Advertisements need to continue increasing personalization

According to Sean Ammirati at Read/Write Web this statement was made at Supernova conference by Sheryl Sandberg , Google's Global VP of Sales and Operations while giving a presentation entitled What's next for advertising?.

Sean Ammirati Says
“This [statement by Sheryl] was surprising to me, given that I don't believe Google has publicly announced any plans to incorporate behavioral targeting into their ad delivery system.”

Those who have been reading my blog know that I have been speculating about Google entering the Behavioral Targeting field. This statement by Sheryl reaffirms my belief.

Why do I think Behavioral Targeting makes sense over any other form of personalization?

Let’s start with the type of data that can power Online Personalization. There are 3 main form of data collection that can be used for personalization:

1. Explicit User/Visitor preferences – This is what a users tells a website about their preferences, interests etc and the site serves them appropriate experience, products, content, ads etc.
Example of this are
my.yahoo.com – you customize what you want and how you want it.

2. User/Visitor Demographic data - This form of personalization takes users Demographic data and serves up appropriate product, content, ads etc. recommendations based on those demographics. This could be a combination of explicit and implicit (location) form of data collection. Most of the data however is entered by users e.g. age, gender, income etc.

3. Behavioral Targeting – This form of personalization does not require any explicit user data. In this form of personalization Users’ intent and preferences are inferred from their browsing behavior via an anonymous cookie and not tied to any PII (Personally Identifiable Information) data. Based on users’ behavior marketers put the users in one or more of the predefined segments and then serve content, products or ad appropriate for the segments that the visitor falls in. Publishers/Networks/Advertisers don’t know who the visitor is all they know that cookie ABC123 is somebody who might be in the market for a new car. Read Behavioral Targeting 101 for more details on how behavioral targeting works.


1. The problem with “Explicit User Preference” is that it is mostly dependent on choices that a site provides to the visitors. If those choices are not indicative of what users really likes then it will give the wrong indication of visitors’ preferences. Say the site only provides me to choose Red, Green and Yellow colors, while my favorites is Blue then I will choose one of the given colors even though it does not show my true preference. Many times the visitors, in order to get through the registration form quickly, will fill whatever choice they see first. Expecting them to enter their preferences so that you can serve them appropriate Ads is not going to work. Preferences also change with time but visitors don’t go back and change their preferences unless there is a very compelling reason to do so. Getting an appropriate ad is not a very compelling reason. This form of explicit data collection border on the line of PII data and hence can suffer backlash from privacy groups.

2. The problem with “User/Visitor Demographic Data” is that a lot of visitor do not provide correct demographic information. It also suffers a lot of the same issues as “Explicit User Preferences”. User’s Demographic also borders on the line of PII data.

Behavioral Targeting on the other hand does not rely on visitors’ explicit information. As visitors preferences change so will their onsite behavior, say if was looking for a sports car about a year ago and now my situation is different and I am looking for a SUV, it will be reflected by my browsing behavior. I don’t have to go change my explicit preferences that I entered about a year ago (no waste of my time); my behavioral data will show that. Absence of PII makes it even more preferred way of personalization of Ads.

Is Web Analytics dead? No, it is maturing

It seems like a title like “XYZ is dead”, substitute XYZ for anything, is in fashion. I guess it gets more attention than saying XYZ is maturing or XYZ is changing. Not long ago there was a title like “Page views is Dead”, now there is an article by Nick Sharp of Webtrends “Web Analytics is Dead”.

Nick Sharp wrote:

“It might seem strange to hear those words coming from the mouth of a vendor that’s been selling the benefits of web analytics for more than ten years, but we genuinely believe that web analytics as a standalone discipline is no longer relevant to today’s marketers.
Marketers have turned their focus away from examining the activity on their website to include the results they’re achieving in other areas of online marketing, such as search campaigns, banner ads and e-mail tools. As a result, they’re not just looking for tools that measure their site performance, but also a way of bringing together the solutions they use to measure and track their online marketing in one single system.
This is why we see web analytics evolving into marketing performance management (MPM), which gives marketers a complete picture of their online marketing performance so they can manage and improve on campaigns across their website, online marketing channels and customer marketing programmes.”

I completely agree with Nick. I wrote earlier this year in my 2007 predictions “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.” Nick is proving my point right.

The only thing I don’t agree with him is the title of the article. This does not mean Web Analytics is dead. It is actually maturing, it is growing up. Web Analytics responsibilities are becoming more than just measuring how people are behaving on the site. It is becoming responsible for showing the effectiveness of other online marketing efforts. Soon it will have to tie in with the CRM system (some are already doing that). It won’t be just about what visitors did on the site, it has to become predictive. It can only happen when all systems about visitors (and customers) come together. With all the system tied together we will be able to predict things like

• On an average it takes 3 visits on the site before a visitor comes into the store (brick or mortar or online or through sales partner) and becomes a customer. Since we have a X% increase in visitors with 3 visits we can predict sales to be $Y in coming quarter.


