Analytics Expert Blog

Note: The following is a post by Matt Lillig, who is the Senior Analytics Lead at Yahoo!.

Promoted Tweets

With the recent launch of ‘Promoted Tweets’, advertisers such as Best Buy, Starbucks, Bravo, Red Bull, Sony Pictures, and Virgin America are lining up to grow their brand awareness using one of the hottest social networks around….Twitter.

According to Twitter on its official blog, “You will start to see Tweets promoted by our partner advertisers called out at the top of some Twitter.com search results pages.  Promoted Tweets will be clearly labeled as “promoted” when an advertiser is paying, but in every other respect they will first exist as regular Tweets and will be organically sent to the timelines of those who follow a brand.” (see an example below with Starbucks).

Real Time Branding

Promoted Tweets could be a great service to help advertisers grow their brand in a viral fashion due to the fact that Twitter is often described as a real-time social network.  We all know how fast information moves across Twitter, right?  Promoted Tweets could be a great way for a company like Ford to quickly get the message out to the masses about its new Ford Explorer 2011 launch.  Or in the case of the Starbucks example, in the image above, offering free coffee to those who bring in a reusable tumbler on April 15^th.  One simple Tweet can lead to lots of sales.

Real Time Tracking

Now that advertisers have the ability to grow their brand in real-time thanks to Promoted Tweets, they also have the ability to track their Promoted Tweets in real-time thanks to Yahoo! Web Analytics.  Unlike other web analytics solutions, Yahoo! Web Analytics gives advertisers the flexibility to log into their account and see visitors right after they’ve reached their web site.  No more waiting for hours to see how their campaign is performing.  With real-time measurement, advertisers can follow the viral effect of the ad campaign and optimize their Twitter advertising efforts accordingly.

How It Works

Step 1 – Log Into Your YWA account and choose the Settings tab/link at the top of the page:

Step 2 – Select the ‘Manage Campaigns’ link under the ‘Campaigns & PPC Tracking’ header:

Step 3 – Select the ‘Add New Campaign’ button at the bottom of the page and choose ‘Other Campaign’ from the drop down menu:

Step 4 – Add your Campaign Properties:

- Campaign Name (Twitter Brand Campaign)

- Description (Real Time Tracking Of Twitter Campaign)

- Cost Type (Free Campaign)

- Campaign Start Date (Start)

- Campaign End Date (End if applicable)

- Show campaign In Reports (Check ‘Show’)

- Vendor (Twitter)

- URL Parameter Equals (ex: If you append your landing page URL with www.landingpage.com?cmp=twitter, then use “cmp=twitter”)

or

- Landing Page URL Contains (ex: If your landing page contains a unique keyword parameters such as www.landingpage.com?cmp=twitter+ford+explorer+2011, then use “twitter” or “ford” as long as those keywords are unique from any of your other ads.  Even better would be to use “twitter ford explorer 2011”)

or

- Landing Page URL Equals (ex: If your landing page contains unique parameters such as www.landingpage.com?cmp=twitter+ford+explorer+2011, then use you must add the exact landing page URL “www.landingpage.com?cmp=twitter+ford+explorer+2011”)

Results

Once Yahoo! Web Analytics has been set up to track the Twitter Promoted Tweet ad, advertisers will be able to see the clicks to their ad in real-time and be able to optimize the value of that ad in real time.

To view the Twitter report in Yahoo! Web Analytics, simply select:

-       Reports link (at the top of the page)

-       Marketing link (in the left hand navigation bar)

-       Campaigns link

-       Campaign Summary link

-       Other Campaigns button

We’ve just released a new section to our Yahoo! Web Analytics Help Center called Quick Reference Guides.  There you can find our quick guides on installation and custom fields.

Our Quick Install Guide contains some basic information for the newer Yahoo! Web Analytics user so that you can get up and running as soon as possible.  Questions answered include:

• Where do I actually get my tracking code?

• Where do I put the tracking code?

• How do I check the tracking code?

You’ll also find some interesting information on how the tracking code works and what are the best steps for quickly checking how well your code is working.

Our Custom Fields Guide will give you lots of great information on YWA custom fields and how you can use them from set-up to reporting.  We cover what they are, provide some use cases and illustrate the scopes and carry-over options.

