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ADMA Forum presentation slides on Eliminating Waste and Increasing Relevance through Targeting

Below are the slides from our recent ADMA Forum presentation on Eliminating Waste and Increasing Relevance through Behavioral Targeting: An Introduction. Please let me know your comments and thoughts, keen to get your feedback.

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Filed under  //   adma   analytics   behavioural   christian bartens   data   forum   introduction   news   presentations   speaking   strategy   targeting  

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Flowtown identifies social profiles, demographics and influencers from customers email addresses

I just came across this new service called Flowtown which is pretty interesting. 
 
The platform lets you upload your contact's email addresses for which it then returns the respective social profiles on Facebook, Twitter, MySpace, LinkedIn, Flickr and StumleUpon. And if all you have is an email address, the service can also give you a name, age, gender, occupation and location. But the best part is the integration with Klout, a service that determines a person's influence level based on Twitter and basically identifies your most influential contacts for you. 
 
Have a look at the below chart, which shows the statistics for all my 1,800 contacts compared to the 50 identified influencers. Not surprisingly, but still interesting to see is that the influencers are definitely much more likely to have a social profile online across multiple networks and that all Twitter influencers also have a Facebook and LinkedIn account.
Visit the official Flowtown website or watch the below demo video to find out more.
 

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Filed under  //   analytics   christian bartens   crm   customers   email   Facebook   Flickr   flowtown   LinkedIn   marketing   media   MySpace   networks   profiling   social   StumleUpon   targeting   tools   Twitter  

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Enhance Google Analytics with Super Cookies

Google Analytics mechanics are quite different to Omniture Stie Catalyst, for Google Analytics many of the calculations such as pages per visit, first visit, last visit, etc are stored in cookies, they are not calculated on the server side. Additionally the visitor ID is not necessarily the same for a given user, it isn't used to tie information together, instead Google Analytics relies on your cookies telling the truth. The problem is that cookies inherently only ever tell partial truths, the attrition rates are huge, so how can you trust this information? The answer is you can to a point, but be aware of what you're looking at, because its far from perfect. If you want to make it more accurate, then use super cookies. This post is aimed to touch on several of these areas where we think flash can add major value to existing Google Analytics solutions. We've already covered the super cookie technology in a previous post, so we won't dwell on the basics, if you need some more background please read the previous post:

Examples of Super Cookie additions to Google Analytics deployments
  1. Flash based persistent cookies work across multiple domains and multiple browsers - Use super cookies to re-set targeting and other custom variables across your network of domains, in any browser.
  2. Cookie deletion measurements - Find out how often do your existing users delete their standard cookies?
  3. Browser switching measurements - Do your users switch between multiple browsers? How does this affect your analytics?
 
Which browser? Who cares!!!
1. Super persistant cookies
For those wanting to get better accuracy from google analytics, or if you're using the Google Analyitcs custom variables for targeting and reporting, this is for you. 
Persisting the profile - In order to keep the rich information on your users no matter whether they delete cookies or switch browsers, you have two main options:

a) Respawn their past GA cookies before loading GA - All their profile information is associated with their visitor ID. By reseting this to it's original value (stored either prior to cookie deletion, or from a previous browser), their profile remains intact. This method can also help you to keep more realistic figures on unique visitors as long as you can replace the visitor ID prior to sending any requests to Google. Although this gives the smoothest operation, the privacy issues are obvious and must be addressed. 
b) Keep a copy of targeting parameters in a super cookie - If you detect a cookie deletion, resend the the parameters to Google Analytics so they can be re-bind them to the new visitor ID. This is a little more privacy friendly, as you're allowing the user to remove association to a specific ID, but their profile remains. You no longer know who they are, but you still know a little about them to help serve them better.

2. Cookie Deletion Measurements
If you grapple with privacy concerns but are still desperate to know how many of your users delete their cookies, then you can use this method to find out without fear of privacy invasion. This technique is useful for adjusting data inaccuracies caused by cookie deletion. 

Super cookies remain after users delete their standard cookies. Because flash cookies are not currently dealt with by browser settings (Chrome has some functionality), or understood by consumers, they are rarely deleted (assume this will increase in the future). By comparing the super cookie value to the standard cookie value, you can quickly tell if a previous value existed and has since been deleted. The high level logic is found below (note: this over-simplistic and does not allow for browser switching, see section 3!). The following pseudo code would actually be done in JavaScript:

IF standardCookie(a) is not equal to superCookie(a) AND superCookie(a) is not null THEN
{
LOAD GA CODE
Set custom variable to indicate a cookie deletion
SEND GOOGLE REQUEST
} ELSE {
LOAD GA CODE
SEND GOOGLE REQUEST
}

The above logic would enable you to see several things including:

a) The total number of cookie deletions (using the prop or event)
b) Conversion rates of users who have deleted their cookies vs those that haven't (using the custom variable). Note: This is particularly useful for Targeting, where profiling enhances conversion. You can directly measure the uplift of normal users compared to users post cookie deletion.

