Why Does Google Analytics Report Values That Are So Different Than Ad Servers and Site Analytics Counts?

I had a client call me today and ask, “Why do we need to use an ad server when we have Google Analytics?”  Actually, he was redirecting a client’s question and asking for ammunition, but the question was legitimate.  He wasn’t talking about ad serving per se, but reporting.


 


Google analytics enables an advertiser to measure counts like an ad server and site analytics software and yet the measurements yield very different results.  In fact, the results are always lower, enabling the client to conclude that they must be more accurate.


 


Hold the phones!  Wasn’t it just like up to four months ago that Google was guilty of 20-30% click fraud rates with its Adwords program?  Advertisers started complaining and dollars started shifting away from Google and towards MSN and Yahoo!.  When Marketing Pilgram broke the story in December 2006 the word “Click Fraud” was changed to “Invalid Clicks” and Google demonstrated that they had miraculously instituted a change that resulted in the double-digit error rates dropping to less than 2%.


 


So why are we trusting Google’s counts?  It would seem that Google has simply put some major filtering in place to cover their asses so that Advertisers aren’t getting overcharged any longer.  And now they are the more accurate source of counts? 


 


In the end, however, what Google counts and what the rest of the industry counts when it comes to banner advertising and site-side traffic has to be inherently different.  Just as it is with click-traffic.


 


According to Google: “Different web analytics products may use a variety of methods to track visits to your web site. Therefore, it is normal to see discrepancies between reports created by various products. However, we generally believe that the best way to think of metrics across different web analytics programs is to think in terms of trends, as opposed to numbers by themselves.”


 


Google presents that their tracking methods can introduce a difference in reporting values: Cookie-based tracking vs. IP + User Agent tracking.


 


Cookie-based tracking relies on a browser setting the cookie. If cookies are disabled, cookie-based analytics programs (such as Google Analytics) will not count the visit.


 


IP + User Agent tracking typically uses log file analysis for its data. Ad servers rely on this methodology. 


 


Another discrepancy that Google talks about is a resultant of first party vs. third party cookies.  “Because 3rd party cookies are set by a source other than the website being visited, they’re often blocked by browsers and security software. Google Analytics uses 1st party cookies.” 


 


Ad servers use third party cookies and therefore these may be getting blocked by Google Analytics.  That would represent a huge discrepancy between the ad server counts and the Google counts.


 


So Google and ad server and site analytics do it differently.  That makes sense.  Now back to my client’s question.  Why would you use an ad server when you have Google Analytics? 


 


For one thing, Google limits a site visit per user to one time every 30 minutes.  Ad servers, by comparison, would not filter such behavior, but would recognize the fact it is a unique visitor (using a cookie) coming to the page more than once.  So impressions would be counted separately from unique impressions.  Google would simply filter the multiple impressions out and give the unique impression.


 


My suggestion to my client was to convince their client to deploy a site analytics toolset so that there would be two third-party validations in place to offset Google.  People don’t seem to get the idea that even Google is proposing that “…the best way to think of metrics across different web analytics programs is to think in terms of trends.”  Especially when it comes to Google.  You get what you pay for … and you don’t pay for Google analytics.


 


Here is something else that we discussed.  If you synchronize your ad server and your site analytics you will get accurate – or actually identical counts.  For example, deploy a DirectServe™ Technology using First Party ad serving with a WebSideStory first party cookie and you will have a seamless pass through of data.  Impressions and clicks will go through to the site and the site will read the ad serving data – actually WWS will receive the data using the first party cookie – and the reporting will match up perfectly. 


 


Remember, DirectServe™ is a patent-pending capability of TruEffect and we are partnered with WebSideStory to implement this kind of solution so that was a plug.  But seriously if you want to put together the pieces this is how to do it.


 


The client also asked about bid optimization.  Hmm, another variable.  Love it.  Well WSS has Bid Opp and so that can easily be brought into the picture as well.  Using a first party cookie, the ad server can lay the cookie down on the user when they click on the keyword and associate the keyword and search engine with that user.  If that user is already carrying the cookie from the client, the ad server can add to the cookie the search variables that regenerated the visit.  Then the site analytics software can receive the data using the first party cookie.  Done.


