DB Cleaner Update — Address Quality Control

Addresses in customer databases rarely look as neat as entries in official directories. People change the order of address components, use abbreviations, and add apartment numbers, entrances, intercom codes, landmarks, or delivery notes.

For example: 5 Shevchenka St., Apt. 3, Nizhyn, Chernihiv Region, Entrance 2, Intercom 47.

For automated processing, an address like this is much more complex than a standard entry. That is why the DM Solutions team has updated DB Cleaner. The product now handles real-world address formats more effectively, correctly processes approximately 98% of addresses on average, and clearly separates reliable, undeliverable, and uncertain records.

DB Cleaner Now Recognizes Addresses the Way People Write Them

The previous version of DB Cleaner expected a standard sequence: region → city or locality → street → building → apartment. If the components appeared in a different order or the entry contained additional text, the address could remain unparsed.

The updated DB Cleaner recognizes:

• non-standard ordering of address components;
• common abbreviations and spelling variations;
• apartment, entrance, floor, and intercom details;
• landmarks and additional explanations;
• delivery instructions and notes for couriers.

This allows addresses to be processed as they are actually stored in CRM and ERP systems, checkout forms, and customer records.

Average Address Processing Increased from 85% to 98%

Based on customer database processing results, the average share of correctly processed addresses has increased from approximately 85% to 98% — a gain of 13 percentage points.

For a database containing 100,000 addresses, the update can mean around 13,000 additional records that DB Cleaner is now able to process correctly.

For businesses, this means:

• fewer unprocessed addresses;
• less manual work;
• a more complete and reliable customer database;
• more records available for delivery, communication, and analytics.

Actual results depend on the quality of the source data, but complex and non-standard records benefit the most from the update.

Fewer Errors and Greater Control

Previously, an unsuccessful parse could look just as confident as a correct one. This made it difficult to separate an incorrect result from a reliable one automatically.

Now, every address receives one of three statuses:

• Ready for dispatch — the address has been recognized, structured, and can be used in the next process.
• Undeliverable — the system has determined that the address cannot be used for delivery.
• Uncertain — the result requires additional verification.

Uncertain addresses are immediately routed for manual review. This reduces the risk of an incorrectly structured record entering a delivery, mailing, or analytics system as valid data.

More Advanced Processing Without Sacrificing Speed

The parsing logic is now more sophisticated, but performance has not declined. In some scenarios, processing an individual request has become even faster.

This matters for workflows in which address data is checked continuously or in large batches:

• recurring CRM and ERP cleansing;
• preparing bulk mailings and deliveries;
• validating addresses during checkout or registration;
• migrating data between systems;
• processing large customer databases.

What the Update Means for Businesses

The updated DB Cleaner helps transform unstructured address records into manageable data that can be used in downstream business processes.

• More addresses are processed automatically.
• Non-standard formatting is no longer a critical obstacle.
• Errors and failed deliveries are reduced.
• Uncertain results do not move forward without review.
• Employees only need to handle genuinely complex cases.
• Processing speed is maintained or improved.
• Overall customer database quality increases.

The update is especially valuable for logistics companies, banks, insurance services, retail, and e-commerce — anywhere address accuracy directly affects costs, service quality, and customer communication.

DB Cleaner Adapts to Real-World Data

Customers should not need to understand database structure rules to enter an address correctly. A modern tool should adapt to the way people provide information in real life.

That is exactly what the updated DB Cleaner does: it recognizes more addresses, provides better control over result quality, and maintains high processing speed.

Request a free audit of up to 500 rows and see how much cleaner and more practical your database can become.