3. Browser Switching Measurements
Many people now use multiple internet browsers for a variety of reasons, evaluation, different features, old bookmarks and probably most importantly, technical issues. The problem for analysts is that traditional cookies are browser specific, so each browser appears as a different user. Super cookies can quantify this issue. Super cookies provide the capability to keep a cross browser profile that remains even if a user uninstalls a specific browser and switches to a completely new one, but for the purposes of the exercise we are only looking to quantify the issue.

To create this capability the following logic can be used. Again this would be written in JavaScript. 
IF current browser is not equal to superCookie(browser) THEN
{
LOAD GA CODE
set custom variable "browser A > browser B"
SEND GOOGLE REQUEST
set superCookie(browser) = "browser B"
ELSE {
LOAD GA CODE
SEND GOOGLE REQUEST
}

The above logic would enable you to see:

a) Which browsers people are switching from/to. This can help you plan future testing resource allocations, etc.
b) Which pages browser switches are commonly associated with (above logic does not show a direct correlation to a specific page, but you can store the final session page in the super cookie and use that to see if the user has made a browser switch on the same page, which may indicate a browser issue).
c) How many browser switches have occurred (set the variable to be page specific)
d) How many users use multiple browsers (if you keep a common visitor ID across multiple browsers)

Hopefully this article has helped to show you how super cookies can be used to improve your Google Analytics deployment accuracy. For actual code examples, please see our original super cookie post or download the zip file below. For any questions or enquiries, please contact us at insights@datalicious.com

 

 

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Filed under  //   analytics   cookie   custom   google analytics   hamish ogilvy   super cookie   variable  
Posted by Hamish Ogilvy 

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Use Google Analytics custom variables and simple JavaScript to target site content in real-time

I was reading this on another blog earlier today and thought it was worth passing on. In essence Google Analytics have provided a function to read the custom variables for targeting purposes. Although this is essentially nothing more than being able to read a cookie and use it to segment and target page content, it's nice to be able to use the same variables used by Analytics, as the targeting immediately has context in reports.
 
If you already use the custom variables (index 1-5), you can now use the following function to read the value and switch out content using some simple JavaScript.
 
_getVisitorCustomVar()
 
_getVisitorCustomVar(index)
 
Returns the visitor level custom variable assigned for the specified index.
 
pageTracker._getVisitorCustomVar(1); 
 
Parameters
 
Int index The index of the visitor level custom variable.
 
Returns
 
String The value of the visitor level custom variable. Returns undefined if unable to retrieve the variable for the specified index.
 
Read the original blog post from Michael Whitaker here or check out the code reference in Google's help section if you want to find out more.

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Filed under  //   analytics   custom   google analytics   hamish ogilvy   targeting   variable  
Posted by Hamish Ogilvy 

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Free ADMA Data & Analytics Council event with Peter Hanlon, Westpac executive and data evangelist

We're stoked to announce that the ADMA Data & Analytics Council is hosting a free event for data gurus (or marketers that want to become one) next week in Sydney.

Peter Hanlon, current Westpac Group Executive People & Transformation and previously responsible for all retail and business banking (and ongoing Westpac data evangelist) will share his personal experience on the importance of data for boosting marketing careers as well as business optimisation in general and of course there will be time for drinks and networking afterwards as well.

When: Next Wednesday, 26th of May 2010, 6.30-8.00 pm
Where: Westpac Place, 275 Kent Street, Sydney CBD

Please email councils@adma.com.au to register (the event is on the top floor so your name needs to be on the list to get in) and take our short pre-event survey on the current state of data and analytics in Australian direct marketing industry (we'll share the results at the event).

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Filed under  //   adma   analytics   christian bartens   council   data   events   news   peter hanlon   sydney   westpac  

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Tracking unique visitor without cookies by analysing browser configurations with over 84% accuracy

For all of you online analysts out there that are scared of cookie deletion rates, private browsing modes and increasingly restrictive privacy laws, there's hope!

The EFF (Electronic Frontier Foundation) has an interesting project called Panopticlick that determines uniqueness of visitors without cookies by analysing the exact browser configuration of a person (i.e. version, fonts, plug-ins, etc). I just did the Panopticlick online browser uniqueness test and it seems that my browser configuration was unique among the so far tested 993,912 people. Go do the test now and help these guys increase their sample size.

EFF found that 84% of the configuration combinations were unique and identifiable, creating unique and identifiable browser "fingerprints." Browsers with Adobe Flash or Java plug-ins installed were 94% unique and trackable.
 
