My apps are trying their best to get to know me.
Netflix offers me the film Lethal Weapon because I like 48 Hours, or recommends the TV program Burn Notice because I like Mad Men and Arrested Development. The predictions are sometimes pretty close to the mark, sometimes seriously off-target, but usually entertaining.
The more entertainment I consume, the better Netflix becomes at predicting what I will like.In contrast, MOG thinks, “Since you love Rush, I bet you’d like to hear some Blue Oyster Cult.”
Nope. I wouldn’t. Sometimes apps miss. And that’s okay.
Netflix and MOG are among an emerging class of applications that are working to understand our unique tastes…and uncover the delicate influences that determine why we want what we want. In so doing, they are becoming increasingly aware of the differences that make us unique.
Over time, I am certain that they will become experts at pleasing us.
With apps like these, personalization is a key product component. Apps don’t just have permission to get to know us, they have the express charge to do so. It’s central to their purpose.
Apps are supposed to get to know us; bluntly customizing to our tastes is how apps prove their value. Ironically, data abounds to give advertisements much of the same personalization capabilities, but ads don’t have license to be so blunt.
Ads have to play it cool, or risk being creepy.
As an ad tech innovator, personalization is really exciting to me. I love the prospect of moving beyond targeting, to crafting ads in real-time to each audience of one – delivering relevant offers that consumers want. I think personalization will drive conversions higher and drastically improve advertisers’ ROI, making each ad more valuable and efficient. The whole industry is thinking along these lines.
As a consumer, however, I’m pretty wary when advertisers cross the line. It seems creepy that advertisers might be watching me, comparing notes about me, sharing data and then building offers that I can’t possibly refuse, because they’ve cracked the code to bring me ads with calls-to-action that are too powerful for me to resist.
The shock of personalizing an offer without providing any context for how the magic trick was done is not usually beneficial. People actually hate that. It feels like a violation.
Case in point: most people find it creepy to get a text message offering them a payday loan when they really do need the money. That’s the sort of data most of us would rather not have shared, and it’s a reminder that data leaks are everywhere. Forget about privacy – the data is out there. What is required is sensibility in handling it.
Advertisers have to adapt their personalization programs to a shifting definition of what’s appropriate. In this regard, defining what is or is not “creepy” is a lot like trying to define what is or is not “pornography.”
In Jacobellis vs. Ohio (1964), Supreme Court Justice Potter Stewart refused to define pornography. He said, “I know it when I see it.” We are all in the same way judging for ourselves what is and is not creepy. Standards for creepiness vary along slender audience segments. Age, technological sophistication and region all play a role in determining what any given consumer perceives as “creepy”.
That said, there are a number of things advertisers can do right now to make sure they are making the most of audience data to drive conversions without crossing the line.
Here are a few recommendations.
One key to personalizing without being creepy is to be upfront about where the data is coming from to power the personalization. Don’t hide the ball…put everything in the open. “Since you listened to U2, we thought you’d like to hear something from Duran Duran”.
Advertisers new to personalization are sometimes tempted to make it seem like a magic trick. But this is usually a really bad idea. The payoff just isn’t there. It’s best to be open about why the ad is personalized and where the data came from to power it. If it’s done correctly, it will feel like a valuable service, instead of a privacy breach.
Interestingly, the ads that appear in personalized apps can typically be personalized without making us feel violated. When ads are personalized inside of an environment that is also personalized, it lends valuable context to the ad. This is why Facebook can offer up sponsored stories, and why Groupon can give you personalized deals. Consumers understand and are coming to expect this behavior. The data and the ad appear inside the “circle of trust”.
Another key to non-creepy personalization is to let people opt out of it. It’s not for everyone, not yet. As soon as the benefits of personalization become evident – which is happening on its own at a very rapid pace – more people will become a lot more accepting. Hugo Liu, Chief Scientist for Hunch, says that personalizing without giving people a way to opt-out is like constructing a building without fire escapes. Personalization can seem like a scary ride; so people will need to know how to get off of it. I would support giving audience members the ability to choose whether or not their experiences are personalized, until consumer acceptance is clearly past the tipping point. Again – that depends on the audience in question.
Finally, rejecting the lure of accessing stale data and instead just using the data that’s right there in the open can yield the best results and also avoid creepiness. Perhaps surprisingly, the most valuable data to use for personalization – the dataset that actually matters most – is usually the data that’s right there in the open. While accessing past purchase history and Experian data might seem like an exciting opportunity, it’s usually not all that relevant to improving the experience or conversion of an ad. Data becomes stale pretty quickly. So there’s usually little to gain from using this sort of data.
It turns out that the most valuable data to make ads more relevant are:
1) Device type, OS and SDK. Optimizing an ad for the device experience is a critical baseline to making the most relevant and actionable ads possible. We sometimes call this targeting, but it’s a form of customization. If a user is on Android 2.3.6, eliminate transition effects. If on iOS 5.1, offer a click-to-buy via iTunes.
2) Location. Where is the user right now? What’s happening around the user right now? Is she shopping, or at a concert? Is she in a hospital or a museum? What’s nearby? Location data can make ads extremely actionable. GPS data is available in HTML5 and advertisers should not be afraid to ask users to share it.
3) Intent. What is the user searching for? Car dealerships or car parts? Coffee or tea? Have they abandoned a shopping cart? Listening for subtle clues here is important, especially for re-targeting. This is where a partnership with a data management platform can really help.
These data types are readily available in mobile ads, which is what makes mobile a terrific realm for pushing the boundaries of ad personalization, without being creepy.