I’ve decided to retire massless communication, at least for now. Check out my new site at www.eleanorbaird.com.

If you’re interested in the final thesis, you can find it at http://dspace.mit.edu/handle/1721.1/44213.

Thanks for reading,
Eleanor

Finally, here it is! There may be some tweaking, but this is essentially how the document will be laid out. Only a few more days to go!

Introduction

• Why this, why now?
• Research Questions
• Methodology

Part I: The History and Current Practice of Targeted Online Advertising

• Mass Communication: Reach, but limited personalization and control
• Enter the Internet: Targeting becomes more precise
• Understanding the Ecosystem
• Types of targeting
• Buying vs. Branding- Searching for the best use of the online channel
• Cookies, Pixels, and Data: How targeted online advertising works
• Current Issues in Behavioral Targeting

The quest for relevance
Industry consolidation…and fragmentation
Privacy Issues
Decline of the banner?
Pricing and Risk
Part II: Vital Signs – Metrics and Measurement

• Metrics Matter
• The Cult of the Click
• Conversions and Sales
• Engagement

Part III: Innovation and Evolution

• Origin of Innovation
• What to watch

Targeted video advertising
Localization
Segmentation through specialized online communities & networks
Rethinking of industry boundaries and silos

Part IV: Future Directions for Targeted Online Advertising

• Targeted online advertising will no longer look like advertising as we know it
• Consumers will assume more control the relationship
• Learning style could be a key targeting method
• Aggregation and artificial intelligence could alter how we think about targeting

Part V: Conclusions and Suggestions for Future Research

I’ve sent this out to a few people now – this is my revised abstract, which I put together this week.   The structure of the paper has changed a bit too, and I’ll post more on that in the next few days.  I’d welcome any comments you have!

In recent years, audience fragmentation has forced the advertising community to revise its thinking about delivering messages through mass communication channels. Changes in web technology and consumer behavior has, in many cases, increased opportunities to target advertising, yet how to make the most effective use of them has proven to be more elusive. The purpose of this thesis will be to understand the implications of this shift for consumers and industry; identify meaningful metrics; search for innovative practices in the field; and investigate potential role of social networks, branded utilities, cross-platform targeting optimization, learning styles, and semantic web in the next generation of targeted advertising.

This is a cross-post from the Convergence Culture Consortium blog, at http://www.convergenceculture.org/weblog/2008/03/mobile_marketing_more_ads_on_t.php

A few days ago, Nielsen released a report where they estimated that 58 million Americans had seen advertising on their phones in the last month. That is a lot of people, but it represents 23%, less than a quarter, of subscribers in the U.S.

And that number might be a little high. According to Nielsen’s site, the findings were based on a survey of 22,000 people who were “active mobile data users who used at least one non-voice mobile service in the fourth quarter”, suggesting that the respondents may be more open to or better able to receive advertising and content in more formats than the average subscriber.

Clearly, there is growing interest in mobile as an advertising channel, but the study found that just 10% of respondents thought that “advertising on their mobile device was acceptable”. As I work on my thesis, I’ve been thinking more and more about mobile phones as a delivery channel for targeted advertising. Although I’m very new to this area, the Nielsen study did make me think about why we aren’t seeing more advertising on our phones and PDAs, why consumers are so opposed to the practice, and if there is a trade-off that’s preferable to the ad-supported content model.

The best advertising medium?
Mobile devices offer some advantages over TV and in some cases the internet, in terms of tracking, timeliness of communications, and understanding consumer behavior. People don’t tend to share mobile phones and PDAs the way they share computers or televisions, making it easier to figure out what people in certain segments are looking for based on their usage of the device, and to reach the right person at the right time. The smaller screen, ability to do one task at a time, and access when other media may not be available may actually create a more engaged audience. Consumers could interact with their phones in many of the same ways they can interact with the internet, taking some of the guesswork out of tracking conversions.

