Ad Targeting on Gmail appears to be using more than just Gmail data

There has been a lot of speculation about how Google will use all the data that it collects about visitors to its various services. Last year I blogged about how Google can use data it collects on Gmail, Google Search, Adsense, Adwords, Google Analytics etc. to do Behavioral Targeting and then continued with few more posts on Google and Behavioral Targeting. Google was first denying the whole notion of it getting into Behavioral Targeting but last year they introduced Personalized Search using Web History and then introduced in-session targeting on their Search Engine Result Page (SERP).

Now, it’s Gmail’s turn.

Users of Gmail are used to seeing text ads on the side and top of their Gmail mailbox. These text ads are based on the content of the email that a user is reading or gets. I was surprised when I recently saw an ad that was neither relevant to the emails I get nor relevant to my Gmail profile. It was however relevant to some of the search made in past by me on Google and relevant to me (maybe), which Google could have guessed from my name (maybe).

The ad I saw was from a Travel Company that specializes in tickets to India, and interestingly the ad was in my native language “Hindi”. Yes that’s right, the ad was in “Hindi”. My Gmail account, on which I got this ad, is for my semi-business use and never get any personal emails other than from my wife, who uses SeattleIndian.com email address. But I have never got an email in “Hindi” in this account. My conclusion is that Google pulled my name, Web history from Google Account (that includes Google Searches, none of which resulted in me viewing “Hindi” pages) and SeattleIndian.com email address to conclude that I might be interested in an ad from an Indian Travel Agency. None of my searches or my emails will indicate that I know Hindi so it was purely a speculation by the Google Advertiser or Google to think that I knew Hindi.

Here is the ad that I saw

Have you seen something similar? Comments? Questions?

Do-Not-Track List: An attempt to kill Behavioral Targeting

An article in AdAge reports that Privacy Groups Propose Do-Not-Track List.

According to the article:

“Demands of these groups would Hinder Marketers’ Behavioral-Targeting Practices Online.

Privacy advocates are expected to propose the creation of a do-not-track list, a sort of internet version of the Do Not Call Registry, at a news conference tomorrow.

In addition to the list, the proposal calls for a requirement that advertisers, as part of their online ads, instantaneously disclose details of what they intend to track. According to a media alert announcing the news conference, the groups behind the proposal include the Center for Democracy and Technology, Consumer Action, Consumer Federation of America and the Electronic Frontier Foundation, among others.

…Typically, advertisers and online media sellers use web cookies to track and maintain information about online consumers. A cookie might be used to figure out what’s in a user’s shopping cart on a retail website or to record a user’s login for a particular site so that user doesn’t have to re-enter a login name and password every time they revisit the site. Cookies can also be used to track surfing behavior and offer up ads based on a user’s surfing history.

Thanks to such behavioral-targeting technology, a user looking at a specific type of auto on a car-review site, for example, could be targeted with an ad for that particular make and model even when they move onto a general-interest site. Behavioral targeting tends to create more valuable inventory and be more effective, according to many advertisers and publishers familiar with the technology.

…However, consumer-privacy advocates charge that collecting such information in order to target ads creates “a privacy imbalance that has deprived Americans of the right to control their personal information.”

So my questions to these groups are:

1. If consumer don’t like the irrelevant ads but still prefer free ad-supported content to paid ad-free content, how are these groups going to provide that?
2. How are they going to create Do Not Target list without (Personally Identifiable Information) PII information?
   1. One solution is used by NAI, that is to drop a cookie to indicate that user should not be tracked. But if a user deletes NAI cookie then the user is back in “Do-Track” list since most of the targeting solutions are “Opt-Out’ systems (user is opted-in by default).
   2. Another solution is to create a universal cookie that might be able to get by without any PII information but who is going to maintain that? Google? Microsoft? Yahoo?(Just Kidding)
3. Is anonymous tracking really a privacy concern? Do consumers really care about Privacy? Or is this mostly a concern of these groups? Anonymous cookie tracking is still better than what these users provide online to the social networking sites. Look at facebook.com, myspace.com where users voluntarily provide information everyday about their whereabouts, likes, dislikes, friends etc.