• A,B,C pages, visits, section, paths etc on the website results in $XX in sales(offline, online, partners, other sales channels) in 4 weeks. Considering we got X number of visitors with A,B,C paths we can forecast $Y in revenue in coming month” etc. We should spend $Z on the banner ad on Google network and $Y on Yahoo network and $Z on Microsoft Network because they will result in X pages views of ABC page and hence maximizing our ROI and bringing in $YYY dollars in revenue (again this could be offline, online or thorough other sales channels).


• Our customers are divided into 5 distinct segments; they exhibit distinct behavior on the site and have distinct needs and buying behavior. Considering that visitors who match the onsite behavior of segment 1 is growing on our site we need to focus our marketing efforts so that we can grow other segment in a way that benefits us or we can plan our inventory considering the needs of growing segment 1.


• We know that visitors who come via search and come X times and Y visits to page A tend to respond better to Free Shipping than 10% off, so let’s give them a message which Shows them Free Shipping. We know we can expect Z% conversion. Even though we won’t make money upfront, life time value of these customer is $XXX.

I am sure some companies are already doing this or at least thinking about it. Soon this will become a norm, more will be expected from the Web Analytics.
So is Web Analytics Dead? No, it is maturing.
Comments? What do you think?

Behavioral Targeting results in 3 Fold increase in click through rate

I have been writing about Behavioral Targeting since the beginning of this blog. Since my writing there have several studies out touting the growth of Behavioral Targeting. What was missing in all these days was any latest case study on Behavioral targeting. In every article, I saw the same case studies by Revenue Science and Tacoda that I had seen year or two ago. Maybe I missed them; it is possible since it is hard to keep track of everything.

An article on WSJ titled How Marketers Hone Their Aim Online reports

“When Pepsi-Cola North America wanted to make a splash on the Web this spring to promote its new low-calorie vitamin-enhanced water, Aquafina Alive, the beverage company didn't run ads just anywhere on the Internet. It placed ads only on sites it knew would be visited by people interested in healthy lifestyles.
Pepsi was using an increasingly popular online advertising strategy called behavioral targeting, in which marketers analyze consumers' online activities to figure out who is most likely to be interested in its product -- and then place ads on whatever sites those consumers are visiting.
In this case, the beverage giant worked with independently owned New York-based behavioral ad network Tacoda Inc. to identify health-conscious people by looking at traffic to sites about healthy lifestyles over a month-long period. Then Pepsi arranged to place Aquafina Alive ads on some of the 4,000 Web sites affiliated with Tacoda so the ads would pop up whenever these health-conscious consumers visited.
The result? Pepsi recorded a threefold increase in the number of people clicking on its Aquafina Alive ads compared with previous campaigns.”

As I wrote in my article yesterday campaign success can not be judged by CTR alone you need to look beyond CTR. I would like to see more details about this study, so if anybody from Tacoda is reading this please let me know where I can find the details.

I hope to see more case studies like this. If you come across a case study then please send those to me. I will compile the results of various BT case studies in my future post. If you are an advertiser or publisher who has been involved with BT I would like to talk to you and get your views on BT.

10 steps for measuring online advertising success

I am amazed at how companies spend millions of dollars on online advertising but none to actually measure if it was successful or not. I have come across several companies in past few years so thought I will share my 10 step process to measuring the success and ultimately improving the ROI.

Below are two eye-opener real life examples that will show why I thought this was a subject that I should blog about:

• A customer spent 8 million on a huge online campaign but had not clue weather they were getting their money’s worth or not. All they got was banner impressions and initial click through rate (CTR ) from their agency. This initial CTR was in line with what their agency had expected so they were contended with the results. As far as measuring beyond the initial CTR they had no idea. Their answer was that we do not sell anything so we can not see if this is generating money or not, all we need to do it generate brand awareness. Well were they generating brand awareness? In few minutes we were able to see that that they had 90% bounce rate (yes they had WA tool implemented but were not looking at it, yah I know what you are thinking). That is 90% of the money down the drain. It is true that everybody who gets to the site has been exposed to the brand but is that enough? 90% bounce rate was pretty substantial considering that initial click through was close to 1%. I don’t think they were able to generate brand awareness.


• Another customer spent about 4 million on an online campaign but was very stingy when it came to using web analytics tool on their site to measure the success. Not sure if the marketing manger was not comfortable with the result that she would get or just did not consider it worthwhile to measure because she had extra money to spend.

Does this sound familiar? If yes and you are marketing manger or marketing exec, I would strongly suggest putting some money aside for measuring your campaigns performance beyond the initial CTR. You will be able to learn a lot more about how your campaign is performing and improve your ROI by simple A/B testing. If you are an analyst then please work with the marketing department and sell them the benefits of measurement.
Below are my 10 steps for measuring the online advertising success, nothing fancy, a simple straight forward process that will improve your bottom line.