 


Re-targeting is a wonderfully versatile capability.  My favorite part of the conversation was when he said, “oh…we’re already testing targeting with TACODA.”  Love it.  Obviously we discussed the event-based targeting aspects of TACODA and how it is based on anonymous occurrences.  He agreed that while the solution works well it is limited to their network and does not have the ability to leverage client data like what DirectServe™ has to offer – site agnostic, web-wide capacity that leverages client knowledge about customers for re-targeting.  He got it and agreed that we were talking about complimentary solutions … for now.


 


Anyway, back to Google.  I think it is key to understand that ad serving has all of its benefits from the perspective of campaign management.  And site analytics has all of its benefits from web site trafficking, modeling and analysis.  But what was at conflict here was ignorance of a client’s client.  If a client is going to use Google, they need to be educated as to why they are using and what they are using it for.  It’s kind of like using fuzzy glasses to read a book.  Or a better example is using your hand to feel your kid’s forehead to see if they have a fever.  It is a trending tool that gives you a relative indication, not an exact measurement. 


 


Google Analytics is great for the advertiser who wants to log in at 3am and see what’s happening.  I do that sometimes with my blog when I write a particularly contentious article – just to see if it’s triggered some reactions.  But my server logs are far more accurate than Google Analytics.  The counts are always 30%+ off.  Same with ad server reports and site analytics. 


 


Educate your client with the tools that are going to demonstrate real accuracy.  Use sales reports and revenue reports – post-click analysis – to demonstrate further discrepancies that translate into real value to the client.  It is possible to show the client where the diversion points in the direction of the ad server and site analytics favor.  Go the extra step and you will prevail.  If you have more than one client that will bring this up, prepare a document that you can use over and over again.  This problem is not going away soon.


 


Reactionary with Insight.

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Gaining Ground with Behavioral Targeting: Mediaplex tells (Almost) All

So I have received a lot of email and even a couple of phone calls regarding yesterday’s article by Mediaplex’s Sean Quick in iMediaConnection.  How could I let an article on Gaining Ground with Behavioral Targeting go by without so much as a comment, when so much of my blog addresses this topic with such conviction?  Well, yesterday was my birthday so I was out having a much needed break!  But I’ll have at it now!


 


Okay, first of all I have to start off by saying that Sean did a good job of breaking up BT into two distinct categories – passive and active.  He used these descriptions to help us understand the difference between the classic event-based targeting capabilities of a TACODA and the re-targeting capabilities that I have been evangelizing on this blog.  I was so pleased to see Sean use the term customer re-targeting as well, since it was not an industry term when I first started this blog and my Urchin reports show Mediaplex on my blog everyday.  I take Sean’s usage of the term as a compliment J.


 


Recently I posted When to Blog and When to Publish, commenting on what I believe to be the hairline-thick line between what is informational and what is self-promotional publishing online.  I issued a request for feedback as to whether I should be blogging or publishing and if there are topics on my blog suitable for publishing, should you believe I should be publishing.  I was contacted by Brad Berens at iMediaConnection who suggested that I could follow the thought leadership track when writing for iMediaConnaction (with their help) and that my self-promotion and subjective style could be reserved for the blog.  Works for me!  Anyway, stay tuned as you may see some writing show up out there as well…


 


Anyway, back to Sean’s article.  While Sean does specifically highlight ValueClick’s Mediaplex as the provider of re-targeting, he also mentioned DoubleClick and Advertising.com.  So I don’t fault him for direct self-promotion.  But what I do believe Sean fails to do is accurately depicting customer re-targeting as it has come to be defined. 


 


If anything I believe that what Sean has done is introduced a third form of behavioral targeting: (1) passive, (2) active event-based and (3) active segment-based.


 


Passive BT goes back to the event-based targeting that I have already discussed in many postings.  Sean describes it as follows:


 


Passive BT — also sometimes called Targeted Segments and other names — is generally done either through applications that reside on a user’s computer, such as downloaded software, or through tracking tags that reside on publishers’ websites.  In either case, these technologies anonymously record consumer web browsing activity.  The consumer is unaware that such tracking is occurring, as it doesn’t affect their surfing activity in any noticeable way.


 


The tracking information is collected and analyzed, and the cornerstone of this approach is the subsequent attempt to make increasingly educated guesses about a consumer’s interests based on the data in order to deliver timely and relevant marketing communications.


 


Examples of providers of this approach include Tacoda, Revenue Science and Claria.