The phones and PDAs themselves are getting more and more sophisticated. Many can how access the internet as WiFi hotspots multiply across the country; an increasing number of cities are making investments in free or inexpensive WiFi. Just about all phones on the market today can download music, ringtones, wallpaper, games, and other content through proprietary networks. Telecommunications companies are investing in force again, puring money into technologies such as 3G and WiMAX that offer wider-range networks and faster service. In the next few years, the sheer volume of mobile content available, and the average consumer’s ability to access it, will probably increase substantially and, as several studies have shown, mobile devices become an increasingly important part of our daily lives.

Willingness to pay
I have seen a great deal written about the possibilities new devices and technologies as platforms for ad-supported entertainment content lately, perhaps to soften the blow of the ads, but results like this make me wonder if entertainment is really what most consumers want and need right now due in part to preference, in part to price.

As always, consumer behavior and preference will set the tone for marketers. According to the April 2006 study by the Pew Internet and American Life Project with AOL and the Associated Press, the most desired mobile device features the users wanted to add were access to maps (47%), instant messaging (38%), services like stock quotes, movie listings and weather reports (24%), email (24%), ability to take still pictures (19%). The desire to access entertainment content, play music, watch video and play games, came in at 19%, 14% and 12%, respectively. Granted, the survey is almost two years old, the technology has improved, and user preferences may well have changed or be on the verge of changing. However, these findings highlight that the primary use of mobile devices are information and communication.

As technology and preferences change, consumers probably will want more entertainment content on their mobile devices. The problem is that the general dislike of advertising is unlikely to shift much in the near term, especially as we’re advertised to more and more of it on every platform, and getting people to pay for some content would be a tough proposition in an environment where television, DVRs, and the internet have conditioned us to expect entertainment to be free, multi-platform, on demand, and ad-free if we choose.

Another consideration is price. The Pew/AOL/AP study found that 36% of cell phone users had “been shocked from time to time at the size of their monthly bills”. The cost of using 3G services where they’re available can run subscribers an extra $15-25 a month (or more) on top of a bill that is likely around $35-40 dollars a month already. Devices themselves are changing rapidly to build in greater functionality, but the way many cell phone contracts are structured, the customer can only replace his or her phone for free or a small fee after two years, or pay hundreds of dollars. Consumer reluctance to spring for a new phone unless the device is really compelling (like the Razr or th iPhone) may also slow adoption of new technology, both in terms of the devices and the network used.

The Nielsen study suggests that price sensitivity is a factor for at least a third of users, and that advertising that supports services they already use may be the best bet for marketers. Findings indicated that 32% of respondents “are open to mobile advertising if it lowers their overall bill”, while only 13% “are open to mobile advertising if it improves the media and content currently available”. Although the release doesn’t suggest that those opinions are mutually exclusive (or correlated), it does seem that more people want to reduce the cost of the services they are currently using over getting better (and probably more extensive) content.

The question then becomes, what mobile applications, services, and content will people consider indispensable enough to pay for, and is that what should be ad supported?

In my next post, I’ll explore issues of personalization and privacy in mobile marketing, and propose some future scenarios for mobile advertising.

Note: This entry is a cross post from the Convergence Culture Consortium blog.

On Monday, Online Media Daily reported that Revenue Science, a behavioral targeting (BT) marketing firm, called for participants in an initiative it is calling the Behavioral Targeting Standards Consortium (BTSC), a group of industry practitioners and thought leaders that would define BT, set standards for data collection and use, define best practices, and identify some common metrics.

What does that have to do with convergence culture? I would argue quite a lot.

I am writing my thesis at MIT Sloan on targeted online advertising, so I have spent the last several months delving into the technology, techniques, issues and potential of the practice of BT. I am an MBA student, so my focus has been on the business and regulatory implications, but I would argue that, particularly as BT gets more sophisticated and the technology we use enables it to reach us through the internet on our computers, mobile phones, and perhaps eventually our televisions and other devices we haven’t imagined yet.

