For a successful e-commerce business, the quality of customer data is a decisive factor in the fluidity of processes and sales performance.
In this article, Data Enso looks back at the experience of our customer, an online store specializing in the sale of clothing and accessories, which experienced a significant increase in return rates and refund requests following a Data problem.
The data quality issue: soaring product return rates
Our client is a mid-sized online boutique offering women's fashion clothing and accessories. The company recorded impressive sales in 2021 and has enjoyed continuous growth since its inception. It offers several third-party brands, but its success is mainly due to its own brand, which is highly prized for its value for money.
However, over the past 12 months, our customer has been faced with a major problem concerning product returns and refunds. Return rates have climbed to 30% of all orders placed, a significant increase on the usual 15% observed in previous years, with direct financial consequences.
Taking into account the costs of processing returns, returning products to stock and refunding customers, the company estimated a financial loss of around 1,260,000 euros over the past year.
The company has also observed a decline in customer satisfaction, as evidenced by online reviews and customer service feedback. The number of complaints increased by 25% in one year, and the Trustpilot rating dropped from 4.4 to 3.9 in less than a year. Customer retention dropped by 15%, directly impacting sales performance.
Faced with these challenges, the company decided to seek help in identifying the underlying causes of this increase in returns and refunds, and in finding an effective solution. As experts in Data Quality Management, Data Enso was chosen to solve this problem.
Investigation: the causes of underperformance
Faced with a significant increase in requests for returns and refunds, our customer quickly launched an internal investigation to identify the underlying causes of this situation, which was threatening its competitiveness and even its very survival. Management set up a team made up of customer service, marketing and logistics managers to take an in-depth look at data, internal processes and customer returns. The team began by suspecting, among other things, a problem with the company's customer database.
Indeed, the database had not been updated for over a year, following a decision by the company to cut costs to optimize margins. In addition, the company had adopted an aggressive Inbound Marketing strategy, using premium-quality lead magnets to generate mass sales. This strategy had not been coupled with a policy of Data Quality Management, either at source (on the form) or downstream of the sale (batch processing of the existing database).
After examining data and internal processes, the task force identified three problematic factors:
- Errors in the database were concentrated in the "delivery address" field for several reasons: no formatting validation for addresses (free field), typing errors, encoding problems (for accents and cedillas), etc.
- The team also discovered duplicate entries in the customer database, probably due to a lack of verification and validation of data entered during lead generation. In other words, instead of updating the address of a customer who moved, the system created a new entry in the database.
- By analyzing customer returns, the team found that certain products were often returned due to incorrect sizes or colors. In fact, many products were listed with incorrect data.
Data Enso's intervention
To remedy this underperformance, the main cause of which was the absence of a Data Quality Management policy, the company's management contacted us. We began by analyzing the situation in detail to understand the nature of the problems encountered and identify the products best suited to the company's needs.
The following solutions have been selected:
- EnsoAddressto clean up the postal address database (validation and formatting)Â
- EnsoDedupto deduplicate and cleanse the customer database (identify and merge duplicates)
- EnsoMoveto update the addresses of customers who had moved, and to check and update delivery addresses.
We also worked with the company to integrate Data Quality Management solutions into the company's contact form via the API to validate and verify data entered by customers at source.
Our customer has implemented our email validation andpostal address standardizationsolutions live on its account creation and order forms. In this way, he avoids recording invalid data in his system as a result of trivial data entry errors when creating an account.
Results and remaining challenges
Following the implementation of Data Enso's solutions, the rate of product returns dropped significantly, from 30% to 11% in the space of six months (below the industry average of 12.5%). This reduction resulted in an estimated saving of 985,000 euros over the year, taking into account the costs of processing returns, returning products to stock and refunding customers.
The company has also recorded an increase in customer satisfaction, with the average Trustpilot rating rising to 4.3 out of 5 in just nine months. The number of complaints has fallen by 20%.
Last but not least, Data Enso's solutions have enabled the company to streamline its internal processes , reducing order and returns processing errors and improving operational efficiency, with a significant reduction in production costs.
One problem remained, however: the customer retention rate had improved too little in nine months. It will take time to reverse the effects of past mistakes and regain customer confidence. Faced with this challenge, the company is planning to launch several marketing campaigns aimed at customers who have suffered inconvenience.
Objective : to subtly communicate the increase in order processing capacity and offer promotional codes and discounts on future orders.
The company has also taken steps to improve after-sales service, including the introduction of Live Chat and a dedicated telephone number.