 


The Active BT that Sean describes is “also called User Retargeting [and] consists of anonymously registering consumers’ proactive, direct interaction with a company’s marketing efforts. For example, display or email advertisements or material on the client’s website and then implementing follow-up marketing programs that address that explicitly expressed interest in an attempt to deepen the relationship and lead to conversion.”


 


So this is still event-based.  A better description is Event-Based Active BT.  The information leveraged for re-targeting is based on other marketing experiences.  Sean does not describe the application of this BT specifically in terms of online advertising, nor does he describe it in terms of preventing the re-prospecting of customers through online advertising.  In fact, what he is doing is explaining that Event-Based Active BT can coordinate disparate forms of online marketing to collectively create a concrete BT model.  Moreover, and what is entirely left out of this article is the PROCESS.


 


One thing that I am so careful to do in all of my postings – and what I believe will be a focus of articles that I would write for IMC – is to illuminate the procedural differences between various kinds of technologies so that people can come to distinguish them.  It is important to understand the impact of a first party design and a third party design for example.  The benefits and differences of these kinds of technologies transcend the advertising experience for both the advertiser and user – in fact for the publisher too. 


 


TruEffect holds the patent-pending rights to first party ad serving.  So if another ad server were to implement a first party design, they would violate that patent and would be putting their clients in a nefarious situation that would result in problems down the road.  Aside from that, other ad servers are not doing it that way anyway right now.  They have their own design using a third party cookie and a synchronization process.  They still have their ‘control the data and you own the client’ model.


 


Listen, Sean is not going to talk to me about it, obviously.  But maybe he will talk to you and then you can come back and talk to all of us on the blog.  OR, maybe Sean would like to come on here and have a discussion with all of us.  It would be great to bring the truth out.


 


If Mediaplex is using a third party cookie to conduct user re-targeting, it is historically synchronizing.  Latency comes into play and there are limitations to the benefits that only a real-time capability can bring to the table.  Only a first party cookie foundation is capable of doing it in real-time. 


 


If Mediaplex is having clients share record information so that Mediaplex can assign cookie values to people when they transact or otherwise experience a marketing event, it is still a third party cookie, foreign to the advertiser and so the limitations include:


 



  1. The ad serving data is mediaplex’s data, accessible only by mediaplex;
  2. The cookie information is not accessible by the advertiser;
  3. The ad serving information is not readily integratable with other technologies such as site-side analytics which may be another third party cookie (omniture) or could be a first party cookie (WebSideStory or Webtrends); and
  4. Mediaplex can not adjust targeting strategies in real-time, targets must be determined in advanced.


As we have covered in many entries on this blog.  First party ad serving, using a first party cookie, allows all of the four aforementioned limitations to be mitigated.  Most of all, targeting can happen in real-time.  An advertiser can change a cookie value, login to the ad server and change the targeting reaction to the cookie; and the change is instantaneous. 


 


With a third-party implementation, the advertiser has have to share the altered customer information with the ad server (Mediaplex, DoubleClick) and then the ad server has to start writing new cookies, which have to propagate, and then the ad targeting can begin.  Can you say latency?


 


Two other limitation issues: (1) SOX and (2) third party cookie deletion.


 


When a third party is handling your data, and you have SOX compliance issues, you have a potential problem.  Using a third-party cookie and a third party ad server, deploying event-based Active BT, means your data about your customers is being shared with a third party who is subsequently developing additional information about your customers and gate-keeping your access to that data.  You need to make sure that you have controls written about the handling of that data because it is out of your control.  This is not an issue with first party ad serving because all of your ad serving data flows directly through to the advertiser and is not withheld by the ad server.


 


Secondly, third party cookies get deleted over 40% of the time – Jupiter Research.  So only 60% of the Event-Based Active BT will be effective whereas over 90% of first party cookies are persistent.  Do the math and you will realize that leveraging a first party cookie will bring a much higher yield in re-targeting activities.


 


So Sean’s article stimulates the interest and probably results in some genuine leads to Mediaplex, but I wonder how far down the path you will get with Mediaplex before you come to realize that you have not come to engage with customer re-targeting but more event-based BT?