In my previous posts concerning privacy I proposed that Behavioral Targeting should be “Opt-In” instead of “Opt-out”, let the users make a call if they would like to be tracked to see more relevant ads.

Here is what wrote
“I believe that if consumers are provided proper education (I will write about consumer benefits in one of my future posts) than they can in fact benefit from Behavioral Targeting. It will be a win-win situation for all the parties involved. Proper education and disclosures by advertisers, publishers and networks will ease the concerns regarding Behavioral Targeting. Consumers have the right to opt out of Behavioral Targeting but what is lacking is proper education on how to do so. The networks currently opt-in users by default; however, in my opinion the proper process should be opt-out by default and opt-in if user chooses to opt-in, just like we do for emails and newsletters. This process will move the burden from users to the advertisers, publishers and networks.

In short run this could result in a lower reach for BT providers. But if the benefits to consumers are properly stated then most of the consumers will be willing to participate. If you (network or advertiser) tell a consumer that he/she does not need to go looking for deals or offers of products/services that he/she is in the market for, these deals/offers will be provided to him/her based on her online behavior no matter where in the network she is in, I think consumer will love it. If a consumer knows the process and she knows that she is willingly participating in the BT, the click-through rate on the ads will be higher too. Why force users into Behavioral Targeting and raise privacy concerns when you can offer them what they want (when they want) and make them your raving fans.”

Originally posted at http://webanalysis.blogspot.com/2007/10/do-not-track-list-attempt-to-kill.html

My Predictions for 2007

So what is year 2007 going to look like for Web Analytics? Here are my predictions for 2007

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.
2. Lot more new writers – There will a lot more bloggers and writers in this field. Can somebody count how many blogs on Web Analytics are currently? This will help me set the baseline.
3. 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.
4. 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.
5. 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.

Agree? Disagree? I would love to hear your comments.

Understanding the "Time Spent on the Site" Metrics

I have come across this KPI over and over again. Many of my clients want to report it on frequent basis and some even have this as one of their goals for the site. However, I am surprised to find that not many people (not even a lot of web analysts) understand how this metrics is calculated and what this is actually reporting. I am personally not oppose to tracking this metric but have an issue when people try to set goals with respect to improving time on site without knowing what this metrics is actually measuring.

What are the issues with the metrics?
Let’s start with looking at the issues with “Time Spent on the Site” or “Time Spent on a Page” metrics.

1. Last page viewed in a visit is not counted in this metrics
2. Single Page Visits are not counted in this metrics
3. Visitors are multitasking, causing inaccuracies in actual time spent on the site.
4. Tabbed Browsing, causing inaccuracies in actual time spent on the site
5. Download time of the page – Time spent on page calculation includes time taken to download the page.

Let’s cover this one at a time

1. Last page viewed is not counted in the “Time Spent on the Site” calculations. – All most all of the tools (Since I don’t know exactly how many tools are there and how each of them work, I am using almost instead of saying all the tools) use the time lapsed between 2 page requests to calculate “Time Spent on Site”. Since last page viewed does not have any subsequent page request, there is no time lapsed recorded and hence the time spent on last page is not counted in the calculation.
To illustrate let’s take an example of a person viewing page A, B and C
A was requested at 10:00:00 AM
B was requested at 10:00:20 AM
C was requested at 10:00:30 AM
User leaves the site at 10:01:40 (Read page C for 1 Minute and 10 seconds)
Web Analytics Tool will show Avg. Time on Site as 30 seconds instead of 1 min and 40 seconds, the actual time spent by the user.
2. Single Page visits – Since this is the first and the last page viewed by a visitor, as explained above this page views is not counted in “Time Spent on Site” calculations. Single page visits are very common due to search engines and other sites linking deep into the site, this is especially true for content sites (news, articles etc.). Users search or click on links and then read the content spend 5-10 mins and then leave. These users will never be counted in “Time Spent on Page/Site” calculations. If yours is a news/content site then I can assure you that you will be underreporting the time spent on site due to either large percentage of single page visits or the users clicking on few links (within seconds), finding what they are looking for and spending majority of the time (few mins) on the last page and then leaving the site.

