Holiday Advice for E-tailers

E-commerce consultant Jack Jia reveals the secrets of improving traffic and getting more sales out of your Web site

With the 2009 holiday shopping season upon us, more retailers—both large and small—are investing in social technologies to mimic digitally the Mom-and-Pop feel consumers experience when they walk into their local privately owned hardware store or clothing boutique. Here are five rules that savvy online retailers already have in place heading into Nov. 30, aka Cyber Monday, the day Internet holiday shopping traditionally kicks into high gear. For those of you not yet incorporating these practices, fear not. They're easy to implement and each can help your business year-round.

Step 1: Let like-minded customers merchandise your products for you.

Since the beginning of time, the societal norm has been to trust experts—our teachers, doctors, lawyers, etc. It was the best strategy available when we could interface with only a few people at a time. The increasingly social nature of the Web has changed this dynamic. James Surowiecki reveals in his best-selling book, The Wisdom of Crowds, something that scientists have known for years: Random groups of informed people can predict outcomes far more accurately than any individual expert. Since that time, companies such as Netflix (NFLX) and Amazon (AMZN) have popularized the use of recommendation engines to identify new patterns in behavior as customers browse and purchase online.

Leveraging crowd wisdom is especially important in content—and product-rich "long tail" sites where manual merchandising and editorializing is neither cost- nor time-effective. Long tail is the concept of selling fewer units of many different special-interest products, as opposed to selling large quantities of fewer popular products, such as the iPhone (AAPL). Instead of asking a merchandiser to define the thousands of niche segments along the long tail, why not let the crowd of site visitors self-define those segments? By tapping into the wisdom of these like-minded shoppers, your customers can effectively recommend products to one another and actually sell for you.

Step 2: Pinpoint customer sentiment ahead of the curve.

Leading industry analysts at market research firms Gartner, based in Stamford, Conn., and Forrester Research, in Cambridge, Mass., have both been giving a lot of attention to the concept of studying customer sentiment to make predictions on future consumer trends. Forrester calls this "customer intelligence," and Gartner has dubbed it "pattern-based strategy" (PBS). According to Gartner, PBS "provides a framework to seek, model, and adapt to leading indicators, often-termed "weak" signals, that form patterns in the marketplace. This is something that transactional-based systems, such as business intelligence (BI) and complex event processing (CEP), simply haven't been able to deliver.

Predictive technologies have helped organizations become much more efficient by automating their interactions with customers. These applications, however, have historically prioritized the wrong set of indicators, often identifying consumer trends weeks, if not months, too late. It's a well-known fact that e-commerce transaction data lag other types of purchasing indicators― such as comparison shopping or length of time the computer mouse lingers on a product ― by months. Only by tapping into the browsing behaviors of shoppers visiting your Web site is it possible to detect early signals, spot trends, and develop new selling strategies before your competitors.

Step 3: Blend community wisdom with expert control.

Although the community knows best in most cases, there are instances when the experts need to exercise precise control over how to promote and position products in their online storefronts. Examples include removing a particular recommendation on an out-of-stock product, or highlighting recommendations about products guaranteed to increase your bottom line. So blend community-driven recommendations with expert tuning that factors margins, inventory levels, promotions, breaking news, and cross-channel content linking.


Step 4: Don't be blind to community bias.

Explicit crowd-sourcing techniques, such as ratings and reviews, have become popular for creating user-generated recommendations online. In theory, this approach has few flaws. If every single person who came to the site weighed in with opinions on every product, you would get a perfect representation of consumer attitudes. But here's the rub: Not everyone contributes. At the end of the day, 99% of the population remains unspoken for.

In reality, there are certain types of people more willing to make their voices heard, particularly when exerting effort is involved (such as writing a review). I categorize the most vocal and misleading group of contributors as squeaky wheels. This could be those people who simply like to complain—or it could be any one of us after a negative experience. Negative experiences tend to stand out more than positive ones and motivate us to take action. Overly positive reviews happen, too, so you ultimately get a representation of the community that is biased to the two extremes.

Another common form of bias occurs when Web site owners "game" the system, using shills to write positive comments. If you have a book coming on the market, your publisher will ask you to recruit friends to write reviews as part of the promotional effort. In my opinion, gaming such as this is actually the rule, rather than the exception, on Amazon and other media sites where products have authors or artists and personal connections abound.

Step 5: Listen to your silent majority while engaging your more vocal minority.

Ratings and user-generated reviews, though often misleading, have become an expected part of the online experience and encourage deeper engagement. However, user-generated review systems must also find ways to inform ratings based on valuable sentiment and implicit feedback gathered from the vast majority of their site visitors, not just the loud minority. With a truly integrated approach to recommendations that blends both implicit and explicit feedback, companies can expect to improve engagement and overall user experience by directing site visitors to the best products possible.

Whether shopping online or offline, consumers want to re-create the feeling of walking into a friendly store or neighborhood boutique. They want the owners to have intimate knowledge about what's on their shelves and which products similar shoppers have found most useful. By following these simple rules, online retailers can get closer to emulating this experience than ever before. The end result will be better conversions (turning Web visitors into purchasers), higher average order values, and ultimately bigger profits to celebrate in the New Year.

Before it's here, it's on the Bloomberg Terminal.