 


The third form of BT that I characterized earlier is Active Customer Re-targeting.  The fundamental distinguishing difference is that the advertiser is creating customer segments and is cookieing their customers directly, as opposed to the ad server cooking the customer.  Advertisers may cookie their customers through eCRM, eCommerce cycles, email processes, site-side analytic platforms (i.e., WebSideStory), landing pages (i.e., CoreMetrics) all using their own first party cookie.  They can create customer segment profiles that associate a user with a customer type, just like they do offline with direct mail, cataloging and telemarketing and then deploy customer re-targeting with their online advertising.


 


So Sean, it would be very interesting to have a follow-up article with which we hear how Mediaplex, and if you’re so inclined to research your other examples – Advertising.com and DoubleClick – conduct the Event-Based Active User Re-targeting.  But that might not be on your agenda.  Hey Brad, maybe I’ll write that article for you!


 


Reactionary with Insight.

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3 Steps to Customized Landing Pages, and 3 More to Holistic Online Marketing Integration

3 Steps to Customized Landing Pages, and 3 More to Holistic Online Marketing Integration


 


So this was funny.  Very often I will go into iMediaConnection and read an article without paying attention to the author first.  I do this intentionally so that I don’t have a bias to the topic or position but rather allow myself to take the reactionary approach as objectively as possible.


 


Jamie Roche’s piece in today’s iMediaConnection, 3 Steps to Customized Landing Pages was a great example.  Jamie describes: “…how to customize your website pages so that even when making a keyword buy of thousands, you still maximize conversions.”  He does this by presenting a three-step process:


 


Step 1: Look at keyword groups by intention


Step 2: Break out landing pages types and create templates


Step 3: Test templates for general effectiveness


 


Jamie does a great job of presenting how to leverage landing pages to increase conversion potential following search marketing campaigns.  As I was reading his article, I was thinking to myself, what technologies would help to accomplish these tasks?  What can people use to manage their dynamic content-serving on landing pages, what tokens could be placed on browsers at the time of the search-term click-thru to associate the keyword group with a landing page topic?  What site-side analytics software could track and report the metrics to evidence the performance.  What cookie-related perspective would promote the ability to integrate with other forms of e-marketing media?


 


As I was reading, I was thinking about Offermatica.  Figures that would be the case, Offermatica is perfect for dynamic landing-page creation, content testing and doing just what Jamie was talking about.  So after I read the article, and went to see who the author was I start to laugh out loud because of course I know that Jamie Roche is the President of Offermatica!


 


So let’s talk about how the picture can be put together.


 


Offermatica is a great solution for doing everything Jamie describes – it’s actually an eloquent pitch and not too bias if you want to read the article.  But it really represents a piece of the bigger puzzle that we try to explore today.  Holistic online marketing aims to couple the outside advertising with the site-side advertising.  Offermatica is the site-side solution.  Once someone arrives at your site, Offermatica will help you put the right offer in front of the right person based on how you go them there.  Perfect! 


 


So how do you provide a solution like Offermatica with the information that they require to make the best decisions that they can?


 


The out-of-the-box solution (sort of) is to provide Offermatica with the selection criteria for testing various landing pages so that they can be rapid testing on-the-fly as your campaigns are running.  On a performance basis, you can improve acquisition rates by leveraging landing page selections over time.  But how do you hook-in the information so that you are producing the landing pages?


 


Jamie uses search campaigns as his example.  What is unclear is how to determine the landing page content.  Presumably it’s not on the fly.  He suggests creating buckets of search term groups and then creating landing pages that correlate to those groups, probably multiple pages for each group for A/B testing. 


 


But how about banner advertising.  Also possible.  The topic or creative group association of an ad can be passed through in the click-thru URL the same way and all of this can be accomplished as well.


 


Okay, next step…how do we leverage advancing technologies and push site-side content rendering to the next level. 


 


But what about dynamic pages that are reacting to the search campaign?


 


Why can’t we leverage knowledge about previously viewed ads and the search campaign to better select landing pages?  If the search term is captured in the click-thru URL and passed through to the advertiser, and knowledge about banner campaigns can be captured by cookies leveraged during the ad serving process, they should each be able to be incorporated into the rendering of a landing page.  Product selection and content placement can be that much more targeted, and accurate.  Not only can you line up the product placement based on the search term that a person used to get to the advertiser’s site, but you can also leverage knowledge about ads and offers that individual has seen with respect to products and offers.  Ads they may have reacted to in the past as well as ads that they have not reacted to.


