Lens Direct is projecting year-over-year sales growth of more than 40% this year.
When a consumer refers to "my store," she means a merchant who knows her tastes and can suggest items she'd like. Improved technology makes it easier than ever for online retailers to offer that kind of personalized service.
In the world of bricks and mortar it can take years for a shop owner to get to know her customers well enough to present them products likely to delight them and keep them coming back. On the Internet, it's becoming possible for retailers to offer well-targeted recommendations to even first-time visitors, and to present the returning shopper with items uncannily tailored to her preferences.
That's because web personalization technology is evolving and improving rapidly. Previous generations of personalization systems were geared toward making suggestions to large groups of shoppers, such as everyone who arrives at a retail site from a comparison shopping engine or by searching for a particular term. While good at getting consumers to products of interest in fewer clicks than if they searched for them without assistance, the technology fell short of the one-to-one selling that an experienced in-store salesperson can provide.
Today, advances in personalization technology and greater availability of information about consumer preferences are making it easier and more affordable for retailers of all sizes to create the kind shopping experiences t hat make a consumer think of an e-retail site as "my store." What's more, the latest personalization systems are more effective in producing profitable sales because they can more easily connect to marketing, inventory and customer service applications. Retailers can extend personalized selling to every consumer touch point, including on-site, e-mail, online banner ads, social networks, and personal mobile devices. By integrating these channels, retailers can realize much greater lifetime value from customers by bringing them back more often.
"Consumers come to a web site and leave without buying something 10 times more often than they do at a physical store," says Bob Cell, CEO of My Buys Inc., provider of personalized product recommendation services. "Personalization is about recognizing and understanding a consumer's individual preferences and suggesting products that will appeal to their individual preferences across touch points, as opposed to broadcasting messages to a crowd hoping they have similar preferences. The higher the level of personalization, the less likely the consumer is to leave without making a purchase."
Anonymous no more
Data represent the foundation of any successful personalization strategy, and today retailers have access to more consumer data than ever. One source of a wealth of information is the public profiles posted by consumers on Facebook.
Retailers can access this information to learn about a consumer's brand and product preferences, her favorite color, birthday and more. A merchant can use that information to present offers on its Facebook fan page tailored to that individual. The offer can be matched to an individual by requiring some sort of identification process, such as asking her to log onto the fan page so there is no mistake about her identity.
"Sophisticated web shoppers expect to be target marketed," says Diane Buzzeo, CEO and founder of Ability Commerce, provider of integrated e-commerce and personalization solutions. "Consumers that regularly go to a retailer's Facebook page tend to be very loyal customers and not likely to view the use of personal information from their public Facebook profile for a personalized shopping experience as intrusive."
Retailers can also use consumer information found on Facebook to create personalized e-mail campaigns. "If the consumer has opted in to the retailer's e-mail list, then the retailer should send a birthday e-mail that includes special offers based on their preferences," adds Buzzeo. "As retailers get more involved with social networking, personalization is going to become a bigger part of their social networking strategy."
Making recommendations based on the preferences of a consumer's Facebook friends is also a powerful personalization tool. For example, if a consumer connects to a retailer's web store through Facebook and purchases a dress, the retailer can show her accessories that her Facebook friends bought when they purchased a similar style of dress. Just as retailers gather product preferences from a customer's Facebook profile, they can do likewise for a customer's Facebook friends.
"Recommending products from a consumer's network of friends on Facebook carries a higher level of trust and relevancy than simply saying people who bought this item also bought these items," says Eric Tobias, president of iGoDigital, provider of personalization and recommendation engines. "Consumers that are fans of a retailer or a brand on Facebook tend to buy more often and generate higher tickets. Retailers ought to be looking for ways to leverage this trend as part of their personalization strategy."
Learn on the fly
For all the consumer information available through Facebook, retailers can also learn a lot about an individual shopper by paying close attention to how she moves through a web site. Personalization engines anonymously follow consumer clickstreams and navigation paths by attaching a tracking cookie to the consumer's web browser. The tracking cookie also identifies the consumer during future visits.
Categories and products viewed, site search terms entered and how long a consumer spends viewing a page all provide important clues to her preferences and goals. The same goes for clickstreams, which can indicate if a consumer is comparison shopping by toggling back and forth between two brands or price points.
Because consumer preferences are constantly evolving, the fresher the data the more relevant it is for making product recommendations.
"How a consumer behaves while shopping on a retailer's site is the most accurate indicator of their intent," says Meyar Sheik, CEO and co-founder of Certona, provider of personalization software. "Once a history has been built on a customer, retailers can compare it to their current movement through the site to distinguish what's different about their current behavior from the previous shopping session. As those distinctions are made product recommendations can be made accordingly."
A consumer that is looking at high-definition televisions in a price range of $500 to $700, for instance, is unlikely to want to see suggestions for televisions priced at $1,500 and up, even though he may have previously purchased items in that price range. "It is important to recognize consumer preferences as they are revealed during the current shopping session before making suggestions," says Sheik.