Above is the report on a page I created to track timespentonsite.asp, this page was the only page that I viewed in my visit (single page visit), this page shows an AvgTime of 00:00:00 even though I stayed on this page for 5 or so mins. (Snap shot from http://www.USAIndian.net)

3. Visitors are multitasking – Most of the time visitors are multitasking. If they are at work they are doing their regular work, talking to other, getting coffee etc. A visitor opens site, views it for 20 seconds, gets distracted come back 20 mins later, pick up the site where she left, clicks on another link views that for 2 mins, clicks another link views it for 20 seconds and then leaves. Does this happen a lot? You bet, look around talk to your colleagues you will find this happening all the time.
How much time will be reported by web analytics tool? 22 Mins. Is that correct? No. Isn’t the actual time viewed 2 mins and 40 seconds.

4. Tabbed browsing – Tabbed browsing even complicates the issue. Jason Burby’s article http://www.clickz.com/showPage.html?page=3623280 talks about how tabbed browsing has made it much easier to open different page of the site and multiple sites. Jumping to another site, opening various pages of the same site complicates the calculation of time spent on page/site. A visitor comes to the site, within 1 min opens 10 pages in different tabs that he/she wants to view. Now spends 1 hour looking at these pages. What will web analytics tool report as the time spent on site? 1 min, even tough user viewed it for 61 mins.

4. Download times of the pages – If a page takes longer than normal to download it will affect the time spent on the site. User might spend 10 second downloading while only 5 seconds viewing the page, however time spent will show 15 seconds.

So with all these inaccuracies is this metric still useful. I think it still has a value as long as you understand what this metrics is showing.

Sudden changes in time spent could indicate a problem with site navigation, search engine optimization or users behavior. It can shows that one of the factors on your site has changed
a. Single Page Visits – Change in single page visits will affect this metrics. If you search engine rankings have changed that can affect single page visits and hence time spent on site.
b. Navigation on your site – it either is obstructing finding the correct information (time spent goes up) or has improved so users are getting right to they content they are looking for (time spent goes down).
c. Problems with a page – This can cause users to exit site prematurely, causing time spent on the site to go down unless the problem is on one of the pages with very high exit ratio. Since the last page is never counted in calculating time spent, a user who exits after seeing this page or exits after getting an error on this page won’t make much difference in time spent on the site calculations.
d. User Behavior – If nothing else changed, then users might be either multitasking more than before or are using tabbed browsing. This will result in changes in the time spent on the site.

Identifying & Solving Client Pains

On Tuesday Manoj Jasra (http://manojjasra.blogspot.com/) started a multi part series in which expert Web Analytics Analysts from the industry explain the “pains” they hear from their clients or have encountered. The expert Analysts also talk about strategies to deal with these pains. I think this is a great effort by Manoj to bring different perspective on client pain points.

Contributing to this series are:
- Eric Peterson
- Marshall Sponder
- Gary Angel
- Avinash Kaushik
- Anil Batra (me)
- Justin Cutroni
- Jason Van Orden
- Robbin Steif
- Akin Arikan
- Manoj Jasra

Yesterday he featured Avinash and I, you can read the full article at http://manojjasra.blogspot.com/2006/12/identifying-solving-client-pains-part.html

The two most important pain points that I have encountered over and over are:

1. Accuracy of the Data – The tools are purchased and set up without understanding the goals of the business. Since the goals of the business/site are not properly understood clients start measuring and reporting on whatever out of the box reports the tool can provide. In most of the cases tool is capturing information that should not be captured and skipping information that should be captured (improper tagging and other issues). To avoid this issue our approach is to start with understanding the business goals and then make recommendation for the tool and configuration of the tool.