 


Offermatica can be leveraged to read the cookie in the browser as they arrive to the advertiser’s web page and react to the information stored in their browser.  More valuable than the click-thru URL of the landing page, the cookie can instruct Offermatica on how to create the landing page too.  Simultaneously the cookie can also share information with the advertiser’s eCRM system and site-side analytics system.  We’ve been through this before.


 


First party cookies are obviously the way to go here.  So if you talk to Jamie and his team and suggest that he accept a first party cookie – say the advertiser’s cookie, or the Offermatica cookie, then he can leverage information in that cookie to make even better decisions for you.  Of course you can get in touch with me through Trueffect if you want me to better explain how TruEffect and Offermatica do this.  Anyway, the first party cookie can pass through information about the banner campaign, search campaign – oooh – even an email marketing campaign.  That’s right, holistic integration of the advertiser’s online marketing effort.


 


Landing pages can be rendered on the fly based on how someone became a lead as well as how they did not become a lead – what ads and search terms generated a response (whether they came through a banner or a search click) as well as what ads did not generate a response.


 


Now, when that person becomes a customer, registrant or other “known” member of your database, DirectServe™ can kick in.  Now that person can be segmented for future re-targeting through all of the same channels using that initial first party cookie. 


 


If the individual conducts a subsequent search, they will be identified upon the click-thru and the knowledge about that user will be passed through to Offermatic, who can render an appropriate landing page that is customer-specific.  Offermatica can further test landing pages that are designed for returning customers.  The eCRM system will capture recurring sales information about returning customers.  And the site-side analytics software – say WebSideStory – will capture the entire cycle as it goes around and around: from search term to sale and from banner ad to sale, over and over, in it’s reports.


 


Reactionary with Insight. 

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Post-Search Data and Banner Advertising


Phil Leggiere interviewed Right Media’s director of Product Management, Alex Hooshmand and published the interview in the January 31st 2007 edition of MediaPost’s Behavioral Insider. 


 


At the end of the interview, Phil asked about the new frontier of Behavioral Targeting, what is coming next.  Hooshmand’s response, “we now have several clients who are using post-search behavior to target banner or display ads.”  Let’s get into that.


 


So what are the options?


 


Obviously RightMedia has some offering within their exchange network although I have not been able to find anything more than that.  Plus as a hermetically sealed network you are limited to being a buyer or seller within that auction environment.  Works great for direct response, low-dollar advertisers and publishers with remnant inventory but not for the rest of the market.


 


One options is Post-search advertising.  AlmondNet delivers post-search paid-listings to users based on previous search behavior across its distributed ad network.  If a user searches on an item through conventional search, their search behavior is cookied and tracked.  When they are encountered in the future they are targeted with relevant paid listings.  This is a lot like behavioral targeting only with paid listings and with search instead of pixel-associated events.


 


MSN’s new AdCenter offers an advertiser the opportunity to target their search advertising by demographics, geography, day-part and several other parameters.  So they are using browser-based cookies to single-out users for targeting.  Crossing the chasm to then offer an advertiser the opportunity to subsequently advertise a banner ad to someone based on search response behavior would not be a hard leap to make.  But that is my supposition and is not something that has been publicly been brought to market.  But it will I am guessing.


 


Then of course there is my favorite, the creative approach that the early adopters are deploying.  Search advertising with First Party cookie ad serving. 


 


Advertisers that manage healthy search campaigns will usually employ the services of an ad server to track their campaigns – leveraging unique click-thru URLs and landing pages to track each keyword.  This approach enables the advertiser to measure the effectiveness of every keyword.  While the search engines may provide impression data on the keywords through their reports, and clicks, the ad servers can provide successful clicks and then post-click events (what happens after someone clicks on the keyword and enters the advertiser’s site) when the advertiser’s site is properly tagged with tracking pixels.


 


One of the benefits of using an ad server is to have the comparative reporting between a search engine’s reported clicks and actual clicks.  Up until recently, Google reportedly had a click-fraud rate of approx 12%.  Now it is 2% with the invention of something they refer to as “invalid clicks” making up the other 10%.  Invalid clicks are screened out clicks that you no longer have to pay for.  So they are making good on the evident occurrence of people clicking on multiple links before pages load, “stopped” browsers, spiders and bots, failed page loads and other behaviors that result in “fraud” click counts but unsuccessful events.  Whereas, the ad server counts the click as resulting in someone landing on the advertiser’s web page.


