How personal should you make the customer experiences you deliver? How personal can you make customer experiences?
In a previous post we described how a guy who doesn’t ski reacts to images on an ecommerce site of a woman skiing. He believes he’d respond more if shown something he can relate to.
If we somehow knew (and that’s an issue for a future post) that this guy bicycles, we could show images of bicyclists. The question for today is, what images do we need in our library to satisfy our visitors and our customer experience goals? Do we have to address, say, 6 possible biking interests (mountain, commuting, BMX, racing, family recreation, camping); 2 genders; at least 3 age groups (child, young adult, senior); and perhaps 6 environments (urban, rural, forested, plains, mountains, coastal). That’s 17 attributes, and 216 images to satisfy all combinations. If all you sell is bikes, perhaps you can afford that. If you cover all sports, or if sports is but one of your categories, how can you possibly?
Most likely, you don’t need 216 or even 17 images to be effective with this guy who bicycles. Maybe you only need 3 images. Which ones? How many? Who knows.
The only way to know is to “test” out the impact of having a few variations. I wish I could believe that there is one answer to the question of what will make our bicyclist happy. I fear that it depends on his current context, and therefore the customer experience must be variable as well.
In this realm, “test” bears no resemblance to A/B testing. Rather, it describes a an automated, data-driven prediction of what will have the greatest impact at this moment in time. Machines can make the predictions and deliver the customer experience. The marketing team has to decide how much to invest in content variations, and which variations are most likely to be important to visitors. Automated customer experience delivery and content planning are two programs that most companies have as yet to perfect, or many have as yet to attempt.
On Target 
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