Maximizing Profit and Customer Satisfaction: Understanding and Reducing Online Returns

It's always fun to indulge in shopping. Be it a pink jumpsuit or the latest Samsung model on Amazon, one can always get it. However, after going on a random shopping spree, we often realize that the neon green pant that cost us a fortune was not that good of a decision.

Question: Would you choose to order a cute pair of Nike shoes from an Instagram ad with a 30% discount or from Nike's official website with no such offer?

Answer: Read the blog to find out. 

Online shopping is fun, but what happens when our purchase falls short? This is where cognitive dissonance comes in, influencing our post-purchase behavior. In this blog, we'll explore how cognitive dissonance relates to online returns and how understanding these processes can lead to better shopping decisions and a more satisfying experience.

What do you mean by Cognitive Dissonance, Post-Purchase Behavior and Return?

Shopping psychology is fun—let's explore! You're browsing Amazon and see a lovely dress you must have. But when it arrives, it doesn't fit. Now what? It's beautiful, yet it doesn't meet your expectations. This dilemma is cognitive dissonance. Next comes post-purchase behavior. You might keep it even if the dress doesn't fit. However, it will be wasted. You can return it; sorry it didn't work out, but relieved the cognitive dissonance is gone. But there's more! Online returns are different. You may have to pay postage, go through a lengthy return process, or worry about the shop accepting the return. These factors may affect your dress purchase and future shopping with that retailer.

Cognitive dissonance, online refunds, and post-purchase behavior all affect shopping. By understanding these psychological processes, we can make more informed and pleasant shopping decisions that match our values. And who knows, we might even find the right dress!

Learn about A/B Testing

Cognitive Dissonance

Cognitive dissonance is when our brain is confused by simultaneously holding two opposing beliefs or attitudes, causing discomfort.

What is the Role of Cognitive Dissonance in Online Shopping?

When people shop online, they often have to make decisions based on incomplete or uncertain information, such as product descriptions, reviews, and images. After purchase, they may experience cognitive dissonance if the product does not meet their expectations or read negative reviews or other information that conflicts with their initial beliefs or attitudes.

Cognitive dissonance influences online shopping decisions and rationalization. Understanding this phenomenon can help retailers anticipate and address cognitive dissonance and reassure and validate customers after purchases.

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Online retailers can use cognitive dissonance to reassure and validate customers after they buy. For example, they may send a purchase confirmation email or message with product or delivery details. They may also encourage customers to write positive reviews or post on social media to reinforce their decision and reduce cognitive dissonance.

How cognitive dissonance affects the return of goods and, thus, business?

Here are some ways cognitive dissonance affects the return of goods and business:

• Delayed Returns
• Reduced Customer Satisfaction
• Negative Reviews
• Increased Costs

Delayed Returns ​

Reduced Customer  Satisfaction

Negative Reviews

Increased Costs

Metrics to Track Cognitive Dissonance

Return Rate

• Definition: The percentage of products that customers return after purchase.
• What it tracks: Return rate can be used to track cognitive dissonance, as it may indicate that customers experienced conflicting thoughts or emotions about the product after making the purchase.

Formula: Return Rate = (Number of Returns / Total Number of Sales) x 100%

Customer Feedback

• Definition: The opinions, attitudes, and experiences of customers with a product or service.
• What it tracks: Customer feedback can be used to track cognitive dissonance, as it provides insights into the thoughts and emotions that customers experience after making a purchase.

Formula: There is no specific formula for customer feedback, as it can be collected through various methods such as surveys, social media monitoring, and customer reviews.

Customer Satisfaction

• Definition: A metric that measures how happy customers are with a product or service.
• What it tracks: Customer satisfaction can be used to track cognitive dissonance, as customers who experience conflicting thoughts or emotions about a product may be less satisfied with their purchase.

Formula: Customer Satisfaction Score = (Total Positive Responses / Total Responses) x 100%

Abandoned Cart Rate

• Definition: The percentage of customers who add items to their shopping cart but do not complete the purchase.
• What it tracks: If customers frequently abandon their shopping carts before completing a purchase, it may indicate that they experience cognitive dissonance during the decision-making process.

Formula: Abandoned Cart Rate = (Number of Abandoned Carts / Total Number of Carts) x 100%

Customer Reviews

• Definition: Feedback and opinions expressed by customers on social media or e-commerce platforms.
• What it tracks: Analyzing customer reviews can provide insights into cognitive dissonance, as customers may express their conflicting thoughts or emotions about a product in their reviews.

Formula: There is no specific formula for customer reviews, but sentiment analysis can measure the positive or negative sentiment expressed in the reviews.

Post-Purchase Behavior

Customer behavior after a purchase is called post-purchase behavior. It includes the customer's evaluation of the product or service, satisfaction or dissatisfaction with the purchase, likelihood to repurchase or recommend the product, and post-purchase behavior like leaving a review or returning the product. By understanding and addressing the post-purchase behavior of their customers, businesses can improve customer satisfaction, retention, and profitability.

What are the 3 Post-Purchase Outcomes?

