Category Archives: internet advertising

Why marketers know if you’ve been naughty or nice

santa watching

There is a story about a jolly old elf who tracks your behavioral data carefully, spies on you even when you’re sleeping, and runs algorithms to assess whether your actions are more positive or negative than social norms. Based on his calculation, the elf will reward you with financial gain in the form of material goods or will deduct from your status by tricking you with what looks like material goods but in reality turns out to be lumps of coal. The system is extensive, including a database of every youth in the world, and is updated annually. If you don’t like this surveillance, good luck: The elf’s privacy policy is unpublished, the observational data cannot be accessed by individuals, and your only recourse to correct misinformation is to send handwritten postal mail to the elf’s address at the North Pole.

Perhaps these childhood stories are why people often freak out about data. The legends of people recording others’ actions, especially those of children, as a form of behavioral modification have been with us for millennium. In Bavaria, the Santa myth is actually split into two figures, a Saint Nicholas who rewards good children with gifts and a devilish, horned Krampus who punishes bad children. Japan has a similar tradition, with an Namahage figure played by men wearing huge, ugly masks, who knock on doors and warn children not to misbehave. Religion is filled with data tracking, starting with God watching Adam and Eve’s naughty apple-biting in Eden, moving on to the widespread but vague idea that somehow all of your actions in your lifetime are being observed for a final post-death judgment. In our deepest beliefs, we perceive there is a connection between what we do, how others record it, and how we will be rewarded.

Which brings us to marketing surveillance 

If you collect enough data to form a baseline for comparing people, you end up with a “database” — and this idea has been around for at least 400 years.  In America in the 1600s, clergy tracked births, marriages and deaths; officials called “tythingmen” would also enter homes to inspect families for observed moral behavior. The first consumer database in the United States was set up in Massachusetts in 1629 to track property ownership. As data expanded, intrusions did too. In the early 1700s, U.S. postal mail was opened regularly to spy on message content.

And then marketers figured out they could make money from all of this information. Database marketing started in the 1940s, first driven by direct-mail marketers (who needed target lists of consumers to mail things to and then calculations to see what worked), later by credit-card companies and banks (who rapidly learned that not all consumers have the same credit risk), and then in the 1990s by Internet marketers who realized they could measure a treasure trove of consumers’ online behavior. While the basic approaches are the same — identify potential customers, differentiate by their value to you and what they need from you, continue to gather more information through interactions, and then customize your response — the cycle time of data marketing increased. Direct mail list updates used to take months; if you purchased a pair of boots at a store in December, it might be March before another company’s boot catalog showed up in your mail. But the Internet enabled a cycle time of identification, differentiation, interaction and customization within days, hours, and now even seconds. Visit, look at shoes, don’t buy them, and you’ll see ads for similar shoes on other web sites within seconds. The prevalence of such digital “retargeting” has gotten so rapid that many consumers are beginning to freak out.

The systems are growing ever-more sophisticated. Digital media vendor Rocket Fuel has begun testing device fingerprinting to track consumers by their individual mobile phones; in a recent campaign for Brooks running shoes, it identified the mobile devices of everyone standing along the running route of the New York City marathon, and then later served ads to those devices for running equipment long after the crowds had dispersed to Baltimore, California or even foreign nations. Digital marketers can pick up the IP address of a home’s Wi-Fi connection, and then retarget multiple devices — based on a trigger of one person’s behavior — across the many iPhones, tablets and computers residing in a household. Creative-based retargeting is another digital approach in which banner ads or online videos can be retargeted based on a single ad appearing on any web page, whether or not a consumer clicks on it; for marketers, this provides the advantage of being able to “lift” a publisher’s audience, such as a reader of, and chase that individual around the web later with a pretty good idea of their demographic profile based on the original reading material.

Consumers are rebelling, so what is the balance?