If you’re using custom fields or you’ve been in a quandary about how to use them – you need to read this guide!

If you have suggestions for other Quick Reference Guides like these, please do let us know.

In 2009 we moved all of our legacy IndexTools accounts to a new data center, additionally we introduced our new v.5 tracking code and updated the v.4 tracking code.  At that time we announced that v.4 would remain fully supported until July 30th, 2010.  Well that migration deadline is fast approaching and we would like to again remind our customers to check their site(s) to ensure that they won’t be impacted.

Please note that when v.4 support ends YWA will continue to track sites utilizing this code but going forward there will be no updates, bug fixes or technical support for that version.

We have created a migration guide for customers needing to switch and our v.5 installation guide is another invaluable resource.  Also, one of our YWACN members, Sally Knows, has put together a free tool called No Tags, No Glory which can scan your site and alert you to any pages that contain legacy tracking code.  You can also contact us if you have any questions or are having issues with the migration.

Yahoo! Web Analytics reached its second birthday last month, and it’s time to reflect upon and celebrate one of the most significant improvements that Yahoo! brought to the product with its purchase of IndexTools – Demographics and Interest Groups.

At the birth of Yahoo! Web Analytics in May 2008, demographic reporting consisted of divining the location of a website visitor from his IP address and inferring his spoken language from his browser preferences (fig. 1).  This information is very important in understanding where your visitors are located, whether there is a gap in your geo-targeting endeavors, whether it’s worth considering broader language support, and so on.

(fig. 1)

While these reports are interesting, they can be slightly one-dimensional in isolation, which is why Yahoo! introduced a richer layer of reporting in order to transform website visitor statistics into visiting people.

The Yahoo! network is enormous and Yahoo! Web Analytics reports capitalise on this by being able to tell the age, sex and gender of your website visitor if they are logged into this network.  This is not shown at an individual level, for obvious privacy reasons, but think of the significance to your targeting efforts if you know that the majority of your website visitors are females between the age of 25 and 34 (fig. 2)!

(fig. 2)

And the fun doesn’t end there.  Yahoo! properties span the length and breadth of the pastimes and enthusiasms of online users.  All types of people are catered for by Flickr, Yahoo! Answers , Yahoo! Sports, Yahoo! News, Yahoo! Finance and so on.  Within these properties are various categories of interest – and both are reported by Yahoo! Web Analytics (fig.3 & 4).

(fig. 3)

(fig. 4)

So, now you know WHO is coming to your site, WHAT are you going to do about it?

We are proud to announce that we have recently completed a series of product training webinars on YWA, which you can find in the Training Section of our YWA Resource Center.

The training sessions were designed to provide new users of the tool with a comprehensive overview of YWA, as well as offer more advanced users refresher sessions on key topics.  The idea of the training sessions is to provide you as much information on YWA as possible and help you to get the most out of the tool.  Please note that the training sessions are focused on the functionality of the tool, rather than how to perform in-depth analysis/take decisions.  However, we aim to give you enough insight into how to use the product so you can focus on getting insight from your data!

The training sessions we have created cover the following topics:

• Session 1: Starts with an overview of how YWA works, and then moves on to cover the standard installation, discussing how to enable basic tracking and how to customize the tracking code.

• Session 2: Covers how to enable sales and merchandising tracking and the standard sales and merchandising reports available in YWA.

• Session 3: Presents a series of YWA standard reports, from basic reporting on traffic, content and navigation, to demographics and techno-graphics profiling.

• Section 4: Is dedicated to conversion analysis and scenario analysis, explaining how to create and analyze sequential funnels on your website.

• Section 5: Presents the tools and features available on the YWA reporting interface, including filters, drill-downs, report comparisons, report customization, bookmark creation, segmentation, and more!

• Session 6: Covers manual campaign setup for different types of campaigns (e.g, paid search, banners, email campaigns, etc.), as well as campaign categorization and bulk campaign management.

• Session 7: Provides you with an overview of the automated setup for paid search campaigns using the Cost Retrieval feature.

• Section 8: Is dedicated to marketing and campaign reporting, and traffic attribution types.

• Section 9: Presents how to create a dashboard from scratch, how to add items to a dashboard, and how to work with the data visualization options available on a dashboard.

• Section 10: Covers how to configure account settings, both at a project and at a user level.

