Returns are an inevitable part of the business for all merchants. While handling returns can be challenging, it is essential to ensure customer satisfaction and prevent any negative impact on future purchases. According to industry experts, returns present an opportunity not only to improve the overall returns process but also to enhance customer loyalty.
Doriel Abrahams, the head of risk at Forter, and Richard Kostick, the CEO of 100% Pure, suggest that the same data used to combat fraud can be utilized to enhance the returns process. By doing so, merchants can not only reduce fraudulent returns but also build stronger relationships with their customers.
In the digital age, certain trends have emerged that contribute to the increasing number of returns. One such trend is bracketing, where online shoppers purchase items in multiple sizes and return the ones that do not fit. Additionally, studies have found that more than half of consumers admit to returning items after minimal use.
While returns can be legitimate, Abrahams estimates that approximately 15% of returns are actually fraudulent or abusive. Fraudulent returns range from returning empty boxes to returning products replaced with bricks. Some scammers even resell the refunded items for personal gain.
For merchants, returns come at a significant cost. Companies like 100% Pure, which focuses on cosmetics, face the challenge of not being able to restock used inventory. As a result, a significant portion of returned items must be destroyed. To address this issue, 100% Pure has implemented a policy where consumers can choose to keep their order instead of returning it. However, this has led to a different type of fraud where customers request refunds while keeping the cosmetics.
To combat fraudulent returns, 100% Pure has shifted to a high-touch returns process. Customer service representatives at the company take detailed notes on customers they suspect of abusing the returns process. These customers are required to ship the products back at their own expense, reducing the occurrence of fraud. Repeat offenders are blacklisted from doing business with the company. This approach has resulted in a returns rate of just 2%.
While this personalized approach works well for smaller companies, it becomes more challenging to scale when dealing with millions of customers. In such cases, data plays a crucial role in distinguishing between genuine customers and fraudulent actors. Forter’s platform, for example, uses generative artificial intelligence to uncover users’ identities and link them to specific behaviors. This technology helps identify good customers while automating the returns process, eliminating the need for manual intervention.
By analyzing data, merchants can also gain insights into consumer behavior and inventory management. High return rates may indicate flaws in products, packaging, or changes in consumer preferences. This valuable information can inform future product development and enhance supply chain sustainability.
As businesses navigate the complex landscape of returns, data sharing and advanced technologies will play a key role in separating good customers from fraudulent actors. However, the battle against fraudulent returns is ongoing and requires continuous adaptation.
In conclusion, managing returns is not just about reducing fraud but also about improving customer loyalty. By leveraging data analytics and cutting-edge technologies, merchants can streamline the returns process, identify fraudulent activities, and build stronger relationships with their customers.
FAQs
1. Can returns negatively impact customer loyalty?
Yes, if returns are not handled effectively, they can disappoint customers and discourage them from shopping with a company again.
2. What are some examples of fraudulent returns?
Fraudulent returns can include returning empty boxes, returning products that have been replaced with other items, or even reselling refunded items for personal gain.
3. How can merchants reduce fraudulent returns?
Merchants can implement measures such as requiring customers to ship products back at their own expense, keeping detailed records of suspect customers, and blacklisting repeat offenders.
4. How can data analytics help in managing returns?
Data analytics can provide insights into consumer behavior, inventory management, and identifying fraudulent activities, allowing businesses to make informed decisions and improve their processes.
Sources:
– Forter: https://www.forter.com/
– 100% Pure: https://www.100percentpure.com/
Returns in the retail industry are an important aspect that merchants must address to ensure customer satisfaction and prevent negative impacts on future purchases. According to industry experts, effectively managing returns not only improves the returns process but also enhances customer loyalty.
One way to optimize the returns process is by utilizing the same data used to combat fraud. Doriel Abrahams, the head of risk at Forter, and Richard Kostick, the CEO of 100% Pure, suggest that leveraging data analytics can help reduce fraudulent returns and establish stronger relationships with customers. By analyzing data, merchants can identify patterns and behaviors that indicate fraudulent activities, allowing them to take appropriate measures.
Several trends in the digital age contribute to the increasing number of returns. Bracketing is one such trend where customers purchase multiple sizes of an item and return the ones that do not fit. Additionally, studies have found that over half of consumers admit to returning items after minimal use. These trends highlight the importance of implementing strategies to combat fraudulent returns.
Approximately 15% of returns are estimated to be fraudulent or abusive. Fraudulent returns can range from returning empty boxes to returning products replaced with bricks. Some scammers even resell the refunded items for personal gain. This poses a significant challenge and cost to merchants, especially when dealing with industries where restocking used inventory is not possible, such as cosmetics.
Companies like 100% Pure, which focuses on cosmetics, struggle with the inability to restock returned items. As a result, a significant portion of returned cosmetics must be destroyed. To address this, the company has implemented a policy where customers can choose to keep their order instead of returning it. However, this has led to a different type of fraud where customers request refunds while retaining the cosmetics.
To combat fraudulent returns, 100% Pure has implemented a high-touch returns process. Customer service representatives at the company closely monitor customers suspected of abusing the returns process, taking detailed notes to keep track of their behavior. These customers are required to bear the shipping costs when returning products, reducing the occurrence of fraud. Repeat offenders are blacklisted from doing business with the company. This personalized approach has resulted in a low returns rate of just 2%.
While this approach works well for smaller companies, scaling it becomes more challenging when dealing with a large customer base. In such cases, leveraging data becomes crucial in distinguishing between genuine customers and fraudulent actors. Forter’s platform, for example, uses generative artificial intelligence to uncover users’ identities and link them to specific behaviors. This technology helps identify good customers while automating the returns process, eliminating the need for manual intervention.
Data analytics also provide valuable insights into consumer behavior and inventory management. High return rates may indicate flaws in products, packaging, or changes in consumer preferences. This information can inform future product development and enhance supply chain sustainability.
As businesses navigate the complexities of managing returns, data sharing and advanced technologies will play a crucial role in separating genuine customers from fraudulent actors. However, the battle against fraudulent returns requires continuous adaptation and the integration of cutting-edge technologies.
In conclusion, effectively managing returns is not just about reducing fraud but also about improving customer loyalty. By leveraging data analytics and employing innovative technologies, merchants can streamline the returns process, identify fraudulent activities, and build stronger relationships with their customers.
1. Can returns negatively impact customer loyalty?
Yes, if returns are not handled effectively, they can disappoint customers and discourage them from shopping with a company again.
2. What are some examples of fraudulent returns?
Fraudulent returns can include returning empty boxes, returning products that have been replaced with other items, or even reselling refunded items for personal gain.
3. How can merchants reduce fraudulent returns?
Merchants can implement measures such as requiring customers to ship products back at their own expense, keeping detailed records of suspect customers, and blacklisting repeat offenders.
4. How can data analytics help in managing returns?
Data analytics can provide insights into consumer behavior, inventory management, and identifying fraudulent activities, allowing businesses to make informed decisions and improve their processes.