Advertising is ubiquitous in modern life, and has always been a fundamental part of mass media and entertainment industry economics, as has measuring and understanding audiences in order to couple advertising and content in a way that will attract their attention and generate sales. BT, however, enables a whole other level of targeting, based not just on what content is accessed, but on inputs provided by the audience itself on what they are interested in. It moves the currency of the media and advertising symbiosis from masses of eyeballs to smaller groups with specific needs and preferences, altering the message and potentially the medium.

The impact of BT is that advertising placement will respond not to the context of the medium, but to the context of how we engage with it.In other words, the cultural implication of BT is a shift in our relationships with advertising, advertisers and content – ultimately, how we experience media.

What is it?
One of the goals of the BTSC is to define what behavioral targeting is, but, until they do, I’m looking at it as a method of targeting advertising messages by segmenting an online audience based on their interaction with content online, meaning which sites they visit, links they click, searches they enter, purchases they make and what time of day they access the internet.

I’ve talked informally to a few people in the last few weeks about their experiences with BT. The most common examples they can think of are seeing ads for low airfares to a particular destination an hour or two after looking at prices, or seeing ads for products and services that relate to a recent search. Some were delighted, some were curious about how it happened, some thought it was “creepy”. It was interesting that Amazon.com’s practice of recommending products based on recent searches and purchases was not mentioned by any of the people I talked to, most Amazon customers – my hypothesis there is that because most of the targeting is done in the context of the Amazon site. What seemed to really attract attention, positive and negative, was the length of time that elapsed between looking for particular information or content and seeing an ad in a different context.

Relevance vs. Privacy: The controversy
Depending on who you ask, BT is about serving relevant ads for the benefit of consumers or a form of clandestine monitoring that violates their privacy. In December, the Federal Trade Commission (FTC), after a series of consultations, released a report called “Behavioral Advertising, Moving the Discussion Forward to Possible Self-Regulatory Principles“, which outlined some proposed guidelines around consumer notification, permission and control, as well as use, and storage, and security of data. It also opens the question of what data might be off limits for this purpose (i.e. medical data, children’s activity) and requests feedback on what might be considered “sensitive data” that should not be used by marketers. There is also the question of what defines data that makes individuals personally identifiable or provides useful information about them without revealing their identity.

From what I could gather, neither consumer advocacy groups nor industry practitioners were particularly happy with the FTC’s position on these issues, which may have spurred the creation of the BTSC.

Audiences and Consumers: The real decision-making authority
BT is a new practice, but it ultimately leads us back to questions similar to the ones asked about advertising more generally. How do we reach the right people at the right moment? What makes advertising compelling on particular platforms? What is the line between relevance and intrusion? How disruptive do ads need to be to gain attention? When do ads become irritating rather than entertaining? And the big question: how do we measure it all?

Ultimately, as many journalists, academics and practitioners have suggested, we are now in an era of unprecedented consumer choice and influence. The audience will decide the answers to these questions over time, and as usages and practices around various internet technologies evolve and become part of cultural practice. They will ultimately decide how much control they want to have over who can observe their activity online and how much privacy they will trade off for convenience, as well as when and how they want to see, respond to, and use advertising. The debates that are going on now among regulators, industry, and advocacy groups are interesting, necessary and fascinating, but now more than ever, understanding first hand what types of content and advertising motivate and engage consumers will be crucial for everyone involved.

Going through my RSS feed this afternoon, I came upon a post on Ilya Vedrashko’s blog, AdLab, about data from comScore and Starcom that suggests that banner ads fail to generate significant clicks beyond certain demographics and certain types of sites, and that the impact of clicks on brand metrics is negligible.

The questions I’m asking myself right now, and expect to address in the next few weeks, are:

• What does this mean for the future practice of targeting online ads? Will advertisers now start to see internet advertising as ineffective?

• Are clickthroughs the right metric to be using?

In my last post, I outlined my current plan for my thesis on targeted online advertising. This time, I’d like to answer what might seem like a very basic question, but it is still a very fundamental one: what do I mean by targeted advertising in the context of the web?

