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During Black Friday, the workload on an online store increases at every stage — from checkout to order picking and handoff to a delivery provider. At this time, even a small address error can create extra manual work precisely when the team needs to process the highest possible number of orders.
An outdated street name, a missing locality, an incorrect postal code, or several spelling variations of the same address may go unnoticed on normal days. During a seasonal peak, these inconsistencies add up: managers have to call customers, verify details manually, and correct orders before shipment.я
That is why Black Friday preparation should cover more than inventory, advertising, and website performance. Your address database needs attention too.
Customer databases may contain addresses with former street or locality names for years. A shopper may enter the familiar version, while the CRM, accounting platform, or delivery service expects the current name.
Your validation process should recognize both former and current names and match them to the same valid location.
An address may be missing a region, community, district, locality type, building number, or postal code. For example, “15 Shevchenka Street” without a city or village cannot be used reliably for delivery.
Before the seasonal peak, define which fields are mandatory and identify records that need additional information.
The same address may appear in several formats:
People understand that these records may refer to the same place. A CRM, analytics platform, or automated data exchange may treat them as different addresses. Standardization converts them into one consistent format.
Look-alike Latin and Cyrillic characters, extra spaces, accidental punctuation, inconsistent abbreviations, and address components in the wrong order make searching and matching more difficult.
These issues are better detected in bulk than corrected one order at a time on your busiest day.
Duplicates distort analytics, complicate customer segmentation, and create confusion around repeat purchases. At the same time, the same address does not always mean the same customer: several people may live there, or a business may place multiple orders.
Define duplicate-detection rules in advance and combine address data with other permitted identifiers.
Before cleaning the database, create a backup and keep the original values. Do not overwrite source addresses without a way to review the changes.
Identify the fields that contain structured address data. Courier instructions, customer preferences, and internal notes should be stored separately.
You do not need to start with the entire database. Select records from different regions, sales channels, and time periods to reveal typical problems.
A test sample helps estimate the share of valid addresses, the number of ambiguous records, and the likely amount of manual work.
After validation, assign each record to a clear category:
This makes it clear which issues can be corrected automatically and which should be sent to a responsible team member.
Once the rules have been tested on a sample, move on to bulk processing. Keep a link between the original and standardized address and maintain a report of all results.
Database Cleaner by DM Solutions helps validate, enrich, and standardize address records. To assess your data before starting, you can request a free audit of a sample of up to 500 rows.
Cleaning historical data solves only part of the problem. If the checkout form continues accepting free-form addresses, errors will quickly accumulate again.
GeoData Online can validate and suggest addresses as the customer types. Learn more about integration options in the DM Solutions product FAQ.
Before the campaign starts, complete the full journey of a test order:
Test renamed streets, small localities, addresses without postal codes, and records that use abbreviations.
Before Black Friday, confirm that:
Do not postpone the audit until the final days before the sale. You need time to test a sample, approve standardization rules, review ambiguous records, and verify data exchange between systems.
The best place to start is a small sample that quickly reveals the real state of the database and helps you plan the next steps.
DM Solutions helps online stores validate, clean, and standardize address data, as well as control new addresses during checkout.
Request an address database audit to find out which errors are present in your data and how to prepare it for Black Friday.