2. Acting on the findings – One of the major issues is acting on the finding. Once we make recommendations many customers can’t take any actions on them. Why? Because of organizational structure. IT, who is responsible for making the changes to pages, reports elsewhere. Marketing can ask for changes but won’t get them because IT has other priorities.

How should this be fixed:
1. Change in organizational structure
2. Help the whole organization know the impact of these changes, show the impact these changes will have on the bottom line.

These are not the only pain points but are the most common that come up almost all of the time. In future I will write about all of the different issues (pain points) that I have come across, so stay tuned.

Measuring Real Conversion Rate

I recently read Avinash Kaushik’s post Excellent Analytics Tip #8: Measure the Real Conversion Rate & “Opportunity Pie”. I like the approach in general but I have a differing view on point #1 and point # 3 in this article. In my opinion almost every real visitor who lands on your site provides an opportunity for conversion.

Point #1, Avinash states that we should disregard those users who view only a page or stays on the site for less than 10 seconds when calculating the real conversion rate opportunities. In my opinion not everybody who bounces (views 1 page or views the site for less than 10 seconds) can be discounted. These users do present a fair change of conversion. Let me show you why I think that’s the case.
Let’s take an example of a visitor who searches on a keyword on a search engine and lands on the site, three things can happen before leading to the bounce.

1. User spends 5 mins reading the page and then leaves the site. (Assume this is a content site and we are collecting email addresses) Maybe the user will come back maybe he/she won’t.

2. User is so lost when he/she land on the site that she leaves (site is so disorganized or the landing page content or value proposition does not matches with the keyword he/she searched – even though site might very well have that content or product somewhere else)

3. User lands on the site which is not worth his/her time and leaves.– Wrong Site.

In the above 3 scenarios your can only discount number 3 but not number 1 and 2, 1 and 2 provide an opportunity to convert. (Note: Scenario No 3 is also worth looking at; not from conversion point of view but why and how did users land on your site when it was a wrong site for him/her).

Number 1 shows you that user was indeed interested in the site and can possibly sign up for email newsletters had your page provided him proper links or path to conversions. Discounting this user is a big mistake, considering how deeply linked sites are these days and users have lot of information on their finger tips. Users generally won’t spend time to find a path to get converted unless you can convince them, but these user provide an opportunity. This is especially true for lead generation sites, where visitors come to read something specific and they might read only one page in their visit but are valid conversion opportunity.

Number 2 shows that your site’s landing page was not well optimized to lead user to a conversion, you can’t discount the users and ignore this fact. This will be huge opportunity lost.

Note: Time spent on the site is calculated by time lapsed between 2 page views, so when a user views only one page they are automatically excluded from this calculations (not sure if there are tools that can calculate actual time spent even when a user views one page). So don’t discount users with one page views, think about why they only viewed one page what you could have done better to convert them

Regarding customer intent (Point # 3) Avinash says that “One of the biggest mistakes business make is thinking that every visitor to the website is fair game, conversion fodder”. Again, in my view there is always an opportunity to convert visitors to customers. In brick and mortar case I have seen my dad (who owned a retail store in India) converting those people who stopped by in front of his shop for 10 seconds or less or just stopped by to say hello or talk about a product they bought earlier or even to complain about a product they bought in past. If he had taken this approach of deciding that it was not worth his time to pursue those people with no intent of buying then he would have lost a lot of revenue and long term customers. For site which sells lot of retail items this is very true. For example a user comes to the site to gain some information about a product he/she bought in past, say information on how to setup up email on the cell phone, with no intention of buying a new cell phone or an accessory, this visitor can still be converted if the value proposition is there or site does a good job of selling. You can’t discount this fact.

