In the next 17 months, it expects 10% of its B2B customers will be transacting on the web, an executive says.
Retailers work on creating enticing cross-sells online — and find it’s not easy.
Effective cross-selling and upselling is a mixture of art and science-coming up with that certain item a customer just can’t refuse to buy. But most online merchants have yet to master the craft. Although 76% of online retailers use at least one method of cross-selling or upselling, only 9% of online buyers say they used site suggestions, according to Jupiter Research.
“Retailers are trying their best but it’s hard to get a lot of traction out of cross-sells and upsells,” says Patti Freeman Evans, Jupiter Research analyst. “Consumers are not making impulse buys.”
But that task may become easier with the increasing use of analytics software. These new automated programs are helping retailers refine the cross-selling/upselling process, leading to additional sales. That’s the case at Sierra Trading Post, which began using an automated cross-selling and upselling program from web analytics company Offermatica Corp. a little over a year ago.
The Offermatica product replaced a manual system that used “a best guess method” on select items that produced mixed results, says Chris Lange, web operations manager. And while there were some initial problems with the automated process that required fine-tuning, the results were gratifying: An increase in average order value of 2% to 5% and “sometimes greater,” Lange says.
Online jewelry retailer Ross-Simons has had similar results with an automated program from Ecometry Corp. “We do in the neighborhood of $1 million a year in upsells so it’s a pretty nice program,” says Terry Matthies, vice president of information technology at Ross-Simons. Ross-Simons had $63 million in Internet sales in 2005.
Automated programs use a variety of methods to generate cross-selling and upselling recommendations, and are being integrated into e-commerce platforms, web analytics programs, site search, and other types of software commonly used by online retailers. Some vendors, such as Ecometry, also offer stand-alone cross-selling and upselling modules.
Recommendations are based on a broad range of information, including a customer’s past purchases as well as overall customer purchase patterns. Some programs track product performance, including which items customers most often buy together, or develop recommendations based on the combination of items that an individual places in the shopping cart.
And in some cases, automated cross-sell and upsell programs will take into account click-stream behavior, customer reviews, and profit margins of items.
Ecometry takes two approaches to cross-selling and upselling, says Brian Dean, vice president of marketing and strategy. The first is a merchandise-driven strategy, in which the retailer selects the cross-sell and upsell candidates for each item. The retailer can configure the system to make substitute suggestions in case an item sells out.
At Ross-Simons, which uses Ecometry’s commerce suite, the retail staff identifies upsell candidates at the web site and call center based on factors such as pricing and quantities available, Matthies says. The information is entered into the system by the retailer’s operational staff.
The second approach is analytics-based-recommendations are based on what previous customers with similar shopping patterns purchased. “It’s similar to what you find on Amazon, which says ‘people who purchased this also liked this,’” Dean says.
Ecometry’s software builds “relative strength indexes” on possible cross-sell and upsell candidates based on the items a customer puts in the shopping cart, and updates the index each time the customer adds an item. That data is used in tandem with information on customer purchasing patterns and product preferences to produce recommendations.
Ecometry’s system uses a common engine for the web, retail store and call center and stores information on a customer’s purchases in all three channels in a central data warehouse. “As you add things to the cart, it’s building a composite affinity calculation for different product categories and individual products,” Dean says. “When you’ve got three items in there, it has a different relative strength index for a product category or a product than if you just had one.”
For example, if a customer puts two country music CDs and a classical CD in a shopping cart, the system most likely will recommend another country album, he says.
The Ecometry system allows retailers to give top priority to the merchandise approach to recommendations, Dean says. “If you don’t have a merchandise rule, than you go to relative strength indexes,” he says.
Ecometry’s system also filters out hugely popular items that could skew results, Dean says. For example, a newly released DVD might show up in shopping carts with a large variety of totally unrelated items.
The system also filters out frequently purchased items, such as batteries. “You don’t want to recommend batteries all the time even though batteries are purchased with a whole host of things,” Dean says. “There are certain things you filter out just because you don’t need to tell people about those things.”
Offermatica’s system uses merchant input in setting up the system, but then uses its Lazy Loading technology to automatically build a database, says Erin Casey, marketing manager. With Lazy Loading, product information automatically is sent to the database at the same time an order confirmation page is sent to the customer.
“As people purchase things, the product information is passed back to our system,” Casey says. “It makes it very easy for the merchant. They don’t have to upload information-the database is automatically being built for them.”
Automated systems don’t necessarily lock retailers into one format. The Offermatica system can make recommendations in categories such as best seller, best seller in category, most viewed or in whatever fashion the merchant chooses. As with Ecometry, merchants can designate which products get top priority. For example, a retailer might want to push a seasonal item to the top of the list. “The merchant is very important in this process,” Casey says.
With the Ecometry system, retailers also can set conditions for cross-sells and upsells. “Some people want to use product recommendations to move overstock-it’s a way of avoiding markdowns,” Dean says. “Other people want to go with a static list-they want to put items on sale for a week.”