In its second-largest acquisition, Amazon buys the company for $970 million.
We’ve heard a lot about how personalization technology helps Web retailers: by increasing the ratio of browsers to buyers, giving stores a way to upsell and cross-sell and strengthening customer loyalty. What we haven’t heard as much about are the customer’s benefits-or risks.
It’s clear that personalization technologies can offer shoppers more convenience by pointing out a popular CD or a deal on batteries for a new cell phone. Yet this is convenience with a tradeoff: the disclosure of additional personal information.
By storing home address, billing address and credit card information with online merchants, customers avoid the hassle of re-keying the data each time they shop at the site. That works only as long as the customer trusts the merchant to safeguard the data beyond a single transaction. The next step requires an even bigger leap of faith: giving a retailer information about tastes or preferences so the merchant can intelligently recommend goods of likely interest. This saves the shopper time, but it also means upping the trust factor.
Up close and personal
When we dig into consumers’ fears, the real concern is about losing control of personal information. No one wants personal details passed from merchant to merchant-or worse.
The more personal the information entrusted to it by customers, the more careful a retailer must be to protect that trust. Personalization technology carries a heavy privacy burden.
To avoid misperceptions, retailers should explain exactly how volunteered or collected information will be used. The long-term benefits of creating and enforcing such a policy will always outweigh any short-term gains from abusing customer information. Online shoppers are willing and able to make important tradeoffs between convenience and privacy when they’re fully aware of the facts.
Because personalization is deployed “under the covers” on Web sites, the benefits to consumers aren’t readily apparent. Although the technology is sophisticated and the processing involved is usually quite complex, the result is fairly simple.
Faced with a large number of products, online shoppers often can’t find what they want and often don’t even know which products might interest them. If left to scroll through an extensive catalog of offerings with few guides or signposts, most people will leave without buying anything.
But there’s a way to give customers a personal touch without collecting a lot of personal data about them. A technique called collaborative filtering helps cut through the confusion caused by vast product catalogs and picks out merchandise that customers might otherwise miss. By crunching huge volumes of purchasing data, such a system makes intelligent inferences about product groupings that would be difficult to determine by any other means.
A personalization system might find that people who buy a particular book or music CD also tend to buy similar items. Personalization works equally well for nearly any large body of products or services. The system becomes more accurate when customers are willing to provide additional information-product preferences, other interests, even contact data.
Personalization can help customers quickly locate what they’re most interested in seeing, even if it turns out to be a book or CD they’ve never heard about. Surprises that closely match a person’s sense of value are always delightful. Behind the scenes number-crunching leads to the shopper’s great find. And people who leave with great finds are highly likely to come back.