 


But back to the integration of search and banner advertising.  When using an ad server to manage search campaigns, a user receives a cookie when they click-thru to the advertiser’s web site.  I know I have gone though this before so my readers should have this down.  But the basics are as follows:


 


The cookie is placed on the browser so that they can be tracked through to the advertiser’s web page and the activity can be credited back to the keyword and search engine.  As this user continues to surf the web they can be recognized and targeted based on that cookie with banner ads. 


 


If it is a third-party cookie, it is event-based targeting.  TACODA, Advertising.com are network examples and Boomerang are ad server examples that can apply this technology and can target a user based on their search behavior.


 


If it is a first party ad serving implementation – DirectServe – then the cookie that is applied is the advertiser’s cookie.  The behavioral targeting features still apply insomuch that if all they do is visit the site, they can be targeted with future ads just like with the example described above for third party providers. 


 


But with first party implementations, the user can also be targeted based on advertiser knowledge generated from the site visit.  For example, if the user clicked on the search term and registered for information, purchased a product or applied for a loan then they are in the CRM system and are a known individual that can be included in a customer segment.  Customer segments can be targeted with DirectServe, first party ad serving. 


 


A user who clicks on a search term and visits the advertiser’s site; and who then completes some level of activity that results in their identification will get a first party cookie.  This individual can then be re-targeted with ads anywhere across the internet at anytime as a customer or registrant.  They can be up-sold, cross-sold or otherwise targeted as an anonymous member of a customer segment (brand preference, purchase frequency, buying habits, etc.).


 


Post-search behavior can be used to create the customer segments when the users arrive for the first time.  For example, the segment examples can further be dissected to include keyword groups so that when targeted, the advertisements appeal to keyword groups that initially generated the user’s response.  Once the user returns to the web page – just like when they first arrived at the site – a content management system can leverage the actual keyword to customize content delivery and properly display product information to maximize revenue or other desired response.


 


I’d love to hear from you on this.  This can be done a number of ways.  But the easiest that I have come across so far is to integrate the three – search, behavioral targeting and DirectServe/first party ad serving. 


 


As I have described in the past DirectServe has three phases of implementation: (1) re-targeting, (2) cookie-writing and data delivery for analytics and (3) integration – CRM, Content Management and Site-Side Analytics.  But for the purpose of this post and this example, I am really only focusing on re-targeting.  That is as far as you need to go and you will already be way ahead of the curve.


 


What else can you do?


 


If you integrate your search with your ad serving, leveraging post-search capabilities to drive your behavioral targeting (prospecting) and customer re-targeting (DirectServe), you will generate data that you can analyze about customers that will enable you to better understand not just what search terms generate leads but what search terms generate customers, customer segment groups, customer values, repeat custom actions and long-term metrics.  Grouping keywords together will help you determine long-term effectiveness of search campaigns.  Furthermore, by integrating post-search with banner advertising, you will be able to recognize how search and banner messages combine to effective solidify messages and have the same impact that can be measured with the same metrics described above.  You can go hog wild!  But most importantly you can measure and determine how to better allocate media spend.  If search works for you, you will know why and how.  You will come to recognize how to compliment it with banner advertising. 


 


Last thing.  When you use first party ad serving, the cookie that you tag a browser with helps you to measure advertising audience.  This means that when you advertise on Yahoo and you buy 1 M impressions, you will know exactly what % of that audience is comprised of existing customers and what % of that audience is comprised of people who have not been to your site before (or who have recently cleared out their cookie file). 


 


What about search?  The same holds true.  Any of your customers who carry your first party cookie will also be measurable.  If someone searches on a term and clicks through to your web site, and they are an existing customer already, they will be measured as an existing customer (their customer segment type will be measured) and you will know what % of the search audience you capture is already comprised of existing customers.  Interesting tidbit.  How much money do you spend with search recapturing recurring revenue?


 


Reactionary with Insight.

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Re-Targeting, There’s More Than One Tactic Indeed

So Tom Hespos – who’s writing I enjoy – has contributed an article in iMediaconnection on why using an ad server to re-target customers can be more effective than say a TACODA or Advertising.com.  Tom’s been reading my blog (and I read his) and has been paying attention to the idea that there is a better way to recognize, distinguish and message to a known audience of users online than to use event-based targeting.  Like me, I don’t think Tom is discrediting the network targeting model but rather differentiating the idea of customer re-targeting from prospect behavioral targeting.