These webinars discuss various aspects of YWA functionality in sessions of manageable length (from 8 – 15 minutes), which you can go through at your own pace.  Each section has a set of review questions that can be taken after you have watched the section and these are located in a separate link next to each training section. Each section quiz has from 3 – 6 questions and should take no longer than a few minutes to complete.  Upon completion of the questions you’ll have the opportunity to review your answers.

We hope you will find these sessions useful, and we would like to encourage you to use these training webinars as a quick reference source on YWA.

In part I we described some of the metrics and KPIs that may be useful to content providers who wish to analyze end-user engagement with their online videos. Now we would like to show a real world example of how to use YWA to capture audience behavior while using the internet’s most popular video platform: YouTube.

Many companies now embed YouTube marketing videos directly into their website. Hosting these videos through YouTube reduces bandwidth costs and takes the headache out of setting up a hosted video platform. Companies looking to dive deeper into the performance of these embedded videos can use YWA to analyze the video metrics of value to them.  For our example we are going to measure positive and negative consumption actions determined by the viewers interaction with the slider bar.

Defining Custom Actions and Fields

The first step is to configure your YWA project for video analytics. We will use Custom Actions and Custom Fields to record the incoming video analytics data.

We’ll define each unique action that our end users might make on the embedded video:

The custom fields are used to record section block number, time section block number, video title, video channel and video type:

Embedding YouTube API Enabled Videos

The next step will be to use SWFObject embed the video into our webpage and enable the YouTube API on it.

We define the following JavaScript function that will initialize an embed YouTube Player identified as “myytplayer”:

function embedYoutube(){
	var params = { allowScriptAccess: "always" };
	var atts = { id: "myytplayer" };
	swfobject.embedSWF("http://www.youtube.com/v/" + video_id +
	"&border=0&enablejsapi=1&playerapiid=ytplayer",
	"ytapiplayer", "640", "385", "8", null, null, params, atts);
}

An API Enabled YouTube Player will call the onYouTubePlayerReady() function when it is fully initialized. We will use this function to initialize all of our YWA tracking routines:

function onYouTubePlayerReady(playerId) {
	ytplayer = document.getElementById("myytplayer");
	ytplayer.addEventListener("onStateChange", "onytplayerStateChange");
	setInterval('video_check_times()', 1000);
}

We can then embed the video in anywhere in our website using the following code:

<div id="ytapiplayer">You need Flash player and JavaScript to view this video.</div>
<script type="text/javascript">embedYoutube();</script>

Tracking Actions

Above we told our YouTube player to call the onytplayerStateChange() function each time the player changes state. We’ll use the function to fire off action tracking data to YWA:

function onytplayerStateChange(newState) {
	switch (newState){
	case 0: // Media Ended
	my_submit_action(video_has_ended);
	break;
	case 1: // Playing
	my_submit_action(video_playing);
	break;
	case 2: // Paused
	video_paused_position=0;
	video_paused_position=ytplayer.getCurrentTime();
	video_paused_position = parseInt(video_paused_position);
	my_submit_action_with_position(""+video_paused_seconds,""
	+video_cf_paused_position,""+video_paused_position);
	my_submit_action(video_paused);
	break;
	case 3: // Buffering
	my_submit_action(video_buffering);
	break;
	case 5: // Ready
	my_submit_action(video_ready);
	break;
 }
}

Checking for slider bar movement

Whenever an end user uses the slider bar, they could be initiating a positive or negative consumption action. For instance if they fast forward to the end of the video because they were bored, this could be interpreted as a negative consumption action. However if they rewind the video it could be because they found that particular section compelling,  a positive consumption action.

In addition we can also keep track of the actual position the slider bar was moved from, and moved to. This is accomplished using an action to signal previous position event – ‘video_playing_position_changed_backward_seconds_prev’  in conjunction with and an action based custom field to actually record the video position in seconds called ‘video_cf_old_position’ with value passed in ‘video_old_position’. Similarly for the position the slider bar is moved to, we use another action: ‘video_playing_position_changed_forward_seconds_new’; and a custom field called:  ‘video_cf_new_position’,  with a value in seconds passed in ‘video_new_position’ .

We can use these custom fields to generate a custom report using the custom report wizard to show the actual time in seconds where a end user begins sliding the slider bar, and ends sliding the slider bar.

