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Duplicates – Where Do They Come From and Why Should We Care?
Most of us shoppers love the shopping part – picking, choosing and trying out various things. But too often we hate the buying part, especially when we’re forced to wait in line, then wait even longer while an associate wrestles with the transaction and tries to locate us for CRM. This frustration is sometimes made worse by crowds during holidays and sales such Black Friday and Boxing Day, but it is always made worse by inaccurate customer records!

From a consumer’s perspective, you know how often this happens. But from a business perspective, have you stopped to really think about what it costs?

Why duplicate records can duplicate costs

A rise in duplicates will increase your direct costs in many ways. For example, duplicates lead to the disintegration of customer records and may “hide” your best customers behind a false record, making them impossible to identify and reach. Based on the wrong or second record, valuable frequent shoppers might appear to have little purchase history; they may look like average customers less worthy of special attention. Duplicate records will also duplicate your printing and mailing costs for no additional return. Additional costs are imposed by the time and effort required to find and correct the errors.

More importantly, duplicates may also increase your costs through lost business. The whole point of your CRM program is to build business through better marketing, engagement and customer satisfaction. Bad records undermine all of that. Instead of encouraging your customer’s loyalty, they may end up encouraging a trip or click to your competitors—at your direct expense.

How an alias appears

To understand how to deal with the problem of duplicates, you must first identify what causes them. We mentioned the impact of holidays and sales on your customers, but they also cause your associates to rush, and in the process to make mistakes. They may type in the customer’s name and email address incorrectly, which means customer records don’t merge automatically. Similarly, they may be given or confuse a work number for a home number, or simply search for the customer record improperly, then end up entering the customer record multiple times with different information. These duplicates may not auto consolidate through the import process, especially if the consolidation scoring is not appropriately set.

Exposing a hidden identity

Since it is close to impossible to avoid all duplications, you must have reliable methods to find and correct them. The two most common ways are to identify duplicates from a customer import and from a manual search. During a customer record import, your CRM system compares new information against existing customers in your database based on four criteria and a 200 point scoring system, as illustrated in the following table.
 
Components
Score
Alphabetic Match Key
 
Typically: LLLLLLLLFFFF (L = Letter in Last Name, F = Letter in First Name)
150
Address Match Key or Phone Number
 
Typically: PPPPP11111AAAAA2222-PPPPP11111AAAAA22222
 
[P = Post Code, 1 = Digit in Address 1
(House Number), A = Letter in Address 1
(Street Name), 2 = Digit in Address 2 (Apartment)]
50
Alternate Key
100
Email
50
 
The score is then added up. If the sum is less than 200 the customers are not considered duplicates, but if it is greater than 200 then they are flagged as duplicates.  If the import consolidation parameter is set to auto consolidate, then the records consolidate when there is a single match. (You will not have to get involved when there are multiple matches to decide which records get merged.)

While working on various work sets, potential duplicates can be activated if they are not a match (<200) or can be consolidated if they are a match (>200). While consolidating duplicates manually you must be mindful of both the last update date and the create date on the customer record, as the most recent information should be retained.
You can also search for duplicates outside the import process using various search criteria – such as nickname and address, nickname and telephone, nickname and email and nickname and zip code – applied to the entire database or a specific subset of customers.  These searches are often run daily. Other searches, such as email and address, can be run weekly or bi-weekly.

While running manual searches you can use the system-defined keys or user-defined keys (for name and address). The system has two default name and address keys, but the user-defined keys help catch spelling mistakes sales associates often make, nicknames they often use, and the use of non-standardized addresses. You can catch more duplicates by creating your own keys and varying the components.

Don’t put it off!

Duplicates should be identified and consolidated daily to keep your database clean and duplicate free. Get your sales associates on board – make sure they understand the value of entering good data and focus carefully when entering records. Determine user-defined keys to fine tune your searches to suit your database, and invest in address standardization software (such as QAS) to minimize errors.

Lastly, and perhaps most importantly, mass consolidate with caution, to avoid making mistakes such as consolidating your VIP customer with a non-VIP customer or an employee record with a customer. While manually consolidating, drag and drop the information you need from the duplicate record to the destination record. Be careful, because the duplicate record gets wiped out, and the only information available to you will be the customer number on that duplicate record.

Watch for our next blog, “Your CRM’s Spring Maintenance.”

Heena Punjabi
CRM Services

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