In its second-largest acquisition, Amazon buys the company for $970 million.
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The products that are served by the recommendation engine also reflect where the inventory will be sourced from, with more profitable products served up first. While Horgan says the company still is in the “test and understand” phase of gauging consumer reaction to recommendations, the company’s goal is to deliver product recommendations that are both more profitable-taking into account inventory levels, re-order time and other factors-as well as relevant to its customers.
To date, Indigo has delivered its recommendations mostly through e-mail to its subscriber list. Horgan says that e-mail containing recommendations based on a customer’s past purchases or purchase behavior that is like that of similar customers has produced double the revenue of non-targeted e-mails.
Indigo also does some personalization on the site, with ongoing real-time customer data underlying a “customers who bought this, also bought this” recommendation attached to every item. And it’s leveraging the data gathered about its customers both online and offline for the print catalog it mails twice a year. The first several pages of the catalog vary, presenting products that are personalized to between 30 and 40 customer segments, Horgan says.
And over the next 12 to 18 months, Indigo hopes to enhance the kiosks recently added to its 300 stores to allow its registered customers to swipe their irewards loyalty program card at the kiosk and instantly receive a set of personalized recommendations.
“Over the last several years we have worked hard to try to improve and make recommendations even more relevant to the customers,” Horgan says. “So there is e-mail, there is the bi-annual publication, personalized recommendations are ongoing on the site, and the future vision is the brand-new kiosk program we have just launched in our stores.”
PrezzyBox.com has found yet another way to make use of personalization technology. Using MarketMaestro personalization software from 7 Billion People Inc., the United Kingdom-based gift site takes personalization out on the web to its search ads.
In creating the ads, it uses language most appealing to the customer profiles the software’s analysis shows are most likely to be interested in what the retailer wants to promote for any reason-inventory levels, margin, or in a recent instance, products the retailer wanted to push for a Valentine’s Day promotion.
“We communicate an overall message-we don’t have specific messages for specific products,” says founder and general manager Zak Edwards. “We have tailored the marketing messages to appeal to as many profiles as possible.”
The software creates profiles of the types of customers that visit the site, and this guides writers in creating search ad copy designed to appeal to the top two or three profiles for a given item. Here’s an example: “Get her what every woman wants-the greatest choice of Valentine’s gifts at Prezzybox.”
That search ad would appeal to two types of shoppers, explains CEO Mark Nagaitis. One is the referential shopper who believes that because other women like Prezzybox products, so will the women he’s buying the gift for. The other is the shopper to whom range of choice is most important. In tests, Prezzybox has found it can double its conversion rate on search ads personalized by profile in this way, Edwards says.
7 Billion People also offers another product, WebLegend, which takes site personalization beyond product recommendations. It adapts how a web site’s pages are presented to site visitors in real time, based on how individual visitors like to receive information as determined by how they click through the site.
The software captures visitors’ clickstream data as they enter and move through the site, to create a portrait for each visitor. It uses behavioral psychology to analyze the portraits to identify each visitor’s goals, decision-making methods, buying behaviors and communications preferences.
Within three to five clicks, the software gathers enough information on the visitor to determine a behavioral tendency on at least one of 15 attributes, the vendor says. At that point, it begins to adapt the presentation of site content to fit the visitor’s preferences.
For example, one type of online shopper looking for a digital camera might enter the model name and go directly to the product page, then click straight to the technical specifications. If the shopper comes back to the home page the software would adjust display of the page to his personality, showing a simple search bar with minimal clutter and marketing offers. If this shopper goes to the product page, the technical specs would be prominently displayed and the checkout process would be straightforward without upsells.
By contrast, a shopper who browsed through a few cameras and clicked on a discount link would be presented a different experience, featuring user recommendations, deals and upsells in the checkout process, a style to which this type of shopper is more receptive, the vendor says.
“The deep personalization made possible by WebLegend is allowing our early clients to increase their profits by better serving the customers already coming to their web sites,” Naigitis says. The software already has helped one online marketer, United Kingdom-based car rental agency 121carhire.com, boost conversions, defined as online reservations, by 50%, according to the company.
Both products are delivered as software as a service, hosted by the vendor and accessed via the web, with MarketMaestro starting at $7,000 per month and WebLegend starting at $15,000.
That kind of technology investment is easier to justify if it helps a retailer not only identify consumers who like a particular style, but who are most likely to snap up those 200 slow-moving yellow sweaters that would otherwise have to be sold at a deep discount.
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