Not everyone is happy about this. Early in 2014, a survey by Truste, a global data management company, found that 74% of Internet users had increasing worries about the use of online data. While only 38% expressed worry about government surveillance, 58% said they had concerns about business use of their personal information. Beyond simple consumer annoyance, the growing use of online data may actually be harming marketing results. 83% of survey respondents said they were less likely to click on an online ad due to privacy concerns. In a deeply ironic circle, the data collection sophistication used to make online marketing work better may actually be depressing response rates.

Smart marketers are recognizing this and beginning to tone down the creep-factor of retargeting, using tactics such as impression caps, dayparting, ad creative versioning, and opt-out options to allow Internet users more breathing room before they are inundated with braying offers.

Data tracking will not ago away, because it is how all of us assess the outside world to calibrate our actions. Marketing in particular is all about treating different customers differently, as the great Don Peppers once wrote — after all, if you have unique needs, you should receive messaging about products or ideas that appeal to your interests, and marketers who play this right will gain greater results from their advertising investments. Just as parents and Santa Claus watch over children to assess behavior, other people will always be watching you too. The practice isn’t creepy in and of itself; what has gotten scary is the instant cycle time it takes someone else to pass their judgment. For our clients, we recommend looking beyond just response and conversion rates to also assess the real end customer experience. You’re trying to share information that benefits the customer, so pace yourselves, people. Everyone likes an elf who brings presents, but we all get nervous if he’s watching us too much.

A look inside the social targeting of 33Across

Say you buy a product. And your friends like the same stuff. Wouldn’t it make sense for a marketer who has you as a customer to target your friends, too?

This concept of homophily — that birds of a feather flock together, or more accurately, buy similar stuff together — has been around for decades, yet it’s been difficult for advertisers in the past to really take action on it. Demographic targeting systems such as PRIZM try to group consumers into similar socioeconomic categories, but that’s just a rough theoretical cut. In a perfect world, you’d want to measure exactly what people buy, then find their real-life friends most like them, and then push similar offers to those friends.

That future has arrived in the form of 33Across, OwnerIQ and similar services that track individual data online. (If the world of online media buying seems confusing, all you have to know is marketers can either buy space or data; space is the old world of buying banner ads on assuming NYT had a good audience, while data is the new world of finding ways to serve online ads to your target consumers directly no matter where they pop up online.) 33Across is one of most fascinating new online buying providers we’ve encountered because it expands your narrow target by adding those consumers’ friend connections.

Here’s how it works:

1. Tag. Say you’re a marketing manager at Nike and want to target people interested in running gear. You can pixel your Nike landing pages online to push cookies onto the computers of everyone who visits. This is a good start — but will create a small population target vs. the millions of other potential buyers online.

2. Add friends. 33Across can compare that data set to 125 million users it tracks online, or more specifically, the visible “friend” connections between these users (no personally identifiable information is collected). The data is observed via any social media tool with public visibility; Facebook, for example, does not resell data to marketers, but may widgets and applications inside the Facebook ecosystem can be observed.

3. Expand the target. If you assume Nike was able to tag 500,000 consumers who visit its sites, 33Across might expand that target to 3 million “strong ties” (users who communicate to their friends very frequently), 8 million moderate connections, and an extended network of 20 million. Nike has just increased its online target by 6x to 40x … with the logic being friends of its most loyal consumers are likely to be interested in fitness products as well.

It’s a fascinating use of social media to reach people most like your best customers. As 33Across explained to us, “by targeting people socially connected to your customers, you’re reaching someone with a propensity to act like and respond like your customer.” At a CPM a fraction of those old-school marquee sites, this new expansion of your target audience seems worth testing.

Image: Cliff1066

Can online ads be 2/3 of media spend? No.

We had a friendly virtual debate with Shiv Singh tonight. You should read his blog, he’s a bright mind for Razorfish. Here’s the replay.


If you’ve wondered why the Internet is hot and continues to still be, this chart says it all. Advertising dollars are moving online in a big way… According to Union Square Ventures partner Fred Wilson, he can see this percentage becoming two-thirds of all advertising spend as TV and radio become audio on the Internet and video online. Do you agree?