An example report to show sections where slider bar activity occurred could  use ‘video_cf_old_position’ as a group and a metric of  action  ‘video_playing_position_changed_backward_seconds_prev ‘ ; as well as additional grouping for video title, channel, type.

There is no callback event handler for user initiated slider changes and so a periodic timer event is used to call our video_check_times() function to check if the play time has been fast forwarded or rewound by the user:

function video_check_times()
{
	video_check_times_counter++;
	video_position = ytplayer.getCurrentTime();
	video_position_change = video_position - video_old_position ;
		if( (video_position_change < -3) || (video_position_change > 5) ){
		SliderPositionChangeEvt(video_old_position , video_position );
	}
	video_old_position = video_position ;
}

We use the setInterval JavaScript function to run this function every 1 second to check for user initiated slider changes.

If we do detect a user initiated change, we’ll then call the SliderPositionChangeEvt function:

function SliderPositionChangeEvt(video_old_position, video_new_position){

	video_old_position = parseInt(video_old_position);
	video_new_position = parseInt(video_new_position);

	my_submit_action(video_playing_position_changed);

	if(video_new_position > video_old_position) {
	my_submit_action_with_position(""+video_playing_position_changed_forward_seconds_prev,
	""+video_cf_old_position,""+video_old_position);

	my_submit_action_with_position(""+video_playing_position_changed_forward_seconds_new,
	""	+video_cf_new_position,""+video_new_position);
	my_submit_action(video_playing_position_changed_forward);
	my_submit_action(""+video_negative_consumption);
}

else {
	my_submit_action_with_position(""+video_playing_position_changed_backward_seconds_prev,
	""+video_cf_old_position,""+video_old_position);
	my_submit_action_with_position(""+video_playing_position_changed_backward_seconds_new,
	""	+video_cf_new_position,""+video_new_position);
	my_submit_action(video_playing_position_changed_backward);
	my_submit_action(""+video_positive_consumption);
}
}

Putting It All Together

We’ve combined all of the above code fragments into a live test page you can view at:

http://www.yanalyticsblog.com/sandbox/ywa_yt/example1.html

We’ve also added some realtime diagnostics information so you can see the state changes that we are tracking. You can download the zipped up source code here: example .

Please note the example code has to be run from a proper http://www… web url and not from just a local hard disk file c://… to function correctly.

Viewing the Data

Once you’ve collected some data you’re going to need to put together a report to view it. We’ll select our desired actions as the metrics in the Custom Report Wizard:

Running the report we can now see that our embedded video is generating more negative consumption actions than positive:

This could indicate that we need to edit the video to make it more interesting to our viewers.

Conclusion

We hope this example does show you the power of leveraging YouTube’s open API with YWA’s versatile tracking code. In future posts we’ll demonstrate some more complex techniques, including one that uses video segmentation to analyze the most popular sections of a video and which sections of video drive conversion clicks. For those eager readers who wish to try this video time segmentation code in advance, it is available here: YWA_Video_YouTube .

In part I we described some of the metrics and KPIs that may be useful to content providers who wish to analyze end-user engagement with their online videos. Now we would like to show a real world example of how to use YWA to capture audience behavior while using the internet’s most popular video platform: YouTube.

Many companies now embed YouTube marketing videos directly into their website. Hosting these videos through YouTube reduces bandwidth costs and takes the headache out of setting up a hosted video platform. Companies looking to dive deeper into the performance of these embedded videos can use YWA to analyze the video metrics of value to them.  For our example we are going to measure positive and negative consumption actions determined by the viewers interaction with the slider bar.

Defining Custom Actions and Fields

The first step is to configure your YWA project for video analytics. We will use Custom Actions and Custom Fields to record the incoming video analytics data.

We’ll define each unique action that our end users might make on the embedded video:

The custom fields are used to record section block number, time section block number, video title, video channel and video type:

Embedding YouTube API Enabled Videos

The next step will be to use SWFObject embed the video into our webpage and enable the YouTube API on it.