1. Determine the goals and objectives of your campaign. - Knowing why you are running the campaign is first and foremost step. Unless you know why you are running the campaign you will never know if was successful or not. Marketing manager and web analyst should be in sync on this. Infect all the stakeholder should be on the same page. A clear understanding of the goals helps everybody focus on same things.


2. Determine success criteria and KPI’s for your online campaign. - Once you know the goals of the campaign, next step is to determine the Key Performance Indicators (KPIs) of the campaigns. These key metrics will allow you to see how the campaign is performing. If you already have a baseline measures from your previous campaign then you can compare your metrics against them or if you don’t have one then within weeks or a months (depending on the duration of the campaign) you should be able to develop one.


3. Create a campaign attributes framework - It is very important to build a campaign attributes framework from the beginning. Deciding what attributes to measure the campaign against early on will make sure you capture them from the beginning. Also upfront thinking will allow you to get a buy-in from agency, as most likely they will be responsible to for providing you with all the campaign attributes. Some examples of the attributes are placement, creative, message, publisher.


4. Implement proper web analytics tracking code on your site and landing page(s) - After you have the framework in place and know which metrics to capture, next step is to get together with you implementation team to implement proper tracking code on the landing pages and site. As you already know if the tracking codes are not implemented properly you will not be able to track your campaigns. I suggest running a test before you go live, so that you can resolve any issues upfront else it will be too late.


5. Configure web analytics tool to measure your KPIs - Another area to pay close attention to is tool configuration. Too many times I have seen disconnect where KPIs are determined but the tool configuration is so messed up that you can not measure anything. Determine what reports you will need and how they will be configured. Work with your implementation team; make sure they understand the goals and what you are trying to measure. I was recently involved with a campaign measurement configuration where we had to reanalyze the data because the implementation guy messed up one configuration. Luckily point no.4 above was correct so all the data was there it just had to be reanalyzed. Pay extra attention.

Tip - Configuration of the tools (reports) should be such that you can compare overall user (or user driven organically) with those driven by the campaign. I have found that this kind of insight helps you better understand your visitors and determine where you should be spending your money and effort. The more you can segment your user base the better insight you will get.

6. Build a scorecard or dashboard that will allow stakeholders to focus on the KPIs – The temptation by stakeholders is to look at every single data point weather they understand the impact of those or not. I have been in meetings were they will try to argue on things that don’t even matter. Why? Because they had access to the data and like to argue. The scorecard or dashboard should allow them to focus on things that matter instead of every data element that a web analytics tool can provide.


7. Tag all your ads with appropriate campaign identifiers - You have determined the KPIs, setup the reports and a nice scorecard is waiting for the data and analysis, but guess what? The agency did not add the proper campaign identifier. All your efforts are down the drain. The problem occurs because people setting up the campaigns in ad servers have zillion other things to worry about and if they are not ingrained in the process they will forget or won’t give due attention to campaign tracking. As I mentioned above in point number 3, if you create the attribute framework and involve the agency then this should not be an issue.


8. Analyze the data in few hours of launching the campaign, fill the scorecard and learn from the data. Few hours might be too early to learning anything meaningful (depending on the magnitude of the campaign) but can show you if something is really screwed up. Tune as necessary.


9. Periodic reporting and analysis (will depended on the length of campaign but start with daily then weekly/monthly). – Periodic reporting and analysis is an important aspect of this process, this is where you will actually know if the campaign is achieving its goals or are there things that should be changed. Don’t stop at reporting only analyze the data (see my article titled Are you doing Web Reporting or Web Analytics. Provide actionable recommendations. Provide your analysis back to the stakeholder. Discuss them, debate them and determine what to test. (I am not going to go in detail on A/B or multivariate testing in this article)


10. Put this process in place and share with all the stakeholders. Buy-in from all the stakeholders is necessary for any process to work. Put some timelines so that key stakeholder can be involved in the process in timely fashion.

The above process will help you measure the true success of your campaigns. Learn from the data and optimize as necessary. Remember there is always room some for incremental improvement. You will be amazed how you can improve your ROI by following above 10 steps.

Have you used a different process that worked for you? Comments? Suggestions.

Behavioral Targeted Ad Spending to Rise to 3.8 Billion by 2011

If you are reader of this blog then you know that I have been writing about Behavioral Targeting from the beginning.
I predicted earlier this year that Behavioral Targeting will become a common term among marketers.

A recent report by eMarkters furthers validates my prediction. According a latest study by Marketers Spending for Internet advertising with a behavioral targeting component will soar to 3.8 billion by 2011.