No. I appreciate the enthusiasm but I also suggest that following hockey-stick projections is a sure way to look silly in a few years. The facts are the average U.S. household has more than four TVs — more TVs than people — and the typical consumer watches 5 hours and 9 minutes of live television. The biggest trend is concurrent media usage, in which people, like myself, watch CNN while typing on a computer and using the phone. The Internet is additive but itself is facing the end of its bubble, a la the emergence of mobile as the new Internet, the diminished ad inventory inside smaller mobile screens, and the shifting modalities of consumers who are learning to create and share their own content. Apples’ “app” innovation has put a nail into the young coffin of mobile advertising since most apps have extremely limited visual inventory to insert any ads at all.

Now, if mobile is the future — and Wall Street guru Mary Meeker says it is, with more than 10 billion untethered devices soon to be in human hands — how has mobile advertising fared? Why, we’ve missed every mobile forecast for the past 10 years.

It’s cool to be visionary, but Internet advertising has a big problem — banner CPMs are falling to the floor, consumers are moving to smaller mobile screens with less inventory, and gadget manufacturers have an incentive to put up new walled gardens that make advertising insertion even more difficult.

Image: XiXiDu

NYT skimmer lets you skip the ads, yet see more ads. Here’s how.

Jason Moriber at Wise Elephant points to a new prototype interface from The New York Times which lets you rapidly skim over news content. He writes:

“It might not be pretty, but it matches the online trend of users skimming through feeds, reading over posts, grabbing the nuggets they want/need … I often say ‘react to the behavior of your market, follow what they are doing, not what they are saying.’ This new interface from The New York Times appears to be on this path.”

The new NYT skimmer format is perhaps most intriguing because it ditches the banner ads that have been encroaching on more and more of the visible real estate on the NYT home page. (See Apple monstrous ad format from last Monday.) But there’s a trick — if you click on any of the article headlines at skimmer, you land at a real NYT inside web page complete with ads. And the ads are more contextually relevant, since NYT can serve them next to the content you want to read. All in all, a nice victory for both marketers and consumers — faster access to the news you want, smaller and less-obtrusive ad formats, and the potential for ads to offer you something relevant, thus driving up response rates. We say, please NYT, keep it live. Bookmark it here.

TV and print push kids to the web

If you have children you know they are drawn to anything web related. We can hardly get our iPhone away from the wee ones. So it’s no surprise that MRI reports children 6-11 leap to the internet to research products they see in offline ads. About 46% of kids report they visited a web site they first heard about in a commercial. Within those numbers, the skew tends to older kids 10-11 who have more access to the net and sophistication.

The implication goes beyond children for marketers who often segment media plans and examine inquiries from each channel — TV vs. radio vs. print vs. web banners vs. SEM — as if they were separate Olympians competing for a gold medal in Greece. That’s a mistake, since one media channel may feed another. Broadcast and print still work to build awareness, and then the web captures the curious as they explore for more information. Integrating your measurement to capture the impact of all media touchpoints won’t be easy, but until you do, don’t turn off the TV.

Sometimes with Google it’s flirtation, not a wedding ring

You didn’t marry your spouse on the first date — but didn’t that first kiss count? Of course it did. Online marketers need to realize the same and not just measure “the last click” when quantifying online advertising performance.

Web consultant Avinash Kaushik points out that marketers running paid search campaigns on Google, Yahoo or MSN need to evaluate search terms based on how they fit into the consumer purchase cycle. Some terms may appear initially to have poor performance … but be a required step to lure the customer to your door. He suggests:

1. Category keywords are used by consumers in the early consideration phase. These terms are typically numerous, have low costs per click, and low results in terms of conversion to leads or sales.
2. Category and brand keywords are used as consumers enter active consideration. Results begin to improve, but bids on these terms become more expensive.
3. High-cost brand keywords are dominant as consumers get close to purchase.
4. And so-called “conversion keywords” are the terms that consumers type in when they are most likely to submit a lead or make a sale.

His point is all the terms are needed to provide a sequence that guides customers from learning about you to considering you to actually buying. Marketers who hope to manage the entire process most effectively should examine metrics other than hard results; flirting may take more than a single click.