We define the following JavaScript function that will initialize an embed YouTube Player identified as “myytplayer”:

function embedYoutube(){
	var params = { allowScriptAccess: "always" };
	var atts = { id: "myytplayer" };
	swfobject.embedSWF("http://www.youtube.com/v/" + video_id +
	"&border=0&enablejsapi=1&playerapiid=ytplayer",
	"ytapiplayer", "640", "385", "8", null, null, params, atts);
}

An API Enabled YouTube Player will call the onYouTubePlayerReady() function when it is fully initialized. We will use this function to initialize all of our YWA tracking routines:

function onYouTubePlayerReady(playerId) {
	ytplayer = document.getElementById("myytplayer");
	ytplayer.addEventListener("onStateChange", "onytplayerStateChange");
	setInterval('video_check_times()', 1000);
}

We can then embed the video in anywhere in our website using the following code:

<div id="ytapiplayer">You need Flash player and JavaScript to view this video.</div>
<script type="text/javascript">embedYoutube();</script>

Tracking Actions

Above we told our YouTube player to call the onytplayerStateChange() function each time the player changes state. We’ll use the function to fire off action tracking data to YWA:

function onytplayerStateChange(newState) {
	switch (newState){
	case 0: // Media Ended
	my_submit_action(video_has_ended);
	break;
	case 1: // Playing
	my_submit_action(video_playing);
	break;
	case 2: // Paused
	video_paused_position=0;
	video_paused_position=ytplayer.getCurrentTime();
	video_paused_position = parseInt(video_paused_position);
	my_submit_action_with_position(""+video_paused_seconds,""
	+video_cf_paused_position,""+video_paused_position);
	my_submit_action(video_paused);
	break;
	case 3: // Buffering
	my_submit_action(video_buffering);
	break;
	case 5: // Ready
	my_submit_action(video_ready);
	break;
 }
}

Checking for slider bar movement

Whenever an end user uses the slider bar, they could be initiating a positive or negative consumption action. For instance if they fast forward to the end of the video because they were bored, this could be interpreted as a negative consumption action. However if they rewind the video it could be because they found that particular section compelling,  a positive consumption action.

In addition we can also keep track of the actual position the slider bar was moved from, and moved to. This is accomplished using an action to signal previous position event – ‘video_playing_position_changed_backward_seconds_prev’  in conjunction with and an action based custom field to actually record the video position in seconds called ‘video_cf_old_position’ with value passed in ‘video_old_position’. Similarly for the position the slider bar is moved to, we use another action: ‘video_playing_position_changed_forward_seconds_new’; and a custom field called:  ‘video_cf_new_position’,  with a value in seconds passed in ‘video_new_position’ .

We can use these custom fields to generate a custom report using the custom report wizard to show the actual time in seconds where a end user begins sliding the slider bar, and ends sliding the slider bar.

An example report to show sections where slider bar activity occurred could  use ‘video_cf_old_position’ as a group and a metric of  action  ‘video_playing_position_changed_backward_seconds_prev ‘ ; as well as additional grouping for video title, channel, type.

There is no callback event handler for user initiated slider changes and so a periodic timer event is used to call our video_check_times() function to check if the play time has been fast forwarded or rewound by the user:

function video_check_times()
{
	video_check_times_counter++;
	video_position = ytplayer.getCurrentTime();
	video_position_change = video_position - video_old_position ;
		if( (video_position_change < -3) || (video_position_change > 5) ){
		SliderPositionChangeEvt(video_old_position , video_position );
	}
	video_old_position = video_position ;
}

We use the setInterval JavaScript function to run this function every 1 second to check for user initiated slider changes.

If we do detect a user initiated change, we’ll then call the SliderPositionChangeEvt function:

function SliderPositionChangeEvt(video_old_position, video_new_position){

	video_old_position = parseInt(video_old_position);
	video_new_position = parseInt(video_new_position);

	my_submit_action(video_playing_position_changed);

	if(video_new_position > video_old_position) {
	my_submit_action_with_position(""+video_playing_position_changed_forward_seconds_prev,
	""+video_cf_old_position,""+video_old_position);

	my_submit_action_with_position(""+video_playing_position_changed_forward_seconds_new,
	""	+video_cf_new_position,""+video_new_position);
	my_submit_action(video_playing_position_changed_forward);
	my_submit_action(""+video_negative_consumption);
}

else {
	my_submit_action_with_position(""+video_playing_position_changed_backward_seconds_prev,
	""+video_cf_old_position,""+video_old_position);
	my_submit_action_with_position(""+video_playing_position_changed_backward_seconds_new,
	""	+video_cf_new_position,""+video_new_position);
	my_submit_action(video_playing_position_changed_backward);
	my_submit_action(""+video_positive_consumption);
}
}

Putting It All Together

We’ve combined all of the above code fragments into a live test page you can view at:

http://www.yanalyticsblog.com/sandbox/ywa_yt/example1.html

We’ve also added some realtime diagnostics information so you can see the state changes that we are tracking. You can download the zipped up source code here: example .