There are essentially three outcomes of post-purchase behavior, no matter the product or industry involved:

• Customer Satisfaction
• Customer Loyalty
• Customer Retention

Metrics to Track Post-Purchase Behavior

Customer Satisfaction Score (CSS)

• Definition: Measures the degree of customer satisfaction with a product or service based on their experience. 
• What it tracks: This metric tracks the overall customer satisfaction levels, including product quality, customer service, pricing, and other factors. 

Formula: Number of satisfied customers / Total number of survey respondents x 100

Net Promoter Score (NPS)

• Definition: Measures the likelihood of customers to recommend a product or service to others, indicating customer loyalty. 
• What it tracks: This metric tracks customer loyalty and brand advocacy and identifies areas for improvement. 

Formula: % of promoters (customers who rate 9 or 10) - % of detractors (customers who rate 0 to 6)

Customer Effort Score (CES)

• Definition: Measures the ease of a customer's experience when interacting with a product or service. 
• What it tracks: This metric tracks how easy or difficult it is for customers to use a product or service, identifying any potential pain points or areas for improvement. 

Formula: Total score of responses / Total number of survey respondents

Repeat Purchase Rate

• Definition: Measures the percentage of customers who make repeat purchases from a business. 
• What it tracks: This metric tracks customer loyalty and retention, indicating the likelihood of customers returning to purchase from the same business again. 

Formula: Number of repeat customers / Total number of customers x 100

Return Rate

• Definition: Measures the percentage of products that customers return. 
• What it tracks: This metric tracks the number of customer returns and indicates potential dissatisfaction with a product, service, or business policies. 

Formula: Number of returned products / Total number of products sold x 100

Reducing Online Returns

There are several strategies that businesses can use to reduce online returns, including:​

1. Provide Accurate Product Information: To reduce cognitive dissonance, businesses can ensure that customers have accurate and detailed information about their products, including features, benefits, and limitations. This information can help customers make informed purchase decisions and reduce the likelihood of post-purchase regret.
2. Use Social Proof: Social proof, such as customer reviews and ratings, can help to reassure customers about their purchase decision and reduce cognitive dissonance. Businesses can encourage customers to leave reviews and ratings and prominently display them on their website.
3. Monitor Post-Purchase Behavior Metrics: By tracking metrics such as customer satisfaction, net promoter score, and repeat purchase rate, businesses can gain insights into customer preferences, expectations, and experiences. This information can be used to improve product design, customer service, and other aspects of the business to reduce the likelihood of returns and increase customer loyalty and satisfaction.
4. Identify and Address Common Issues: By analyzing the reasons behind returns, businesses can identify any common issues or problems with their products or services and take action to address them. This can include improving product quality, providing more detailed information, and enhancing the overall customer experience.
5. Improve Customer Service: Finally, businesses can provide excellent customer service to help customers resolve any issues or concerns with their purchases. This can include offering flexible return policies, providing prompt and helpful responses to customer inquiries, and ensuring that customers are satisfied with their purchase experience.

By applying these strategies, businesses can reduce cognitive dissonance and post-purchase regret, improve customer satisfaction and loyalty, and ultimately reduce the number of online returns.

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Metrics to Track Online Returns

Return Rate

• Definition: This metric measures the proportion of products customers return after purchase. 
• What it tracks: It tracks the percentage of products returned out of the total number of products sold. 

Formula: (Number of products returned / Total number of products sold) x 100.

Return Reasons

• Definition: It provides insight into the product or service issues that customers are experiencing, such as defects, wrong size, or dissatisfaction.
• What it tracks: This metric tracks the reasons why customers are returning products.

Formula: Surveys

Cost of Returns

• Definition: It helps businesses to understand the financial impact of returns on their operations. 
• What it Tracks: This metric tracks the cost of processing and handling returns, including shipping, restocking, and refurbishing. 

Formula: Total cost of returns / Total number of products sold.

Return Window

• Definition: It helps businesses to ensure that their return policies are customer-friendly and aligned with industry standards.
• What it Tracks: This metric measures the time period during which customers can return products.

Formula: (Return window end date - Purchase date) / Total number of days in the return window period

Repeat Returns

• Definition: It helps businesses identify customers experiencing persistent product or service issues.
• What it Tracks: This metric tracks the percentage of customers who return products multiple times.

Formula: (Number of customers who returned products more than once / Total number of customers who made a purchase) x 100.

How does Data help in Pattern Recognition to Reduce Online Returns?

Data collected from the back-end of e-commerce applications such as Shopify, Stripe, and WooCommerce can provide valuable insights into customer behavior and patterns related to returns. Here are some examples of how data from these platforms can be used to reduce returns:

1. Shopify: Shopify tracks various order metrics, such as order value, product categories, and order frequency. By analyzing this data, businesses can identify products or categories with a higher return rate and improve product descriptions, images, and other product information to reduce the likelihood of returns.
   
