Behavioral Targeting Resources: Ask Anil Batra

A friend of mine and a regular reader of my blog asked me about the resources that are available for someone to learn about Behavioral Targeting. Since I get a lot of questions via emails, I thought that I should answer it via a blog post so that others, who might be interested in the same topic, can benefit from it as well.

With this post I am also officially starting a column called “Ask Anil Batra”. Please send me your question on Web Analytics and Behavioral Targeting and I will try to answer them in my blog posts.

Now back to answering the question. Here is a list of Behavioral Targeting Resources that I know of:

• Media Post’s Behavioral Insider – great articles. I read it regularly
• ClickZ – Behavioral Marketing Articles – Another great resource that I read.
• Behavioral Targeting – Specific Media Site
• How To Target – A Revenue Science Site
• Fishing From Barrel: Only Book on Behavioral Targeting
• My Blog – I write extensively about Behavioral Targeting on this blog

Behavioral Targeting vendors have a lot of information and whitepapers on their own sites. I will do repost in future with a list of vendors and any whitepapers that might be of value. If you are a Behavioral Targeting vendor and would like to be included in this list then please contact me.

If you know of a resource on Behavioral Targeting then please leave me a comment or email it to me and I will add it in my future post.

Got a question on Web Analytics, Optimization or Behavioral Targeting? Send it to me at batraonline (at) gmail.com.

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Google and Behavioral Targeting

Google, so far, has refrained from behavioral targeting. But I think it is about time and it is the logical next action for Google to start offering Behavioral Targeting to its advertisers and publishers. Yahoo and MSN are both testing their Behavioral Targeting capabilities; their Behavioral targeting depends on the user data generated on their own sites. Tacoda and Revenue Science built the concept of network first and then are recruiting publishers to participate in the networks. Google is taking all together a new route. It is busy putting its footprint all over the web. These footprints will help Google build the largest and the best Behavioral targeting Ad network. Google already has publishers (Google Search, Content Network, You Tube) and advertisers (Adwords and PPC). Visitor behavior will come from various Google applications which are everywhere on the web. Google knows more about the user on the web that any other company knows. Google is every where (almost) on the web.
Let’s start from Google Search. Via user’s search keywords and key phrases Google knows what the user searched for, how many times she searched, which sites she visited, how many times and what time of the day she searched. Google might not know the visitors name but knows the visitor via anonymous cookie.
When a visitor arrives at any site from Google search chances are Google will be present there in form of Adsense, Adwords, Google Checkout or Google Analytics.
Even if a visitor by passes the Google search and uses some other way (yahoo search, live search, bookmark, by directly typing in the URL or any other way) chances are she will visit a site which has Google in one or more of above mentioned form.
Google Adsense/Adwords – A visitor who clicks on an Adsense Ad reveals a lot of about her preferences. Just like search Google knows, Google knows which sites (products, offers) the visitor is interested in. How many times the visitors clicks on the ads and what types of ads she clicks on.
Gmail – Google know what emails a user gets, it knows the content of the email, just look at all the ads that show up when you are reading your email. Even if Google does not have the users physical address it knows how to reach her.
Google Checkout – Google knows what a user buys, where she buys from, how often she buys and voila by using Google checkout she just gave Google her name, address etc.
Google Analytics – This is the one of the best tool (as far as behavioral targeting is concerned) Google has put on the web. Not only will it tell Google which sites the user visits, it will also tell Google where she visits them from, what pages she looks at , how long she stays on which site, what she buys, what keeps her engaged and what does not and list goes on.
You Tube, Blogger, New alerts and several other Google products provide will further enhance the data set Google has.
Google Analytics, Google Search and Adsense is where the majority of the data and the power of the network will come from. Aggregated data of all the applications will provide such a rich set of that that within 2 – 3 clicks Google will know weather user is a good prospect for a particular offer, product, service etc. or not.
I think it is a matter of time when Google start connecting the dots and announce it’s entry into Behavioral Targeting. They might call it something else but at the core it will be leveraging the visitors’ behavior all across the web to better target ad on its network.

