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We know what you’re thinking

IMAGINE browsing a website when a saucy ad for lingerie catches your eye. You don’t click on it, merely smile and go to another page. Yet it follows you, putting up more racy pictures, perhaps even the offer of a discount. Finally, irked by its persistence, you frown. “Sorry for taking up your time,” says the ad, and promptly desists from further pestering. Creepy. But making online ads that not only know you are looking at them but also respond to your emotions will soon be possible, thanks to the power of image-processing software and the ubiquity of tiny cameras in computers and mobile devices.

Uses for this technology would not, of course, be confined to advertising. There is ample scope to deploy it in areas like security, computer gaming, education and health care. But admen are among the first to embrace the idea in earnest. That is because it helps answer, at least online, clients’ perennial carp: that they know half the money they spend on advertising is wasted, but they don’t know which half.

Advertising firms already film how people react to ads, usually in an artificial setting. The participants’ faces are studied for positive or negative feelings. A lot of research, some of it controversial, has been done into ways of categorising the emotions behind facial expressions. In the 1970s Paul Ekman, an American psychologist, developed a comprehensive coding system which is still widely used.

Some consumer-research companies also employ goggle-mounted cameras to track eye movements so they can be sure what their subjects are looking at. This can help determine which ads attract the most attention and where they might be placed for the best effect on a web page.

This work is now moving online. Higher-quality cameras and smarter computer-vision software mean that volunteers can work from home and no longer need to wear clunky headgear. Instead, their eyes can be tracked using a single webcam.

One of the companies doing such work, Realeyes, which is based in London, has been developing a system that combines eye-spying webcams with emotional analysis. Mihkel Jäätma, who founded the company in 2007, says that his system is able to gauge a person’s mood by plotting the position of facial features, such as eyebrows, mouth and nostrils, and employing clever algorithms to interpret changes in their alignment—as when eyebrows are raised in surprise, say. Add eye-movement tracking, hinting at which display ads were overlooked and which were studied for any period of time, and the approach offers precisely the sort of quantitative data brand managers yearn for.

At present the system is being used on purpose-built websites with, for instance, online research groups testing the effect of various display ads. The next step is to make interactive ads. Because they can spot the visual attention given to them, as well as the emotional state of the viewer, these ads could tailor their responses.

As similar gimmicks become widespread, privacy concerns will invariably mount. People would need to give consent to their webcams being used in this way, Mr Jäätma admits. One way to persuade internet users to grant access to their images would be to offer them discounts on goods or subscriptions to websites.

Realeyes is also working with Kaplan, an educational-services company, on a project in Hungary which is using the system to measure how children respond to virtual games that teach them English. The hope is that by performing the same emotion-reading trick that marketers use, the type of tasks and the characters that appear in them can be made more engaging.

The technology would make computer games more engaging, too. Sony, for one, thinks that reading players’ emotions with webcams would let software pick up on their subconscious behaviour and change the game in ways that would enhance the experience. The company claims that in the future it will be possible to have something like a detective game in which the camera can read players’ faces and measure their heart rates in order to have a stab at deciding which ones are lying.

In fact, webcams that monitor a person’s heart rate are soon to appear. Instead of sticking sensors onto the skin, Philips has developed a vital-signs camera system which the Dutch company says can measure heart and respiration rates extremely accurately. To calculate the heart rate the camera detects tiny changes in the colour of the skin. These changes, imperceptible to the human eye, occur as the heart pumps blood through the body. The person’s breathing rate is measured by detecting the rise and fall of his chest. The firm will soon launch an app for Apple’s iPad 2 which will allow people to measure their own heart and breathing rates using the two webcams in that device.

Philips is developing the technology as a contactless system to keep a virtual eye on hospital patients, such as newborn babies, who might find conventional monitors distressing. The company is also eyeing anxious parents who always want to know what their tots are up to, as well as anxious coaches and their athletes. Advertising firms will, no doubt, be just as keen to measure heartbeats, especially for ads designed to get pulses racing. Those who find it all smacks of Big Brother can turn their webcams off. If you are playing online poker, that is probably a wise idea.

Google is opening wider a beta test of Dynamic Search Ads, an interesting new type of AdWords ad for larger advertisers that eliminates the need for keywords.

With this ad type, designed for retailers or other advertisers with large, often-changing inventory, Google automatically generates ad copy — based on the advertiser’s template — by looking at the content in the advertiser’s Web site. Google also automatically displays the ad in response to search terms it thinks are a good match, without the advertiser having to select keywords. Google has been using a similar no-keywords approach in its program for small local advertisers, AdWords Express.