Another thing that should be looked at, in calculating real conversion opportunity, is the effect of cookie deletion on visitor conversion. Cookie deletion inflates the number of visitors and hence your conversion potential. For example, a user comes to the site every day views few pages at the end of the each day deletes the cookies. This user will appear as 30 unique users when you look at the whole month but as you know this is only user. So you only have one conversion opportunity when you use visitor as your denominator.

You don’t have to agree with everything I said but let me know what you think.

Homepage – How critical is it?

Recently I came across a customer, who wanted to make a cool looking homepage and putting all their promotions and one of the main lead generation links only on the homepage.

Since the beginning of the internet the homepage of the site has been considered the most important page of the site. Till recently, that truly was the case. Visitors entered the site mainly through the homepage; it was the main entry to the site. Cool looking homepage was considered the key to the success of the site.

Visitor’s behavior has changed; homepage is no longer the only entry page into the site. Visitors enter from all sort of different pages and not just the homepage. Homepage is still an important page but not as critical as you might think. Look into the data provided by your web analytics tool before you start changing the homepage in a hope that once the page looks cool everything will be fine. Pretty simple process but a lot of marketers ignore it.

This customer’s decision to redesign their site was made without looking into the data their web analytics tool was providing. A simple analysis showed them that only 14% of the visitors were entering the site from home page, and only 24% of the visitors actually saw the home during their visit. They were going to loose an opportunity to convert 76% of the visitors by putting the promotions and the main lead generation link just on the home page.

These days users don’t have time to look around. Days of web surfing are long over. Users are generally looking for some specific information/product and once they find it (via one of the factors listed below), they come to the site, get the content/product etc from the site and are gone from the site without checking the homepage.

Below are some of the factors that cause users to bypass the home page.

1. Search Engines – Visitors, now more than ever, rely on the search engines to find the sites or pages which are relevant to what they are looking for. Search engines link into internal pages not just home page, at least that’s the case for well search engine optimized sites.

2. Viral Marketing – Friends referring friends to internal page (pages other than homepage) of the site.

3. Bookmarks – Visitors are book marking the internal pages which have content/products which interest them and then use these bookmarks to visit the site.

4. Deep linking on the other sites – Other sites, blogs etc. are linking to the internal pages with content/products relevant to their content.

5. Online Advertising – Online Advertising (and offline too) drive users to landing pages which are generally internal pages.

I am not saying that you should not have a nice homepage (people do judge the book by the cover, if the see the cover) all I am saying is your redesign should be based on facts and not just gut feel. Focusing just on the homepage is not a smart idea. Your critical promotions and conversion processes should be easily accessible from the top traffic and entry pages, if not all the pages.

As always, I would like to hear your point of view and the stories that you might be willing to share.

Web Analytics – Tool For Measuring Off Line Efforts

Web Analytics, as the name suggests, is used for measuring and analyzing the web traffic. Online campaigns can be effectively measured by almost all of the web analytics tool in the market.

To measure online campaigns you assign a unique campaign identifier at the end of the landing url and then use your analytics tool to see how many people responded to the end and then track them all the way to end conversion. It is easy (sort of) to calculate your Return on Investment on online campaigns.

You can use the same method to track offline campaigns, print, in-store display ads, billboards etc.

Here is how it works
1. Create a campaign tracking code(s) to track this campaign just like you do in online campaign
2. Create a easy to remember unique URL e.g. http://www.SeattleIndian.com/saveondining
3. The URL created in step 2 above redirect the users to actual landing page passing the campaign variables.
4. When a user arrives on page created in step 2, the user will be redirect as in step 3 and it will appear in the web analytics tool as the user is coming from a campaign.
5. Add the URL created in step 2 to your print advertising and you are done.