Follow the Search

Search, as you already know, is attracting a lot of attention from Marketers. People who use search engines to navigate to Web sites far exceed those who type the URL directly into the browser address bar or use bookmarks according to a survey by Piper Jaffrey Investment Research.

Marketers are spending more and more money on Search Engine Optimization (SEO) activities to boost their organic search listings. However, nobody really knows how search engines index various sites and pages in their organic listings. So many times I have seen that a keyword search will show a site’s page (mostly home page) even though that page is very generic and has little to do with the keyword that was searched. The page might have had the content related to that keyword sometime in past or that keyword is still there but there is a lot of other content too, the content that is not really relevant to the keyword that drove the visitors to that page.

Note: Even in Search Engine Marketing efforts, there are a lot of marketers who spend a lot of money buying keywords and then send the visitors who click on their paid listings to a very generic page, most of the time to the home page. Not only are they wasting money on these clicks they are losing an opportunity to convert those visitors into customers. I will cover this in a future article.

A visitor, who types in that keyword and lands on the site, gets confused because he/she does not find what he/she was looking for. Visitors are very impatient, they do not have time to go through all the content on the page to search (yet again) for what they were looking for. As a result visitors immediately bail out causing a very high bounce rate and a lost opportunity for the website owner.

So, as an owner of the site, what do you do?

Simple answer is “Follow the Search” in 5 simple steps. The basic idea of “Follow the Search” is to provide user with a relevant content that will drive them further into your site and hence drive up your conversion. Don’t assume that visitors will find their way because they won’t. Give them an immediate reason to stick around, show them they have arrived at the right site.

Here are simple 5 steps of “Follow the Search”:

1. Capture the search word – As soon as the user lands on your site, capture the keyword user searched on a search engine to get to your site. This can be accomplished by writing a simple code on your page to look for the referring url that drove the visitor to your site. Note: If you have the money then you can also use tool such as Offermatica to do the same.If the referring url contains one of the search engines (you can create your own list of search engines that you want to track but for simplicity I would suggest looking for major search engines and the top search engines driving traffic to your site) then extract the keyword from the referring url. Google, MSN and ASK have the keyword in query string called “q”, while yahoo has the keyword in query string called “p”. Example of the Google referring url is

   http://www.google.com/search?hl=en&q=anil+batra&btnG=Google+Search

2. Build a list of links to the content (or products) that that matches the keyword user searched on the search engine. You can use your on-site search technology or human defined list of content (or products) relevant for your top 50 or 100 (depends on the resources you have) keywords.
3. Use a highly visible area of your home page (or any other page) to display the list that was built in step 2. You can use left side, right side or main content area of the page but make sure it is in the highly visible area of the page, I recommend conduction A/B test to figure out the best location. Use a catchy label such as “Top 10 Resources for [XYZ keyword]” or something similar. Visitors love the top 10 or Top X lists and by tying it with the keyword they searched on the search engine you will make their life so easy that they will not abandon you.
4. When a user arrives from a search engine, capture the keyword (step 1), use the list of content related to that keyword (step 2) and display it to the visitor (step 3).
5. Save the search keyword in session or cookie – Save the search keyword in session or cookie so that you can display the results every time user comes back to the entry page (the page where search engine sent him/her). By saving in cookie you can even show the same results in subsequent visits.

Don’t forget to configure your Web Analytics tool to measure your success – Some of the things you might want to track are

• How many visitors or visits clicked on items in these lists?
• Which links are getting the most clicks?
• What is the conversion rate (whatever your end actions are) by visits (or visitors) who click on these links?
• Change in end action conversion rates
• Change in bounce rates

Here is an example:

Here is a screenshot of http://www.portlandindian.com. This is the page visitors gets when they arrive on PortlandIndian.com. Note, home page above has very little to do with “Roommates”. It has top navigation link and maybe some listings mixed in with classifieds.

When visitors searche on Google for “Portland Indian Roommates”, they get Home Page of PortlandIndian.com as the 1st listing. As I mentioned above this page has very little to do with “Roommates” search keyword that user searched.

However, when the visitors arrives on the site via this keyword, the site follows the above mentioned steps and presents the visitors with the Home page with a section called “Rentals and Roommates” right in the middle of the page.