For Dynamic Search Ads, advertisers input their Web site URL or the URL of a range of pages on their site — say, a retailer wanted to promote their women’s clothing — and select a bid price based on the value of that category to them. Google then continually crawls the Web site so it knows when inventory changes, and can theoretically respond with relevant ads more quickly than the marketing team that’s manually creating keywords and ads. The system is also designed to keep on top of changes in the types of queries people are performing — Google says 16% of searches every day are new.

In an effort to keep this from impinging on advertisers’ existing campaigns, the system will hold back the dynamically generated ad in favor of advertiser-created copy, if the advertiser already has a campaign targeting the specific search term.

“We want to make sure it doesn’t affect keyword campaigns,” Baris Gultekin, director of AdWords product management, told me. “This is purely incremental.”

Gultekin says the company will provide advertisers with reporting on search terms that generated clicks, the matched destination pages and ad headlines generated, average CPC, clicks and conversions. Advertisers may optimize by adjusting a max CPC bid.

The new ad type has been in development for two and a half years, and “a couple hundred” advertisers across a variety of verticals have already been testing it. Gultekin says advertisers on average are seeing 5-10% increase in conversions with a positive ROI.

One advertiser in particular — ApartmentHomeLiving.com, a real estate Web site with constantly changing inventory — says it saw a 50% increase in conversions at an average cost-per-conversion that’s 73% less than their normal search ads. The company is already a seasoned search marketer with campaigns of up to 15 million keywords.

Dynamic Search Ads are available in all languages and all countries currently, but only to advertisers in the limited beta. The company is soliciting inquiries from customers that might be interested in participating in the beta in order to widen its reach.

Most entrepreneurs think about the color of their site in terms of how colors look together and whether they’re generally appealing, but color actually has a lot more to do with what your visitors think about your site – and the actions they take – than you might realize.

There have been entire books written about the psychology of color in buying habits. It’s a topic that has been well studied, and most marketing degrees include at least some study of this topic. We don’t want to bore you with psychology talk though. So here are the basics of what various colors mean, who they appeal to, and who should use them.

First, a Few Stats

Some of these statistics have to do with the color of individual products, but they demonstrate very clearly the power color has in the minds of consumers. According to a recent KISSMetrics report:

• 93% of consumers place color and appearance above other factors when making a buying decision.

• 85% of shoppers state color as the primary factor in their decision to buy a product.

• Brand recognition, which links directly to consumer confidence, is increased by 80% when the right colors are used.

What Does it Mean?

It’s important to know what specific colors mean to people. It’s been shown that certain colors invoke specific feelings in most people, so let’s see what colors really mean.

Yellow: Youthful and optimistic. Use it to grab attention. Usually not good as a background or primary site color.

Red: Energy. Creates urgency and increases heart rate. Good for appealing to impulse shoppers.

Blue: Creates feelings of trust and security. This is why many banks use it in their logos or marketing. Navy or dark blue  is used to market to the budget-conscious.

Green: Gives the impression of wealth. Relaxing and easy-going. Teal can be used to appeal to people on a budget.

Orange: Aggressive and excitement. Good for calls to action and impulse buying.

Pink: Feminine and romantic. Used to market to women and girls and traditional buyers.

Black: Powerful and sleek. Use it to market luxury products and appeal to impulse buyers.\

Purple: Soothing and calming. Often used to market anti-aging products.

Part of the study mentioned above found that what your site visitors see when they come to your site, from overall design to the colors used, really does make an impact on whether they buy from you. In fact, 52% of people surveyed who said they would not return to a site stated the reason as ‘aesthetics.’ If there was ever any question, that should confirm that the look of your site is one of the most important parts of your business.

Marketers have built a temple that needs to be torn down. Demographics have defined the target consumer for more than half a century — poorly. Now, with emerging interest graphs from social networks, behavioral data from search outlets and lifecycle forecasting, we have much better ways of targeting potential customers.

The rise of mass-produced consumer goods also brought the rise of mass-market advertising. In the 1950s and 1960s, the goal of television was to aggregate the most possible eyeballs for advertisers. In order to convince consumers that an advertising message was relevant to them, consumers had to buy the idea that they were just like everyone else.

Marketers created that buy-in by bucketing people into generations. When you lump 78 million people into one group called “Baby Boomers,” it’s much easier to sell them stuff, especially when consumers accepted their generational classification.

