Retailers lose 8-15% of annual sales to merchandise returns, costing over $165 billion annually in return expenses. Advanced analytics can help optimize return policies and reduce fraudulent returns by analyzing customer return patterns and behaviors. This can enhance retailer profits by up to 5% of annual sales through minimizing expenses, boosting repeat sales, and detecting return abuse.

1. UNLOCKING VALUE IN
MERCHANDISE RETURNS
Over 8 – 15 % of a Retailers Sales are strategies leveraging transaction information
returned for various reasons. This can cause and the best of analytics can help manage
both a negative sales impact, and an Returns leading to a significant boost to the
increase in expenses. However smart bottom line.
Best Customers Identify your best and most profitable
1.5%
customers. Customize your Returns
Next Best
Customers
policy to maximize revenues and repeat
2.0% sales
Retail Sales Returns
92% 8% Average Customers
3.0%
Fraud / Abuse
Detect Fraud and Return Policy abuse
1.5% using advanced analytics
Advanced Analytics leveraging Customer behavior & historical transaction data can
enhance a Retailers bottom line by as much as 5% of its annual sales
• Fraudulent and abusive returns cost
retailers approximately $10-15B annually,
• Handling returns costs US retailers over
accounting for nearly 10% of the return
$165B each year
dollars
• 30% of the top 100 retailers actively use a
• Expenses related to returns such as product
returns solution that can verify if the
repackaging, markdowns and item
receipt is valid, but cannot intelligently
disposition cost retailers even more
advise the store about the validity of the
return
Minimize Fraudulent Minimize additional
Returns expenses related to returns
Opportunities in
Returns
Treat Returning Customers Encourage Cross-channel
Differentially synergies
• Handling product returns should be an
important component of a retailers CRM • A cross channel return policy will create
strategies cross-selling opportunities. For example,
retailers can encourage customers to shop
• Retailers should capitalize on product in stores when they come to return online
return occasions and treat them as and catalog orders
additional touch points to strengthen their
relationship with customers

2. MERCHANDISE RETURNS -
ANALYTICS DRIVING PROFITABILITY
OPTIMIZE RETURNS POLICIES BY
REDUCE FRADULENT RETURNS
ANALYZING RETURN PATTERNS ACROSS
USING PREDICTIVE MODELS
CUSTOMERS & PRODUCTS
Chien-Chih Yu and Cheng-Su Wang The Retail Equation
A Hybrid Mining Approach for Optimizing Returns Policies in e Retailing Unlocking the Value in Return Transactions
About Marketelligent
Marketelligent provides data analytics-based consulting industries - Retail Banking, Consumer Packaged Goods,
and outsourcing services that help you make smarter Consumer Retail, Telecom and Media. We offer an
business decisions. The firm is backed by senior affordable global delivery model leveraging the best of
professionals with experience across Consumer focused domain expertise and analytic capabilities.
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