Questions? Comments?

Presidential Candidates and Behavioral Targeting

I read an interesting article by Michael D Jensen titled “What do the Presidential Candidates use for Analytics?”

One that caught my eye was John McCain, who is using Revenue Science. I don’t think John McCain is using revenue science for web analytics but I think he is using it to participate in Revenue Sciences’ Behavioral Targeting network. Interestingly enough I saw Revenue Science tag on only the home page, other pages did not have any code. Maybe he is still “Undecided” and is testing it out.

Participating in Behavioral Targeting is an interesting concept for Presidential Candidates. In my opinion they can influence a lot of votes by participating in Behavioral Targeting.

Here are some of the ways how the presidential candidates can use Behavioral Targeting (provided they put the tracking code on every single page).

1. Retargeting – If a visitor lands on candidate’s site and then wander over to some other site in Behavioral network, the candidate can advertise to this visitor when they are anywhere on the network. By visiting candidate’s site, the visitor has just shown interest in candiate and so he/she can make sure that this visitor never looses the sight of the candidate(think opposite of out of sight out of mind).
2. Undecided – John McCain has a section called “Undecided”. Any visitor who goes to that section and view 2 or more pages is definitely undecided. Target them with a message (ad) that makes them decide in your favor, this can be used for both on-site and network targeting.
3. Segment Visitors – Segment users based on what content they read or interact with on your site. Using this behavioral understand where they stand in their decision process and then targeting them, on the network or even on-site, with relevant message.
4. Contributions – Say somebody starts a contribution process but never finishes it. Target them with a message that drives them to contribute to your campaign. This can also be done both on-site (after visitor abandon’s the contribution process but still remains on the site) and on-network, follow the user as he/she moves around the network.
5. Use visitor’s off Site Behavior to understand what really makes them tick – If the behavioral targeting network is big enough and have wide variety of sites. Understand which sites visitors visit before they arrive to your site. When they come to your site, show them a message that will align with their off-site (on-network) behavior. Say I care about education and visit sites or blogs (participating in the behavioral network) on education; when I arrive on your site, show me your stance on education. This will help me make my decision.
6. IP Based Targeting – Based on the geo location candidate can
   1. Do more media buy and targeting in the geo locations where they don’t get a lot of traffic from.
   2. Segment user visitor based further and see what the visitors from their top geo locations doing on their site. This will allow you to fine tune the on-site messages.

I am sure more and more presidential will participate in targeting advertising such as Behavioral Targeting.

What do you think? Do you have any more ideas on how they can use Behavioral Targeting? Send those to me.

Interactive Ad Bureau (IAB) Opens D.C. Office and a Lobbyist

Aiming to increase its sway over government, the Interactive Advertising Bureau has opened a Washington, D.C. office and hired its first in-house lobbyist, Mike Zaneis. Source: http://publications.mediapost.com/index.cfm?fuseaction=Articles.san&s=55849&Nid=27638&p=420929

Prior to joining IAB, Zaneis served as executive director of technology and e-commerce at U.S. Chamber of Commerce in Washington.

Zaneis predicts the upcoming Congress will see a number of Internet topics debated on the Hill, including privacy concerns, spyware legislation, data security legislation, and net neutrality.

“Congress is starting to take a look at this and is trying to understand how the Internet really works. And since advertising is the engine that allows the Internet to go, we’re going to have to engage with them and do some education on what our members are doing,” said Zaneis. Source: http://clickz.com/showPage.html?page=3625053

Omniture Acquires Touch Clarity and WebTrends Announces Partner Integration

Yesterday Omniture announced that it will acquire Touch Clarity, a Behavioral Targeting Company. Within few minutes a WebTrends announced partner integrations with leading digital marketing vendors, including email marketing firms ExactTarget, Responsys and Silverpop; on-site behavioral targeting firms Kefta and Touch Clarity; and consumer opinion and customer voice firms ForeSee Results and OpinionLab.

This promoted me to write this article because this is exactly what I predicted.