But now, that entire system has broken down. The year that someone was born will not tell you how likely he is to buy your product.

Fragmentation is now the norm because the pace of change is accelerating. Generations have been getting smaller because there are fewer unifying characteristics of young people today than ever before:

With the recent rise of the social web, people self-select into groups so small, so fragmented, and so temporal, that no overarching top-down approach could be successful at driving marketing performance.

Marketers have responded by adding more demographic information to the mix, but even that is a losing battle. I worked with one client who was introducing a technology product, and had identified a target market of “connected consumers.” Connected consumers were 34-55, had a household income over $120k, and read technology publications regularly. This target market represented 14 million consumers.

They were targeting 14 million consumers to sell 50,000 units — that means they were hoping for 3.5 sales for every 1,000 people with whom they connected through their marketing.

What if, instead, you could get 500 sales from every 1,000 people you marketed to?

It’s possible through psychographic profiling. Psychographics look at the mental model of the consumer in the context of a customer lifecycle. Amazon.com has long been a leader in this space, through innovations like “recommended products” and “users like me also bought.” Its algorithms have learned to predict its users, and what they are interested in. And now, there are a number of tools that any business can use to leverage psychographics.

Here’s how a psychographic profile might look different from a traditional marketing profile target for a childcare provider:

Psychographics provide much more useful information about users. There are multiple data sources making this possible today. Social profile data, behavioral data and customer lifecycle data can now finally be leveraged to contact people who are ready to buy.

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Social Profile Data

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Profile data from social networks consist of all the fields users grant permission for brands to use on their behalf. Most things that users track on social networks can be leveraged to create a closer relationship with a customer. Fields like relationship status, alma mater, interests and occupation can all be managed through social profile data management tools.

Social profile data is the critical cornerstone of psychographic insights. The level of nuance and insight provided by social data, when compared to standard demographics, is the difference between performing surgery with a scalpel or a butter knife. Previously unimaginable questions are now routine:

• Are customers who kayak more likely to buy water shoes than those who canoe?
• Who is more likely to spend over $100 on an order: Seattle Seahawks fans or Seattle Mariners fans?
• Are your customers more likely to purchase when they move across the state or across the country?

In addition, companies such as GraphEffect are measuring purchase intent by doing semantic analysis on Facebook status updates. This type of qualitative analysis can move users into specific marketing funnels from their very first online experience with your brand.

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Behavioral Data

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Retargeting advertising messages is gaining popularity among marketers, but its very success has jeopardized its effectiveness. Ads that follow users around the web have been implemented — usually poorly. Every ad network quickly incorporated the ability to place cookies in users’ browsers, and display specific ads to them any time they visit a site that’s part of their networks.

The next generation of ad targeting will focus more on telling the customer a story over time, based on specific behavior triggers. That means ad networks and clickstream data aggregators will work together to trigger when a customer moves forward in a mental model toward a purchase event.

Site content and product recommendations will also be informed by clickstream analysis. Companies such as RichRelevance, Certona, Baynote and Monetate all offer the ability to personalize information to specific visitors based on their behavior. Leveraging those alongside a payload of social profile data can turbocharge those services from the first moment a new user visits a site.

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Customer Lifecycle Data

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Social profile data can also be used to predict customer lifecycle. Imagine knowing not only if a customer has children, but the exact ages of those children. In addition, key indicator purchases, like buying diapers for the first time, indicate a customer entering a new lifecycle. Other key indicators, like shipping address changes, first purchases of furniture, or first purchases of substantially higher-value goods can all indicate the start of a new customer mentality and behavior pattern.

These patterns are predictable, so you know the future behavior of high school seniors by looking at the current behavior of college freshmen. By using demographics alone, all high school graduates would be marketed to identically. Using psychographics, we know who is likely to be interested in specific product or content recommendations at a specific time — such as when they actually start their first day of college.

This vision is starting to gain traction among serious marketers. At the 2009 Internet Strategy Forum, Xerox’s VP of Interactive Marketing, Duane Schulz, said that a 1% clickthrough rate was a huge failure — even though it is 10 times the industry average. In his mind, a successful campaign would never waste 99% of its impressions. Using psychographic data, you don’t have to waste any impressions.

We have seen a similar upheaval in marketing before. In the 1960s, marketers who embraced the power of television, broad-based insights into psychology and demographic data created world-class brands and billions of dollars in value. At that time, if you didn’t advertise on TV, you lost. Today’s new tools offer a similar choice: Build a deep understanding of your customer, or risk irrelevance.