Please note the example code has to be run from a proper http://www… web url and not from just a local hard disk file c://… to function correctly.

Viewing the Data

Once you’ve collected some data you’re going to need to put together a report to view it. We’ll select our desired actions as the metrics in the Custom Report Wizard:

Running the report we can now see that our embedded video is generating more negative consumption actions than positive:

This could indicate that we need to edit the video to make it more interesting to our viewers.

Conclusion

We hope this example does show you the power of leveraging YouTube’s open API with YWA’s versatile tracking code. In future posts we’ll demonstrate some more complex techniques, including one that uses video segmentation to analyze the most popular sections of a video and which sections of video drive conversion clicks. For those eager readers who wish to try this video time segmentation code in advance, it is available here: YWA_Video_YouTube .

In part I we described some of the metrics and KPIs that may be useful to content providers who wish to analyze end-user engagement with their online videos. Now we would like to show a real world example of how to use YWA to capture audience behavior while using the internet’s most popular video platform: YouTube.

Many companies now embed YouTube marketing videos directly into their website.  Hosting these videos through YouTube reduces bandwidth costs and takes the headache out of setting up a hosted video platform.  Companies looking to dive deeper into the performance of these embedded videos can use YWA to analyze the video metrics of value to them.

To keep things simple, lets just concentrate on 2 measurements: video starts and video completions.  This will allow us to see how many visitors were compelled to start watching a video and the number of them who found the video interesting enough to see through to the end.

Defining Actions

The first thing we will want to do are add two custom actions to our YWA project, Video1_End and Video1_play:

We selected unique because we are only interested in tracking the first time the action happens during their visit. Also, you will want to create new custom actions for each video that you track on your site.

Embedding YouTube API Enabled Videos

The next step will be to use SWFObject embed the video into our webpage and enable the YouTube API on it.

We add the following JavaScript code to the head of page:

<script type="text/javascript">
function onYouTubePlayerReady(playerId) {
 ytplayer = document.getElementById("myytplayer");
 ytplayer.addEventListener("onStateChange", "onytplayerStateChange");
}
</script>

The addEventListener function in the code above will trigger every time that the YouTube player changes state.  In our example here we are interested in 0 (Video End) and 1 (Video Play).

We can then embed the video in anywhere in our website using the following code:

<script type="text/javascript">
var params = { allowScriptAccess: "always" };
var atts = { id: "myytplayer" };
swfobject.embedSWF("http://www.youtube.com/v/aWPi-po2KYU?enablejsapi=1&playerapiid=ytplayer", "ytapiplayer", "425", "356", "8", null, null, params, atts);
</script>

YWA Action Tracking

We’ll also add the following function to the head of the page in order to catch all of the state change events fired off by the YouTube API:

<script type="text/javascript">
function onytplayerStateChange(newState) {
	showytplayerState(newState);
	switch (newState){
		case 0: // Video End
			var YWATracker = YWA.getTracker("XXXXXXX");  //Replace Xs with your YWA Proj ID
			YWATracker.setAction('05');
			YWATracker.submit_action();
			break;
		case 1: // Video Play
			var YWATracker = YWA.getTracker("XXXXXXX");  // Replace Xs with your YWA Proj ID
			YWATracker.setAction('06');
			YWATracker.submit_action();
			break;
		}
}
</script>

Running The Report

After your YouTube API and YWA Tracking Code is inserted you should start to get real-time data about the video’s performance in your YWA project.  The easiest way to view this data is to run the Conversion Summary report:

Conclusion

While basic, this example does show you the power of leveraging YouTube’s open API with YWA’s versatile tracking code.  In future posts we’ll demonstrate some more complex techniques, including one that uses video segmentation in order to calculate positive and negative consumption actions.

Also, you can download an example that contains all of the above code HERE, enjoy!