You can read the fill press release at
• Omniture Acquires Behavioral Targeting Company Touch Clarity
• WebTrends Announces Marketing Lab Partners to Deliver More Measurable, Automated Relationship Marketing

Anybody who read my predictions for 2007 (http://webanalysis.blogspot.com/2007/01/my-predictions-for-2007.html) might have already seen this coming.

Here were my 3 predictions for 2007, and this acquisition proves all 3 of them true. My new comments are in Bold

1. Web Analytics won’t be standing alone – Marketers will want 360 degree view of the customers. Integration of various data sources and tools will be expected from web analytics and other supporting tool vendors. Omniture started the trend with Omniture Genesis, and this will continue, we will see more acquisitions and partnerships similar to Omnitures.

- Both the above press releases confirm that this prediction has come true. Customers are demanding this stronger integration. I wrote a follow-up on this same predictions last week, you can read it here http://webanalysis.blogspot.com/2007/02/follow-up-on-my-web-analytics.html

2. Web Analytics will be about taking actions – More and more marketers would like to take actions and not just report the findings. It just won’t be about what happened, it will be about taking action to drive sales, user satisfaction, lead generation etc. Incentives and bonuses will be tied to the online KPIs. Optimization and Behavioral Targeting will become a common term used by marketers.

- Omniture acquisition of Touch Clarity, a Behavioral Targeting company confirms this prediction has come true too. WebTrends announcing partner integration with Kefta (Optimization and Behavioral Targeting) and Touch Clarity (Behavioral Targeting) confirms that marketers are demanding Optimization and Behavioral Targeting. It is not just about reporting, it is about taking actions. In near future I am expecting to see a lot of case studies about what actions customers took and how it affected their bottom line.

3. Behavioral Targeting – Only few main behavioral network players will be left and some of the existing ones with poor networks will either go out of business or be sold. See my previous article on why size of network matter. Behavioral Targeting won’t exist in isolation. Web Analytics tool will have to support behavioral targeting and visa versa. Also, on-site behavioral targeting will become very common.

- Part of this prediction has come true. I have yet to see any consolidation in behavioral network players. But as the above two press releases confirm “On-Site Behavioral Targeting” is becoming common.

Web Analytics is maturing. Gone are the days when marketers were just satisfied by learning like
“Traffic went up”, “Traffic went down” etc. It is about deeper understanding of the visitors behavior (Web Analytics), segmenting them (Web Analytics and Behavioral Targeting), taking actions based on this deeper understanding e.g. targeting relevant content, products etc. (Email, Behavioral Targeting, Optimization).

So I am 2.5 on my 3 predictions. I have already declared 1 more prediction come true (http://webanalysis.blogspot.com/2007/02/follow-up-on-my-web-analytics_09.html). So for the year I am 3.5/5 so far and the year has just started. I feel good about my predictions.

Questions, Comments???

Targeting Cart Abandonment by Email

Today I read an article called Four Ways to Improve Marketing ROI Through E-mail by John Rizzi, CEO of e-dialog. This is a good article for those who are trying to determine how to collect email, learn from email marking and email effectively. In his last point he says “Use Behavioral Targeting” to convert abandoned carts. He suggests using incentives to bring customers back to complete the cart they had abandoned. This is a great idea but I want you to be aware of following two issues before you jump into it.

1. Lack of Email Address: If you don’t have an upfront email collection process it is very likely that visitors (customers) will leave even before they give you their email address. If that’s the case then you won’t have any email to target (You can still deploy anonymous on-site behavioral targeting. Check out my article on behavioral targeting).
   If you decide to put email collection up front it might cause cart abandonment rate to go up. You have to provide a very good reason to your customers on why they should provide you email even before they started buying anything or checking out. Like any other change on the site, I suggest conducting A/B testing before you start collecting email addresses for all your customers. If the tests do not show desired result you might be better off with on-site anonymous behavioral targeting.
2. Backfiring of incentives: Let’s assume you have the email address and are ready to send an email incentive. As you already know the word spreads very fast these days. Most of your customers (visitors) will find out about your offers which could ultimately result in two outcomes:
   1. If the incentive is not too enticing (such as free shipping) your customers (even regular customers) might find out about it and start abandoning the cart in anticipation of receiving that offer or they might just use the coupon or offer code given to them by somebody on the internet.
   2. If the incentive is too good (such as $10 free for any purchase over $5.00, not sure why would you do that but I have seen companies giving free money just to get users to signup), the word will spread sending new customers to your site. So be prepared to handle the amount of traffic this viral marketing will generate and a possible bankruptcy.
      Appendix A shows what happened to Starbuck when they sent out an e-coupon to limited number of employees (or that’s what Starbucks thought).