 


Tom discussed in his Re-Targeting, There’s More Than 1 Tactic “Prior site visitors can be bucketed according to what they’ve done (or haven’t done, for that matter) on an advertiser’s website. Now it’s easy to distinguish between the casual visitor, loyal purchaser and occasional buyer, using some simple logic rules.”  But his example of choice is DoubleClick.  I am all for DC’s Boomerang technology and think it is great for event-based targeting.  But again it is not leveraging customer knowledge.


 


“The ad server allows for segmentation based on which action tags have fired.”  Tom is suggesting that the tactic to use is an ad serving solution that relies on pixels placed on web pages that fire when someone lands on certain pages and cookies that user to associate them with that event.


 


This methodology is very effective, don’t get me wrong.  It is a proven tactic for getting a message in front of someone who is going to be better positioned to receive that message based on events that correlate to that message.  But it has little to do with what you know about that user as a customer.  If the pages viewed are customer-specific (i.e., within a purchasing environment) than yes you have cookied them as customers.  But what about customer attributes in your CRM system?


 


You could go one step further … Tom doesn’t talk about this – but of course he was limited to 700 words – but you can share customer profiles with DC and have them correlate customized cookies for you.  Most people don’t but you can.  DC can write cookies to your customer’s browser so that they can actually recognize someone and re-target them based on attributes you have defined but they are static. 


 


So you can say, anyone who lands on thank you page A will get cookie A, and that is high value customer.  Anyone who lands on landing page B will get cookie B, and that is frequent shopper.  And so on.  So there is more than 1 tactic.  Tom is right.


 


But there are limitations.  First of all, you are limited to targeting based on a third party cookie.  This is actually a HUGE limitation.  Jupiter Research said in 2006 that over 43% of third party cookies get deleted within 30 days by either anit-spyware, adware or browser settings.  So less than 60% of the customers will never get re-targeted using the DC cookie.  If it were a first party cookie – the advertiser’s cookie – it would persist far more frequently as it would not be on the blacklists of the anti-spyware companies and would pass the browser blocking settings.


 


Secondly, a using a DC setup like Tom has suggested means that any data written to the cookie through the ad serving process is maintained by DC.  So all the ads displayed and site combinations are reported by DC.  Access to the data is gate-kept by DC.  This is a re-targeting only process.


 


With first party ad serving – DirectServe alternative – all of the ad serving data passes through back to the advertiser.  The ad server can not gate-keep the acquisition marketing data and prevent the advertiser from controlling their own data.  Gaining an understanding of how someone becomes a lead or customer or how an existing customer returns is part of the re-targeting program.  The event-based tactic that Tom talks about in his article is not possible, or not made available I should say by DC.  Food for thought, who controls or who owns your data when you work with DoubleClick?


 


So I agree with Tom, there is more than 1 tactic out there.  You can use TACODA, Advertising.com Dotomi and others for event-based prospecting.  You can use DoubleClick Boomerang for customer re-targeting which is also still event-based.  You can even step it up and have custom data written into the cookie.  But as Tom suggested, get strategic, “…you might want to look at other actions that can define the ways in which a site visitor can interact with your brand.”  If you have customer knowledge stored in a database (CRM), leverage it.  If you are writing cookies based on customer behaviors than target it with first party ad serving.  If you are using site analytic software to track site-side behavior, use a first party cookie so that you can integrate the anonymous behavioral patterns with your CRM profiles.  Then you can integrate your ad serving data too.  Check out Web Analytics and Ad Serving – Proto-Analytics for 2007 for more on that topic.


 


Anyway, there is more than one way to skin a cat.  But first figure out what you want to end up with when it’s skinned.  Re-targeting opens up doors for you to do a great deal.  You can offer existing customers opportunities to continue to do business with you based on recent activities (event-based behavior) or you can communicate to them based on a more complex model (CRM profiles).  You can learn from how them respond to re-targeting by integrating ad serving data with site-side analytics (first party cookies) and you can develop CRM profiles based on first party cookie data to enhance customer segments for future ad serving targeting (DirectServe).  The cycle opportunities are significant.  It all depends on how deep you want to go down the rabbit hole!


 


Reactionary with Insight.

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