In the modern distribution chain, every step from order to delivery is interconnected and intertwined. All it takes is one incorrect piece of data (email, postal address, telephone number) to trigger a cascade of costly errors that damage your brand image, competitiveness and sales performance.
In this article, Data Enso details the Data vigilance points in the distribution chain, and offers you a case study to quantify the loss of revenue and explore possible solutions.
Data" points of vigilance in the distribution chain
Ordering, shipping and delivery... three key stages that can make or break the efficiency and competitiveness of your distribution chain.
The order: corresponds to the receipt and processing of the customer's request.
The point to watch here concerns the verification of data on the contact form. Incorrectly entered email addresses, names or telephone numbers will lead to errors in order confirmation, and require manual intervention that delays the process and adds to the cost. Failure to validate data at source will also lead to inconsistencies in personalized communications with the customer, affecting your image.
Shipping refers to the preparation, packaging and dispatch of the product to the carrier.
This stage requires rigorous management of product, packaging and delivery address data. An error in the postal address or poor coordination with the carrier will result in delays and additional costs. It's also important to take into account the weight and size of the product when calculating shipping costs and choosing the right mode of transport.
The final stage, delivery, consists of taking the order to the recipient.
An incorrect address or a wrongly entered zip code will lead to delivery errors (wrong addressee in the right address, wrong address, etc.). Also, misinterpreted delivery preferences (e.g. morning or afternoon delivery, specific instructions for the delivery person) will lead to delays or unsuccessful delivery attempts. At this level, Data Quality also makes it possible to synchronize efficiently with delivery partners, ensure compliance with regulations and maintain transparency in real-time tracking... which are decisive factors in the quality of the customer experience.
The role of Data Quality Management in the ordering process
The quality of customer data is crucial to the smooth running of the order process, yet this aspect is often neglected, to the detriment of the overall efficiency of the distribution chain.
Initially, failure to validate customer data at source (on the form) and/or curatively (processing an existing database) will inevitably lead to malfunctions in order confirmation. An error in the first or last name, for example, will not allow you to personalize your communications correctly, which can lead to frustration. Clearly, you'll be addressing a customer who has just placed an order with a typo in his first name, or even with a different first name.
Even more serious: an error in the email address will prevent the order from being confirmed, forcing the customer to contact customer service, resulting in a negative experience for the customer and operational inefficiency for the company.
Finally, data quality at scale contributes to the Single Customer View (SCV), where all customer information is consolidated in a single profile.
Objective: to facilitate access to reliable, useful and complete information on each customer for all company departments (marketing, sales, customer service, shipping, etc.).
By centralizing this data, the order can be processed consistently at every stage, from entry to dispatch and tracking. SCV therefore minimizes the risk of inconsistencies and errors, such as an incorrect shipping address or telephone number, which will not only delay delivery but also increase its cost.
Data Quality and distribution: a case study
Our customer is an e-commerce site based in France, specializing in the sale of local food products with quality labels. Following rapid growth driven by increasing demand, management has decided to implement a new order management system in early 2022.
A few months after implementation, the shipping and returns team noticed a worrying increase in the number of returned parcels. After reviewing the reports and comparing them with the company's historical rates, it was found that 3.5% of parcels were being returned to sender due to incorrect delivery addresses, compared with an average rate of 1.5% before the new system was implemented.
This situation quickly gave rise to concern within the company: the malfunction in the address verification process was obvious.
After diagnosis, it was discovered that the new order management system was better calibrated for the growing volume of demand, but less efficient in terms of data verification.
Several consequences:
- The return rate rose from 1.5% to 3.5%, resulting in additional costs of €60,000 in the space of six months.
- Customer satisfaction was logically affected, as evidenced by the drop in the company's Trustpilot rating from 4.5 to 4.2 over a six-month period. Return problems generated an influx of negative comments (+18%)
- Time spent processing returns and correcting incorrect addresses increased from 36 to 48 hours per week, reducing productivity and increasing pressure on the shipping and returns team.
- The inability to deliver on time and accurately led to an estimated 2% loss in recurring sales.
Faced with these alarming consequences, management took immediate action. The first step was to identify a dedicated technological solution capable not only of verifying addresses as they were entered into forms (thanks to an API), but also of cleaning up the existing database, which had become polluted. Data Enso was chosen:
- Implementation of real-time verification: an address verification API has been integrated into the online order form, enabling real-time validation. The data entry error rate was reduced by 90%.
- Database clean-up: correction of incorrect addresses, deletion of obsolete data, deduplication, formatting, etc. Result: 98% improvement in data quality.
4 months later, the return rate had dropped to 1.2%, saving €40,000 over the period. The Trustpilot score rose to 4.4, and recurrent sales gained 3 points. Finally, returns management time has been reduced to 28h/week (compared with 48h previously).
Are you facing similar problems in managing your data (first and last names, postal addresses, emails, telephone numbers, etc.)? Our Data Quality Management solutions can help you achieve operational excellence, boost your profitability and improve customer satisfaction. Find out how we can help.
