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Lotte.com boosts retail sales, satisfaction with SAS® for Customer Experience Analysis

Understanding why customers abandon shopping carts results in $10 million sales increase for distributor

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 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. 

With almost 1 million website 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 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 website visitor numbers (UV), page view (PV) status of site visitors and purchasers, 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 and 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 website. 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. 

Since implementing SAS for Customer Experience Analytics, Lotte.com has seen many benefits:

A jump in customer loyalty
A large amount of sophisticated activity information 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, purchase completion) compared to actual visitors for each campaign type (affiliation or e-mail, banner, key words and others), so detailed analysis of channel effectiveness is possible. Additionally, it can confirm 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 location 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 database 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 database captures customer demographic information, shopping cart size and conversion rate, number of orders and number of attempts.

By analyzing which stage of the ordering process deters the most customers and fixing those stages, conversion rates can be increased. Previously, analysis was done only on placed orders. By analyzing the movement pattern of visitors before ordering and at the point where breakaway occurs, customer behavior can be forecast and sophisticated marketing activities can be undertaken. Through a pattern analysis of visitors, purchases can be more effectively 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 customer's behaviors, 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 customer service improvements and target marketing subjects, and this has aided the success of a number of campaigns."

However, the most significant benefit of the system is gaining insight into individual 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 better customer experience can now be achieved.

Plus, when SAS for Customer Experience Analytics was implemented by Lotte.com's largest overseas distributor, it resulted in a first-year sales increase of 8 million euros (US$10 million) by identifying the causes of shopping-cart abandonment.

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Lotte.com

Challenge:
How to better understand customer behavior online so sophisticated targeted marketing can be undertaken and the customer online experience improved
Benefits:
Identifying the causes of shopping-cart abandonment resulted in a first-year sales increase of $10 million for Lotte.com's largest overseas distributor. With SAS, Lotte.com reaches high-profit customers to influence purchases, and it responds quickly to changes in visitor patterns.

By finding out how each customer group moves on the basis of the data, it is possible to determine customer service improvements and target marketing subjects, and this has aided the success of a number of campaigns.

Jung Hyo-hoon

Assistant General Manager

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