Picture a wholesale textile company with a simple problem. One sales rep entered a client as ‘Ahmet Yilmaz Tekstil.’ Another logged the same firm as ‘A. Yilmaz Tekstil Ltd.’ The accounting clerk issued invoices under ‘Ahmet Yilmaz Tekstil Tic.’ The CRM (customer relationship management) software treats all three as separate customers. Ask the system how much revenue that client generated last year and you get one third of the real number. The rest is buried under names that look different but belong to the same person.
CRM software is meant to keep all customer information in one place — sales history, contact details, payment patterns. But the system only delivers value when the data inside it is accurate and consistent. Data cleansing means finding and correcting records that are wrong, incomplete, or duplicated. Deduplication is a specific part of that work: identifying records that belong to the same customer and merging them into one. The two terms are related but not the same. Cleansing covers the whole picture; deduplication handles the overlap problem specifically.
How do duplicates appear in the first place? Usually because more than one person enters data into the system. A sales rep meets a new client and adds them on the spot. The accounting department enters the same firm separately when preparing an invoice. A few weeks later, two records exist for one customer. Spelling differences make things worse. Writing ‘Istanbul’ in lowercase, using ‘Ltd.’ instead of ‘Ltd. Sti.’, entering a phone number with or without the area code — to the software, these look like different entries. The program reads characters, not intent.
Before starting any deduplication work, write down a set of matching rules. Which fields will you compare? The tax identification number is the most reliable match. If two records share the same tax ID, they are the same customer — no debate needed. When the tax ID field is empty, combine the company name and phone number as your criteria. Address can help too, but addresses get written in too many ways to use alone. Put these rules on paper and share them with everyone who touches the system. Without agreed rules, the cleaning process creates new confusion instead of solving the old one.
To run the cleanup, use the reporting function already built into your CRM. Pull a list of records that share the same tax ID. Then generate a list of records with similar company names. Exporting these lists to a spreadsheet program and reviewing them there is often the most practical approach. For each pair of duplicates, decide which record is the primary one — usually the older or more complete entry. Transfer any useful information from the secondary record: sales notes, contact names, phone numbers. Then either delete the duplicate or mark it as inactive. Marking as inactive is safer than deleting outright; if a mistake was made, you can reverse it.
Once the initial cleanup is done, the next step is preventing the problem from coming back. Agree on a standard format for entering company names. Will you abbreviate or write in full? How will phone numbers be entered — with the city code or without? Write these rules on a single sheet of paper and keep it near the computer where data entry happens. When a new employee joins, hand them that sheet. No complicated training required. Simple, shared standards stop most duplicates before they start.
Customer deduplication might seem like a small administrative task, but its effects reach further than most managers expect. Sales analysis, revenue per customer, and year-end mailing lists all depend on clean records. Sending two separate offer letters to the same client because they appear twice in the system is an embarrassing mistake that damages credibility. A CRM program that requires the tax ID field to be filled and warns the user when a similar record already exists makes this job much easier. If your current software does not offer those features, build a habit of manual review once a month. Keeping data clean is not a one-time project — it is ongoing maintenance, like any other part of running a business.
This article was originally written in Turkish by Gökhan MERCANOĞLU on June 24, 2002 and has been automatically translated into English and other languages using machine translation.