2. Stripe: Stripe collects payment data such as payment method, location, and time of purchase. This information can help businesses identify patterns related to returns, such as
   customers who consistently return items purchased at a certain time or using a specific payment method. Businesses can then use this information to tailor their marketing and promotional strategies to reduce returns.
3. WooCommerce: WooCommerce collects customer data
   such as purchase history, order frequency, and average order value. This data can be used to identify customers who are more likely to return items and take steps to improve their overall experience. For example, businesses can offer personalized recommendations, discounts, or loyalty programs to these customers to reduce the likelihood of returns.

In summary, by analyzing data from the back-end of e-commerce platforms, businesses can identify patterns and trends related to returns and take targeted actions to reduce the likelihood of returns in the future.

Case Studies

Let us look at a few case studies on how companies have successfully reduced online returns and handled difficult situations without losing loyal customers:

1. Zappos: Zappos, the online shoe and clothing retailer, has built its business around customer service. They offer free shipping both ways and a 365-day return policy. They also have a 24/7 customer service team that is always available to help customers with any issues they may have. This commitment to customer service has helped Zappos reduce returns and build a loyal customer base.
   
2. Amazon: Amazon has implemented several strategies to reduce returns, including offering detailed product descriptions, photos, and customer reviews. They also offer free returns on many items and have a user-friendly return process. Additionally, Amazon uses machine learning algorithms to predict which items are more likely to be returned, allowing them to take steps to prevent returns before they happen.
3. Warby Parker: Warby Parker, the online eyeglass retailer, offers a home try-on program where customers can try on up to five pairs of glasses at home for free before making a purchase. This helps reduce returns because customers can see and try on the glasses before buying them. Warby Parker also commits to
   sustainability, which appeals to many customers and helps build brand loyalty.

Let us look at a few case studies on how companies have tackled unwanted situations without losing loyal customers:

1. UnitedAirlines' customer service recovery: In 2008, musician Dave Carroll released a music video titled "United Breaks Guitars" after United Airlines broke his guitar during a flight
   and refused to take responsibility for it. The video went viral, and United faced a PR crisis. However, the airline quickly responded and apologized, offered to repair Carroll's guitar, and donated $3,000 to a music charity. The response was widely praised, and United recovered from the incident.
   
2. Ritz-Carlton's personalized service: Ritz-Carlton is known for its exceptional customer service. This was displayed in a 2012 incident when a guest left behind a valuable laptop in a hotel room. The guest called the hotel to report the missing laptop, and the Ritz-Carlton team quickly located it and shipped it back to the guest. However, they didn't just send the laptop back - they also included a stuffed animal for the guest's child and a book on the area where the hotel was located, showing that they had taken the time to personalize the service and truly care about the guest's experience.
3. Domino's Pizza's recipe change: In 2009, Domino's Pizza faced criticism over the quality of its pizza, with many customers saying it tasted like cardboard. Rather than ignore the criticism, Domino's completely revamped its pizza recipe, using better ingredients and a new sauce. The company also launched a
   marketing campaign to promote the changes and encourage customers to try the new pizza. The campaign was successful, and Domino's was able to win back customers who had been dissatisfied with the old recipe.

There are many incidents all over the business world where companies have solved numerous crises very tactfully and did not lose any customers.

Instagram Vs Nike Website

Question: Why did the people who ordered shoes from an Instagram ad with a promo code return more than those who ordered from the main Nike site with no code?

[P.S: This is a completely hypothetical situation and is in no way related to Instagram or Nike.]

Answer: There can be numerous reasons why this happened. Let us look at the most common reasons:

1. Different Expectations: The people who ordered through Instagram might have had different expectations about the shoes compared to those who ordered from the main site. This could be because the ad may have portrayed the shoe differently or the messaging may have been unclear.
   
2. Impulse Buying: Instagram ads can be very tempting and may lead to impulse buying. People may see the ad, get excited, and purchase without fully considering whether they actually need the pair of shoes.
   
3. Limited Information: Instagram ads might have provide limited information about the shoe, and people may not have researched enough before purchasing. This could result in them realizing that the shoes does not meet their needs after receiving it.
4. Promotion-focused buying: People who order through Instagram may be more likely to be motivated by promotions and discounts and less likely to be satisfied with the pair if it does not meet their expectations.

Conclusion

In this blog, we discussed the topic of post-purchase behavior and cognitive dissonance and their impact on reducing returns in e-commerce. We first defined cognitive dissonance and how it relates to post-purchase behavior. We then explored various metrics that can be used to track cognitive dissonance and post-purchase behavior, such as return rate, customer feedback, and customer satisfaction.

Next, we explored various ways businesses can gather data on post-purchase behavior, including using backend data from platforms like Shopify and WooCommerce. We also discussed how businesses could apply cognitive dissonance and post-purchase behavior to reduce online returns by offering product recommendations, improving customer service, and reducing the return window.

Lastly, we explored case studies on how companies can reduce returns and how they can tackle difficult situations without losing loyal customers.

Overall, the blog provided insights into the various factors that impact post-purchase behavior and cognitive dissonance and ways businesses can leverage this knowledge to improve customer satisfaction and reduce returns in e-commerce.

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