Pew’s internet future squeezes advertisers

No surprises, but Pew’s latest paper The Future of the Internet III points out the 4 billion cell phones that now exist worldwide will soon replace computers as the gateway to the internet. Susan Crawford, founder of OneWebDay, tells Mediapost “by 2020 we’ll have standard network connections around the world … billions of people will have joined the internet who don’t speak English. They won’t think of these things as ‘phones’ either — these devices will be simply lenses on the online world.”

All of which gives advertisers a challenge. The screen sizes on phones are smaller than PCs, reducing advertising inventory by 90% or more — putting the same pressure on web publishers that they recently put on newspapers. The adage “why buy advertising for dollars in newsprint when you can buy it for pennies on the web” may turn into microcents on mobile phones, as consumers chat with scant side space for marketers.

See our complete thoughts on the future mobile advertising challenge in BusinessWeek.

U.S. politicians swing at online targeting

So U.S. politicians are now asking Google, AT&T and 31 other companies if, and how, they target ads to online consumers. The root of this investigation lies in new technology that allows ISP providers such as your cable system — who give you the box that hooks your computer into the internet — to compile data on everything that web users do. This is different than having single web sites track your behavior; now, “deep-packet inspection technologies” could conceivably track every site you hit, every article or photo you read, the keystrokes you type, and assess patterns in your behavior to determine that you are a 42-year-old male who likes earth-toned striped socks from Banana Republic.

Privacy experts howl, claiming that ISP data mining would be like giving consumers helmet cams that relay every action to advertisers without consumers knowing about it. The flip side, though, is that consumers respond to personalized ads driven by data extremely well. National U.S. click-through rates average 0.14% on banner ads; targeted ads that follow consumers’ behavior across multiple web sites have CTRs above 0.76%.

Seems there is a difference between what consumers say they like and what they actually do.

Photo: Peter Baker

Google and NYT knock out software by watching you

Last fall we came across Google’s image labeler, a little game that invites you to race a stranger (somewhere out there) in tagging photos with titles that make sense. We got served Drew Barrymore and typed “knockout.”

Turns out Google and other companies are using your personal down time to improve how computers recognize photos, video and scanned text. Humans are better than computers at image recognition; but if millions of humans say an image is X, the computer begins to get it too. In the cleverest move, the twisted-word Captcha codes you type to gain access to Twitter or Facebook are being monitored by The New York Times to improve computer recognition of printed words … in essence, using 10 seconds of your brain to refine software that will scan back issues of NYT from 1851 to 1980.

Both ideas, the image play and “ReCaptcha,” are brainchilds of Luis von Ahn — a Carnegie Mellon guru who created the fuzzy password tests for Yahoo in 2000, and is expanding to use downtime to solve problems of artificial intelligence. The average U.S. consumer spends 1.1 hours a day on electronic games and 1.7 hours using email, all input-heavy interactions that could conceivably be leveraged for broader computing tasks.

Just think of what he’ll do with the 17 minutes you spend in the bathroom.

Tip from Brad Ward.

NYTimes and InformationWeek, why are you shouting?

Clutter diminishes response.

We thought of this recently reading, where an errant mouse scroll causes annoying ads to pop up for things we are NOT interested in. Alas, this week The New York Times also began running those damn interstitial ads on its main home page — meaning you had to see a full-page ad before you get to the news.

The trouble is responses, or click-through rates, decline when consumers see clutter. This is true across media — direct mail postcard response rates slide in November, when mailboxes are stuffed with catalogs; newspaper costs per inquiry shoot up the week of Thanksgiving, when papers are overstuffed with mall ads; and, a popular women’s web site, has given clients we know some of the lowest-possible click-through rates.

One of the reasons ad networks (collections of web sites) are attracting advertisers is their results, in terms of click-through rates, are often better than single major content sites. Many people think it’s because behavioral targeting allows you to track people of a certain description across thousands of sites.

Could be. Or maybe those smaller sites just have cleaner layouts, so the ads get noticed.