Of course the whole thing falls down if people use more than one browser or multiple computers and I'm one of these people (I'm actually running Safari, Chrome and Firefox at the same time sometimes which is sad, I know). Anyway, still a great idea if you ask me so check out the actual research paper below if you want to find out more or read the official press release.

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Filed under  //   analytics   christian bartens   cookies   data   eff   panopticlick   privacy   research   unique visitors  

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StickyBits: Tag any barcode with content and improve user experience and campaign tracking

StickyBits is a new service that lets you attach content to any bar code anywhere as long as you have an iPhone or Android. Other users who scan the same bar code can then see your comment or attachment (image, video, audio, etc). 

Try it now! Install the iPhone app and scan the below barcode.
http://itunes.apple.com/au/app/stickybits/id356204501?mt=8
The whole thing is similar to the Google Favourite places service we wrote about earlier but much more flexible. Anybody including businesses can now generate barcodes and attach content to them including special offers or additional information, very powerful! 

Visit the official website below for more information or email us at insights@datalicious.com if you want to find out how your business could us this technology to improve user experience or campaign tracking.

Sign up and start tagging
http://www.stickybits.com/

Generate free bar codes online
http://www.barcoding.com/upc/
http://www.barcodesinc.com/generator/

       
Click here to download:
StickyBits_Tag_Barcode_Everyth.zip (2542 KB)

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Filed under  //   analytics   android   app   barcode   campaign   christian bartens   iphone   offline   online   retail   tools   tracking  

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Tynt: Leveraging the copying and pasting of your website content for search optimisation

Tynt is an interesting piece of technology that deals with people copying text from your web site. The software essentially adds a backlink to the copied text that is also trackable. The result is that when people copy the text, more often that not they will also paste your link.
 
The benefits of this technology are pretty obvious, more back links which increases traffic and aids SEO, as well as additional analytics to help you better understand your site content.
 
The company has a patent pending on the technology and it is apparently already used by thousands of sites. It is free and the total javascript payload is only approximately 12k. Worth a try, particularly for content rich sites ... 
 
For more details, see http://www.tynt.com/
 

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Filed under  //   analytics   copy   hamish ogilvy   link   paste   seo   software   tools   traffic   tynt  
Posted by Hamish Ogilvy 

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Diagram: Integrated campaign flow and simplified metrics framework across multiple channels

How many times have you talked about a truly integrated campaign but lacked a diagram and metrics framework to properly explain and measure the interaction between channels? We recently designed the below campaign flow and simplified metrics framework for one of our clients to explain the interaction between the various different paid and organic channels, websites, social networks, retail outlets and CRM. 
 
Unfortunately we can't share the actual campaign results but the impact was amazing. The traffic levels increased significantly during the campaign and for the first time rivalled historic peaks from previous Christmas periods mid year. However, the integration of the analytics framework into the campaign planning process from the very beginning ensured that tracking best practice was followed and a maximum amount of data could be collected across all channels. Best of all, if the below framework is used across all campaigns they start to become comparable and a benchmark emerges but that requires a lot fo discipline on all sides.
 
But let me explain a little more about our thinking behind the metrics framework. First of all, we renamed the 'awareness' stage to 'reach' because those metrics are a lot less debatable for all channels (i.e. we know how many people search for something or were exposed to a banner but not really how many people actually become aware of a message). As metrics on 'interest' and 'desire' are actually hard to differentiate in the standard AIDA(S) formula we combined them into a single 'engagement' category (i.e. everything after a non-bounce and before an actual conversion). The 'action' metrics category stayed the same, it simply contains all the conversion data on actions we wanted people to take but doesn't have to be limited to sales of course. Finally, 'loyalty' is a hard one to measure at the best of times and pretty fluid so we renamed that stage to '+buzz' which stands for positive buzz or people talking about the company in favourable terms which is of course far from being loyal but we would argue it's easier to measure and one would be pretty hard to achieve without the other.
 
Anyway, what do you think? Please feel free to comment and help us to improve the model and maybe even share some actual metrics you measure at the different stages.

     
Click here to download:
diagram_integrated_campaign_me.zip (219 KB)

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Filed under  //   action   aida   analytics   benchmark   buzz   campaign   christian bartens   data   digital   engagement   flow   framework   integrated   media   metrics   reach   services   traditional  

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WooRank: Free SEO analysis and report

Just came across the below tool which generates some really nice SEO reports outlining what is working well and what could still be improved for each website.

Have a look at our blog report below for a sample, looks like Posterous is doing ok but could still improve some things.

http://www.woorank.com/en/www/blog.datalicious.com

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Filed under  //   analytics   christian bartens   data   ranking   seo   tools  

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