So should you provide incentives to bring back customers who have abandoned carts? Yes I think so but think about all the pros and cons before you jump into it. Below are some of the steps that you should include into your process for using email incentives

1. Select a sample (say 20%) of visitors, who abandoned the shopping cart, who will receive any offer (I am assuming you have already created and tested a process for upfront email collection).
2. Test different offers within this selected group. Testing will show you which offer works and which ones don’t.
3. You can use more behavioral data (and I encourage you to do so) to determine what offer will make sense to which visitor segments (create few manageable segments so that you can stay focused). E.g. A customer who abandoned at shipping step might be more interested in free shipping than a user who added products to the cart but then left without clicking on the final checkout button (provided the customer has given you the email address), a 10% off coupon might be a better offer for this customer.
4. Unless you purposely want to engage in viral marketing, make sure coupons and codes can only be used by those for whom they were intended for and for specific period only. Also don’t forget to configure your web analytics tools properly so that you can measure effectiveness of these offers.

Note: If you provide users the same kind of incentives 2-3 times to a customer then he/she (most of them) expects it every time.

Appendix A: Starbucks Lawsuit
“Starbucks e-mailed the grande iced beverage freebie to a limited number of employees in the Southeast on Aug. 23, with instructions to pass it on to friends and family.
The forwarding turned into a frenzy as the coupon landed in thousands of inboxes and on Internet message boards – forcing the chain to reject scores of coupon-touting java lovers pouring into stores for the perk.” Source: ocregister.com

Part II Web Analytics Predictions for 2007- Follow up

In January I wrote my web analytics predictions for 2007. I wrote about the current status of two of my predictions in my previous post

In this post I will cover another of my predictions, prediction number 1:

A Great Career Field– There will be a lot more jobs in this field in 2007. A great year for those who are planning to enter this field or looking to move into better jobs in this field. Most marketing jobs will have web analytics as a requirement. Currently there are 1024 open job on Indeed.com but I expect this number to rise as there will lot more openings than qualified candidates.

Today I checked indeed.com and found that there are 1711 jobs listed under “Web Analytics”. This is a jump of 67% just in a month. I declare that my 1st prediction has also come true. Stay tuned for an update every month.

How about a little prediction game? Send me you prediction on how many jobs there will be on March 1st.

Note: Jan numbers were taken on 7th Jan, Feb numbers were taken on Feb 8th. I plan to take these numbers on 1st of every month.

Follow-up on my Web Analytics Predictions for 2007 Part I

In January I wrote my web analytics predictions for 2007. Two of my predictions were

Web Analytics won’t be standing alone – Marketers will want 360 view of the customers. Integration of various data sources and tools will be expected from web analytics and other supporting tool vendors. Omniture started the trend with Omniture Genesis and this will continue we will see more acquisitions and partnerships similar to Omnitures.
Web Analytics will be about taking actions – More and more marketers would like to take actions and not just report the findings. It just won’t be about what happened, it will be about taking action to drive sales, user satisfaction, lead generation etc. Incentives and bonuses will be tied to the online KPIs. Optimization and Behavioral Targeting will become a common term used by marketers.
Today I read an article Report: Web Analytics Market Pumped for Growth which hits on the same points that I predicted.
Here are two quotes from this article
“Many Web analytics companies started collecting data about Web site visits and providing reporting tools to analyze that data,” Megan Burns, Forrester Research senior analyst told CRM Buyer. “Now they’re moving to the next level of value, which is enabling people to act on that data and becoming a platform for managing interactive marketing activities.” This is exactly what I predicted “ Wen analytics won’t be standing alone and it will be all about taking actions on the data.
Here is another quote from Jason Palmer of WebTrends
“As an application category, Web analytics is evolving beyond data collection and reporting, claimed WebTrends’ Jason Palmer. “Traditionally, Web analytics has been about performance management, tracking Web site behavior and usage,” he said. “Four or five years ago, it began evolving into campaign reporting and most recently, campaign management and optimization.””
It is nice to see the validation by industry experts and leaders. The year has just begun I am sure by end of this year we will see similar quotes from a lot of industry leader and experts. I would like to declare that my prediction number 4 has already come true and number 3 is on its way to become true.

