinations might include such examples as iOS 4.0.1, iOS 5.0, Android 3.1, and so forth.

New Mobile Reports

You no longer have to use custom fields and custom reports and try to approximate your mobile traffic. We’ve introduced some great new reports:

• Device Type > System > Device > Device Type
• Device Type > System > Device > Device Carrier
• Campaign by Device > Marketing > Campaigns > Campaign by Device

Note: The Campaign by Device report appears just below the Campaign by Type report, already on the menu.

Users can see Visits, Visitors, Page Views, & Actions by:

Device Type
—-Device Type
——–Device Make
————Device Model

Device Carrier
—-Device Carrier
——–Device Make
————Device Model

Campaign by Device
—-Campaign Vendor
——–Campaign Type
————Campaign
—————-Device Make
——————–Device Model

Yahoo! Web Analytics users can customize these new reports, adding or removing dimensions and metrics.  See below for a couple of examples.

—Device Type report—

—Device Type report—

Getting a facelift

We’ve taken on board feedback from users on our User Interface and we’ve made a couple of small changes. We want to make a cleaner workspace for our users and, while this is a work in progress, we’ve made a couple of changes in this release. We hope you like them!

Before

After

Since this change is a reality, we analysts need to deal with it and one of the first steps we can take is to calculate what percent of our Google search traffic is encrypted and thus not providing any keyword data.  This new metric can be called “Lost Keyword Data” and is something that should be tracked over time and included with your keyword reports.

To calculate this “Lost Keyword Data” in YWA we will create two custom segments that we will compare against each other.  One will show traffic generated by Google that doesn’t provide keywords and the other will show the total traffic sent by Google.

Start by creating a custom segment and adding two dimensions: 1. “Search Engines equals “Google” 2. “Search Phrases is empty.”

Then save this custom segment so that you can quickly apply it to reports across YWA:

Using the same technique we’ll create and save a segment for all Google searches:

Now I can use the “Compare Segments” functionality of YWA along with the two custom segments I created to directly compare the impact that encrypted searches has had:

Here is how these segments compare on a basic Visits report for the previous 12 week period:

Next we’ll export this table to Excel to calculate the percentages:

I have now quantified exactly how much impact this change by Google has had on my site.  In this instance I can see that the percentage of encrypted Google searches (Lost Keyword Data) has gone from a 1/2 percent to 6 percent from October to November!  This is certainly a trend I’ll be keeping an eye one and falls in line with what has been seen by other analysts on the sites they monitor.

General example (click on image to see full size):



However, we have not been able to support all the currencies our customers have requested and have not regularly updated the conversion rates.  We’re changing that!

This Thursday (November 10th), we’ll begin supporting all currencies tracked by Yahoo! Finance and we’ll update our rates on the first business day of each month.  We wanted to let you know in advance of the release so that you’re aware of how the change will work if you operate in more than one currency.

Note: These changes will apply to data collected from November 10th onwards and will not apply to historical data.  The Sales Details report will be unaffected.

Above your reports, you will see a new tab, called “Currency Rate”.  With the upcoming release, this will be displayed to all customers, but in future, we’ll display this only when the base currency differs from the reporting currency.

On this tab, you will see a link to the “Currency Rates used in this report”.  Clicking on this will expand the tab to display the relevant currency rates applying to the reporting period chosen.

We’re confident that this is a great step in improving our currency support at the request of customers and this move is part of our continuing progress in accuracy.

On November 17th, we’ll remove the “Look and Feel” customisation section from the YWA Consultant account settings and replace it with a “Customise Client Interface” feature which we feel is a simpler and better way of co-branding with us.

If you look in your Consultant account (in the Settings section), you will see that this feature is already available – so you can make your changes now and have them take effect following the release.

To customise your clients’ interface is simple.  You can:

• Link to your company’s logo (please note that this must be securely located – i.e. https://, not http://)
• Add some header text.
• Add links and information in the footer, such as company or support information.

We feel that this will allow us to maintain consistency across our Consultants’ accounts and make co-branding much easier.  We hope you like the change!

Note:  Following the release on November 17th – any change made through the old feature will be replaced by the standard YWA branding, so it is important to use this new function if you currently co-brand.

Customers using Yahoo! Web Analytics and importing their AdWords cost and impression data into the campaign reporting  via the AdWords API will have noticed that this data has been missing for several weeks.  Initially, we believed our developer token was expired and we re-applied for the token – this placed us in a 3-week queue.   Due to a communication break-down with Google, we have only just discovered that we missed a change in the terms of usage with the AdWords API and this has been the actual source of the delay in rectifying the problem.

We are working on rectifying this as a priority and and we are very sorry for the inconvenience we know this has cause to several customers.   We will update this post as soon as we have further information.

Update [Nov 16]: We have made a submission to Google and are awaiting their approval and re-activation of our token.  This may take a couple of days.