| Page 1 |T O M M I L L E R | V I C E P R E S I D E N T, B U S I N E S S D E V E L O P M E N T T W M I L L E R@M E R K L E I N C.C O M | 312.952.0255 M E R K L E I N C.C O M

CASE STUDYMEASURING THE IMPACT OF CUSTOMER LOYALTY PROMOTION

| Page 2 |

CASE STUDY | MEASURING THE IMPACT OF CUSTOMER LOYALTY PROMOTION

S T R A T E G Y A N A L Y T I C S T E C H N O L O G Y M E D I A C R E A T I V E

SituationA specialty fashion retailer wanted a next generation CRM solution to support retail and direct to consumer marketing for several brands. The retailer enjoyed YOY revenue and profit growth for several years. However, senior management believed they could increase the pace of growth and enhance their successful catalog and ecommerce businesses through improved customer engagement and cross-channel integration. They engaged Merkle’s strategy, analytics and technology services to achieve these goals.

ApproachMerkle designed and implemented a CRM solution with the following features:

• 360° customer view across key data dimensions, including sales (retail and web), call center data, web, promotion history, email behavioral data, demographics, etc.

• Retail data model that supports specialized business requirements critical to the industry• Single version of truth and business rules across campaign, BI and analytic environments• Management of data from over 150 disparate source systems and 25,000 data files• 1200 pre-computed aggregate customer attributes for analytics, campaigns and reporting• Web-services application to manage offer redemption• POS reverse append solution to enhance identification of retail consumers

This includes more than 20MM unique customers and 200MM orders. It has enabled a one-stop-shop approach to all aspects of marketing execution (catalog, email and SMS channels combined with customer analytics) across all brands and provided an integrated view of inbound metrics and the ability to measure ROI at the customer level.

Results – Example 1The client asked Merkle to improve performance of the customer catalog, a major driver of both direct and retail sales. Leveraging the new database, Merkle created an enhanced catalog model and tested it against the incumbent model developed by a prior vendor. Merkle’s model had the following impact:

• Response Rate: Increased by 136%

Dollars per Book: Increased by 237% Merkle’s advanced analytics capabilities and access to integrated customer data in a single environment were keys to this success.

| Page 3 |T O M M I L L E R | V I C E P R E S I D E N T, B U S I N E S S D E V E L O P M E N T T W M I L L E R@M E R K L E I N C.C O M | 312.952.0255 M E R K L E I N C.C O M

Results – Example 2The technology solution also enabled a variety of impactful customer analyses. For example, Merkle helped the client understand the impact of providing a special offer on the website for all loyalty members. Measurement of the program was difficult because the company made a business decision to make the offer available to all loyalty members, making it impossible to implement a formal statistical test. Despite this difficulty, the marketing team needed a means to assess the offer’s impact and determine whether to implement the program in the future. Merkle’s Quantitative Solutions Group (QSG) developed a rigorous statistical methodology to provide the required information in the absence of a formal test. As a result, the client will be able to understand impact of the offer on online and offline loyalty sales.

Merkle integrated multiple data sources and developed predictive models to estimate the impact of the loyalty promotion on the client’s bottom line. The key analytical component of the solution was a set of advanced econometric time-series models that estimated baseline loyalty sales in the absence of the promotion. Significant variables included loyalty specific web traffic (separated via web log data), seasonal effects, promotional offers and historical sales. Merkle calculated the effect of the promotion as the difference between actual sales and projected sales based on the time-series models. The same solution can be extended and leveraged to accomplish similar measurement tasks in the future.

Merkle’s approach provided an accurate estimate of the impact of the promotion and return on investment. The client used the results to inform their ongoing loyalty promotion strategy on the website and to argue successfully for incremental budget for additional loyalty-related promotions. Merkle is currently working on ROI assessments for other aspects of the site.

For More Information, Contact:Tom Miller Vice President, Business Development twmiller@merkleinc.com 312.952.0255

| Page 4 |

CASE STUDY | MEASURING THE IMPACT OF CUSTOMER LOYALTY PROMOTION

S T R A T E G Y A N A L Y T I C S T E C H N O L O G Y M E D I A C R E A T I V E

8/2011

JOIN IN THE CONVERSATION

linkedin.com/company/merkle

facebook.com/merkleinc

twitter.com/merklecrm

flickr.com/photos/merklecrm

youtube.com/user/merklecrm

www.merkleinc.com