Example:
I will be using Google analytics (http://www.google.com/analytics) for this example

1. You have a campaign called “Save on Dining” running as a Half page color in local newspaper
Your campaign variables are
utm_source=Newspaper
utm_medium=Print
utm_content=HalfPageColorAd
utm_campaign=SaveOnDining

2. Create a easy to remember unique Vanity URL e.g. http://www.SeattleIndian.com/saveondining
3. The URL created in step 2 above redirect the users to actual landing page passing the campaign variables.
http://www.seattleIndian.com/dining.asp?utm_source=Newspaper&utm_medium=Print
&utm_content=HalfPageColorAd&utm_campaign=SaveOnDining
4. When a user arrives on http://www.SeattleIndian.com/saveondining will be redirect to http://www.seattleIndian.com/dining.asp?utm_source=Newspaper&utm_medium=Print
&utm_content=HalfPageColorAd&utm_campaign=SaveOnDining

Note: You can also set some variables on the Vanity URL web analytics tracking code instead of redirecting to a new URL.

Add the URL created in step 2 to your print advertising and you are done.

So why did I write this article? Well, there are two reasons why I decided to write this article today.
1. I have been involved with tracking campaigns for a fortune 50 company and this topic has come several times. So I had to write this one day.
2. I just read an article by Kevin Newcomb (http://www.clickz.com/showPage.html?page=3623461) about how one company successfully tracked offline campaigns so I thought this is a good time to write it so that users not only know that it can be done but how it can be done.

As always, I would like to hear your experiences with offline campaign tracking.

Who moved my traffic?

Your site traffic is down, you are running up and down the hallway freaking out. Who moved my traffic, who moved my traffic. Wait before you get all anxious about the traffic. Downturn in your traffic might not be something to freak out.
Below are some of the things to look at to find out why your traffic is down. Some reasons are within you control (stop freaking start working) some out of your control. Some might be very obvious and some might not.

• Seasonal Impact – Do year over year comparison and see how the traffic pattern was last year.
• May be overall traffic is down even for your competitors (do comparison at http://www.alexaholic.com/ )
• Has a new competitor entered the space? How is their traffic?
• Traffic drivers – How was the traffic from these sources?
  Campaigns (Banners, Search, Emails) – Did they ran as normal.
  Email – Did anything change there? Did you send out your regular emails, newsletters?
  Search – Did you change anything here, has search engines changed their algorithm.
  Search – Did you change your site? Meta Tags? Content?
  Affiliates – Has any affiliates changed their site.
• Environmental Factors – How is the weather in the geographical region where you have most visitors from? Nice weather can keep people outdoors, resulting in lower traffic.
• Was there any site outage?
• Have you made change to your web analytics tool configuration? If yes, investigate what those were? Problems in filter could be filtering out a lot of traffic.

This is a work in progress. Feel free to send me other things that you might look for.

Web Analytics Books

Know of a book I am missing send the name to me. I have not read all of these but complied this list of of Eric Peterson’s Yahoo Group postings.

Web Analytics Demystified by Eric T Peterson http://www.webanalyticsdemystified.com/about_wad.asp

Web Site Measurement Hacks by Eric T Peterson http://tinyurl.com/mzk6r

The Big Book of Key Performance Indicators” by Eric T Peterson http://www.webanalyticsdemystified.com/about_kpi_book.asp

Web Metrics: Proven Methods for Measuring Web Site Success” by Jim Sterne http://tinyurl.com/mptuj/n/n

Drilling down: Turning Customer Data into Profits with a Spreadsheet” by Jim Novo
http://jimnovo.booklocker.com/

Measuring the Success of Your Website: A Customer-centric Approach to Website Management” by Hurol Inan
http://www.hurolinan.com/books/WebAnalytics/default.htm?src\u003dbooks

Search Analytics: A Guide to Analyzing and Optimising Website Search Engines” by Hurol Inan
http://www.hurolinan.com/books/SearchAnalytics/default.asp?src\u003dbooks

E-Metrics: Business Metrics For The New Economy” by Matt Cutler & Jim Sternehttp://www.targeting.com/emetrics.pdf