As always, I would love to hear your comments and feedback.

Behavioral Targeting Hack

So you have read about behavioral targeting and want to get started but are concerned about spending the money on a Behavioral Targeting tool. If that’s the case then continue reading. This article will show you how you can easily deploy behavioral targeting capabilities with minor coding on your site and without spending any money on a tool or engaging a Behavioral Targeting vendor.

Below I have outlined the Behavioral Targeting process in simple steps and next I have provided an example. This process is affordable and lets you test the water before you get fully engaged in Behavioral Targeting.

1. Identify the user segment that you want to target e.g. “In market auto buyers” – You can also build a monetization model. Monetization model is not necessary but allows you to prioritize and determine what segments make sense. I am not going to get into details of how to build a monetization model in this article; you can contact me if you need help with building the monetization models.
2. Identify what content views (behaviors) will determine the segments. Eg. Users who have viewed 2 or more pages related to auto loans.
3. Determine what content, message or product you want to show to users who fall in those segments. e.g. A banner ad targeted to this segment.
4. Build a capability in your code to read/write a cookie as user views the content that defines the segment. e.g. Write a cookie every time user views the auto loan related page.
5. Write the unique identifier in the cookie when a user falls in that segment. This identifier will let you know which users fall in which segments. E.g. as soon as user has viewed 2 auto loan related pages, write a cookie (say segmentid)
6. Build a capability in your pages to read a cookie and then serve contents based on the cookie value as users continues to browse the site or comes back for a repeat visit.
7. Create reports in your analytics tool based on segmentid cookie to see the behavior of your users who are in that segment. This helps you better understand your target segments.

Example:

This is an online bank and wants to target those users who are in market to buy a car.

1. I want to target users who are in market for car loan. I will call this segment “In market auto Buyers” and I will give them segment an id of CAR001 (a unique identifier)
2. A user who views at least 2 pages the car loan section or starts a loan process funnel but does not complete it will be identified as the “In Market Auto Buyer”. How did I determine how many pages or what pages will put a user in this segment? I made it up. How you determine what defines a user segment will depend on your particular business and goals.
3. I want to show my target users a banners and links which will prompt them to fill the auto loan application (loan process funnel).
4. We will need 3 cookies, one to keep track of how many pages user has viewed in the determined section (autoloanpgs), the other to keep track of the segment users falls in (if you want to create multiple segments than you can add those to this cookie) (segmendid), and a third one to make sure you do not target a user even if the user falls in the segment (segmentdonotrget). Third cookie ensure that you do not target the user once a user has been targeted and completes the intended action
5. As soon as user views a page in this section,
a. Read the cookie called “segmentdonotrget”, if this cookie has a value of CAR001 do nothing, you do not want to target this customer. You are done.
b. Read the cookie called “segmentid”, if this cookie exists and has value of CAR001 then, you don’t need to track this user any more, this user is already in your target segment. Go to step 6.
c. Read a cookie called “autoloanpgs”, if it exists increment the value by 1 else write the cookie with a value of 1. (The idea is to increment this cookie with a value for each page view within “Auto Loans” section). If the value is 2 or above write the cookie “segmentid” with a value of “CAR001” (Note if you are using multiple segment then you can use the same method but will have to delimit the values by a , or some other character)
6. On every page of the site read “segmentid” cookie and if you target segment “CAR001” exists then serve ads or links to “Auto Loan” to these users.
7. Once the user completes the auto loan process, write the segment id in “segmentdonotrget” so that you do not target this user again.

I have tried my best to explain this process. If anything is not clear then please do write to me and I will make sure to clarify it in this article.