Targeting isn’t a new concept at all – marketers and advertisers have been finding ways to segment audiences for decades. What makes targeting in the context of the web so interesting to me is that it offers opportunities for near mass personalization from a variety of different angles and media formats in a very short period of time, and the capability to get real time data on how users respond to those changes. The flip side is the privacy issues that arise from those capabilities, which I will talk about in later posts.

I’ve divided online targeting into four categories:

1. Geographic, where advertising messages are presented to users based on their estimated geographic location, derived from their IP address.
2. Profile, where advertising messages are presented to users based on “traditional” demographics like age, gender, or geographic location, or on other self-descriptive information they may have entered in an online profile, such as interests, hobbies, favorite films, vacation plans, etc.
3. Contextual, where advertising messages are presented on a site because it is complimentary to the content of the page being viewed. Examples include putting ads for cable packages on electronics sites that sell televisions, or hotel ads on flight booking pages.
4. Behavioral, where advertising messages are displayed based on a user’s online actions, which could include what links they click, what time of day they are online, what sites they visit and how often, what search terms they enter, what they buy, and how much time they spend on a site.

If you follow this field at all, you probably know that behavioral targeting is the “hot” form right now that is getting a fair amount of press right now. There definitely is promise in analyzing behaviors to determine the intentions and motivations of a user, but I would content that targeting becomes the most accurate when we can effectively mix and match these techniques based on the behavioral data.

In my next post, I’ll elaborate a bit more on these categories, how they are related, and where the data for each can be derived. Thanks for reading, and please post any comments or questions.

For my inaugural post, I thought I’d explain in a little more depth what my MBA thesis is actually about by providing both a very early abstract and an outline, below. Future posts will be thought pieces based on my research, the purpose being to get some ideas “on paper” as I write for my April 6th full draft deadline, but also to vet some of my ideas before I make them part of the “official” thesis. So, I always appreciate questions, suggestions, and comments of all varieties on what I post on the blog. You can also email me at eleanor@sloan.mit.edu.

General overview

In the last several years, fragmentation of audiences has forced much of the advertising community to revise its thinking about delivering messages through mass communication channels. As new media forms have emerged that enable interactive search, collaborative filtering and social networking among consumers, so have opportunities to target advertising, yet how to make the most effective use of these tools has proven more elusive. The purpose of this thesis is to review past and current practices in targeted advertising, understand consumer motivations and attitudes about privacy and ubiquity of ads, and project future trends and directions for designing and targeting personalized advertising content.

At the moment, I’m working with an outline that divides the document into eight parts:

1. Introduction and Overview

a. What is targeted online advertising?
b. Why is this subject important? Why now?

2. History & background

a. Timeline and trends since mid-1990s
b. Evolution of types of targeting, origins of theory and industry approach
c. Consumer behavior on the web, the importance of relevance and cognitive processing of ads online

3. Targeted online advertising today

a. Users and providers of targeted online advertising – an overview
b. Technologies and platforms
c. Perceived benefits of targeted advertising
d. Consumer experience
e. Integration with broader marketing and advertising campaigns
f. Issues and drawbacks of using these techniques

4. Metrics & outcomes

a. Metrics and success indicators
b. Consumer and press reaction (brand impact, sales impact)

5. Regulation and privacy

a. Key issues in the U.S. market – privacy laws, FTC involvement and self-regulation initiatives

6. Case studies of non-U.S. markets – May include Ireland, Poland, U.K., China, Japan – still deciding which ones would make the most sense

7. Future outlook

a. Will certain types of targeting become more prevalent?
b. What does the regulatory landscape suggest?
c. How big a part of advertising spending may it become, relative to other media?
d. What could technological change affect?
e. What will it be like to be an agency? An advertiser? A consumer?

8. Conclusion

I am expecting that parts 3 (current state), 5 (regulation and privacy), and 7 (future state) will be the key parts of the document, and the ones that require the most research and development. I also think they will be the most interesting and challenging to write.