Application Case 8.3 Understanding Why Customers Abandon Shopping Carts Results in $10 Million Sales Increase Lotte.com, the leading Internet shopping mall in Korea with 13 million customers, has developed an integrated Web traffic analysis system using SAS for Customer Experience Analytics. As a result, Lotte .com has been able to improve the online experi- ence for its customers, as well as generate better returns from its marketing campaigns. Now, Lotte .com executives can confirm results anywhere, any- time, as well as make immediate changes. With almost 1 million Web site visitors each day, Lotte.com needed to know how many visitors were making purchases and which channels were bringing the most valuable traffic. After reviewing many diverse solutions A Jump in Customer Loyalty and approaches, Lotte.com introduced its integrated Web traffic analysis system using the SAS for Customer Experience Analytics solution. This is the first online behavioral analysis system applied in Korea. With this system, Lotte.com can accurately measure and analyze Web site visitor numbers (UV), page view (PV) status of site visitors and purchas- ers, the popularity of each product category and product, clicking preferences for each page, the effectiveness of campaigns, and much more. This information enables Lotte.com to better understand customers and their behavior online, and conduct sophisticated, cost-effective targeted marketing. Commenting on the system, Assistant General Manager Jung Hyo-hoon of the Marketing Planning Team for Lotte.com said, As a result of introducing the SAS system of analysis, many new truths were uncovered around customer behavior, and some of them were inconvenient truths. He added, Some site-planning activities that had been undertaken with the expectation of certain results actually had a low reaction from customers, and the site planners had a difficult time recognizing these results. benefits Introducing the SAS for Customer Experience Analytics solution fully transformed the Lotte.com Web site. As a result, Lotte.com has been able to improve the online experience for its customers as well as generate better returns from its marketing campaigns. Now, Lotte.com executives can confirm results anywhere, anytime, as well as make immediate changes. A large amount of sophisticated activity informa- tion can be collected under a visitor environment, including quality of traffic. Deputy Assistant General Manager Jung said that by analyzing actual valid traffic and looking only at one to two pages, we can carry out campaigns to heighten the level of loyalty, and determine a certain range of effect, accordingly. He added, In addition, it is possible to classify and confirm the order rate for each channel and see which channels have the most visitors. Optimized Marketing Efficiency Analysis Rather than just analyzing visitor numbers only, the system is capable of analyzing the conversion rate (shopping cart, immediate purchase, wish list, pur- chase completion) compared to actual visitors for each campaign type (affiliation or e-mail, banner, keywords, and others), so detailed analysis of chan- nel effectiveness is possible. Additionally, it can con- firm the most popular search words used by visitors for each campaign type, location, and purchased products. The page overlay function can measure the number of clicks and number of visitors for each item in a page to measure the value for each loca- tion in a page. This capability enables Lotte.com to promptly replace or renew low traffic items. Enhanced Customer Satisfaction and Customer Experience Lead to Higher Sales Lotte.com built a customer behavior analysis data- base that measures each visitor, what pages are visited, how visitors navigate the site, and what activities are undertaken to enable diverse analysis and improve site efficiency. In addition, the data- base captures customer demographic information, shopping cart size and conversion rate, number of orders, and number of attempts. By analyzing which stage of the ordering pro- cess deters the most customers and fixing those stages, conversion rates can be increased. Previously, analysis was done only on placed orders. By analyz- ing the movement pattern of visitors before ordering and at the point where breakaway occurs, customer

behavior can be forecast, and sophisticated market- ing activities can be undertaken. Through a pattern analysis of visitors, purchases can be more effec- tively influenced and customer demand can be reflected in real time to ensure quicker responses. Customer satisfaction has also improved as Lotte .com has better insight into each customers behav- iors, needs, and interests. Evaluating the system, Jung commented, By finding out how each customer group moves on the basis of the data, it is possible to determine cus- tomer service improvements and target marketing subjects, and this has aided the success of a num- ber of campaigns. However, the most significant benefit of the system is gaining insight into indi- vidual customers and various customer groups. By understanding when customers will make purchases and the manner in which they navigate throughout the Web page, targeted channel marketing and bet- ter customer experience can now be achieved. Plus, when SAS for Customer Experience Analytics was implemented by Lotte.coms largest overseas distributor, it resulted in a first-year sales increase of 8 million euros (US$10 million) by iden- tifying the causes of shopping-cart abandonment.

What were the challenges, the proposed solution, and the obtained results?