There are three key reasons for the large spending gains:
1. Behavioral targeting helps marketers reach a more engaged audience with fewer ad impressions
2. Behavioral targeting helps publishers monetize their "long tail" pages — the non-premium or remnant inventory that either is sold for less money or remains unsold
3. Even though individuals are often not aware of the process, many tend to find ads targeted by their actions to be more relevant to their needs, and therefore more palatable or even welcomed


Behavioral targeting spending will continue to grow at a significant rate, peaking at nearly 74% next year due to a combination of greater advertiser acceptance, greater publisher support (only about one-third of Web sites can do behavioral targeting, according to Advertising.com) and greater overall online ad spending with the national elections and Summer Olympic Games.



By 2011, "very large publishers will be selling 30% to 50% of their ad inventory using this [behavior targeting] technique," predicts Bill Gossman, CEO of Revenue Science.

Fishing From Barrel: Only Book on Behavioral Targeting

I came across "Fishing From A Barrel" by Rob Graham, Director of Training and Founder of LearningCraft. I think this is the first and only book on Behavioral Targeting (if you have seen another one then please let me know). I am halfway through the book and will post my review when I am done. Based on what I have read so far, I would recommend this book to those are interested in Behavioral Targeting and want to learn more.



According to LearningCraft.com Fishing From A Barrel takes an energetic and foundational look at how behavioral targeting is changing the face of advertising as we know it and introduces readers to the fundamentals of behavioral targeting technologies and how advertisers and publishers can use BT to achieve greater campaign and ROI results for their online advertising.

While still in its infancy, Behavioral Targeting is filling in many of the holes that have been part of the direct marketing landscape for over 100 years. Fishing From A Barrel brings readers on a journey that introduces them to concepts such as:

The future promise of Behavioral Targeting
Why Mass Marketing isn’t the best way to reach an audience
How to target and market to ‘individuals’
How to plan for and create highly targeting ad campaigns
How publishers are using BT to turn a huge profit
What you need to know about ‘Customerization’
How new targeting data goes well beyond demography
Why contextual targeting often falls short
Understanding and using ad networks
Using BT with traditional media channels
How to collect and use relevant web analytics
Understanding new definitions of Reach, Acquisition and Conversion
How to create targeted audience segments
The importance of privacy to consumers
What makes consumers consume?
Meeting consumer needs and expectations with every campaign
The Foundational Communications Model
Communicating Interactively
Who’s who in Behavioral Targeting

You can buy the book directly from LearningCraft.com. Let me know what you think about this book.

Additional Reading: My Blog Posts on Behavioral Targeting

Web Analytics Job Market is Hotter than Ever

Here is the latest update on “Web Analytics” jobs.
This snapshot was taken on June 1st. from Indeed.com and SimplyHired.com. Both of these sites are job aggregators that collect open job positions from individual company sites and from job boards such as HotJobs.com. SimplyHired.com also provides job boards called job-a-matic, like the Job Board I have on my blog. These job boards allow individual bloggers or site owners to quickly create a job board specific to their site’s content.
Like last month, Indeed.com has more jobs listed than simply hired.


Note Month in the above graph represents the month when the data was gathered.

Both indeed.com and simplyhired.com show an upward trend in open positions. Web Analytics jobs listed on indeed.com are up 16.16% from last month. On Simplyhired.com open jobs are up 5.71% from last month.
“Web Analytics” jobs listed on indeed.com are up 95.90% from Jan 1st numbers. Yes 95%, supply of web analyst is far exceeding the demand; it is a very very hot market for “Web Analytics” jobs.

Which tool experience is in demand?


Open Job Positions on indeed.com and simplyhired.com for various web analytics tools.


3 month comparison of open job positions for various web analytics tools based on indeed.com data.

Key Findings

1. WebTrends experience is in most demand. Till last month (May 1st snapshot) Omniture was the most demanded tool experience followed by Webtrends.


2. Webtrends related jobs are significantly up compared to last month.


3. WebTrends related jobs are 12% higher than Omniture related jobs. Last month Omniture was in lead.


4. Visual Sciences showed a big jump in open positions, around 140 compared to 1 last month.


5. Open jobs related to other tools (except Omniture, WebTrends, Visual Sciences) remained about at the same levels as last month.

I expected “Google Analytics” jobs to go up considering all the press coverage V2 of Google Analytics got. Even though Eric’s Vendor discovery tool reported that 25% of the urls tracked via this tool had Google Analytics , I am not seeing a lot of commitment in terms of hiring analysts to work on the data these companies will gather from Google Analytics. I guess companies have heard about Avinash’s 10/90 Rule and are saying “Hey I spent $0 on the tool so I guess I have to spend 9 times that on people so which is 9*$0 = $0). (Hint to the companies: Read the full article)

Want to start a career in web analytics? Check out my article Starting a career in Web Analytics and my Web Analyst interview series to see how others got started in web analytics.