Measuring and resolving for what is important

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Duplicate data might seem harmless at first, but it can create extreme difficulties in the long run. Such as a database’s failure to provide a single customer view. This in turn makes it challenging for the sales and marketing team to use it in mundane tasks like marketing automation and campaign building.

When put into monetary terms, duplicate records cost money, not only in terms of storage but also in terms of wasted effort and energy in decluttering the duplicates from the system. All of this can take you months, there is also the subtle cost of confidence and faith in the data. Systems riddle with duplicates leave data users worried about the correctness of their decisions and completeness of their work.

Duplicate customer data is also much more prevalent in systems of record, than companies often realize. An average duplicate rate in a database could be as high as 20%-30% in some industries.

By neglecting customer data quality and duplicates in particular, you are compromising the overall health of your business record-keeping. When you don’t have the right information about your customers, there’s also no way you can be confident that you are targeting the right people with precisely the right offer. A natural consequence is that you’re also likely to be providing poor customer service. The latter will in turn negatively impact your brand reputation and waste precious marketing resources and effort.

Different types of Duplicate data

Duplicate data are not necessarily just copies of the original record; there are various types of duplicate data that might be present in your systems.

  • Exact copies in the same resource– Often, records from one data source are transferred to another without any duplicate checks. For example, when organizations transfer customer data from CRM to their CDP, even when the subscribers’ data is already stored, they could create duplicate customer records of the same entity.
  • Exact copies on multiple sources- This happens when companies do back-ups of their information and store copies they have in hand without performing any data cleansing process and duplicate identification.
  • Not-exact duplicate on multiple or same sources- A non-exact duplicate is when the original data is represented in various ways, which may or may not mean the same thing. For instance, John Dona Ruth can be defined as John D Ruth and JD Ruth; both aren’t wrong but can create different representations which in aggregate present as duplicates.

How to remove duplicate customer records?

Here are some best practices to identify and remove duplicate data from your customer master

●     Use validation checks on data entry.

Adopting strict data checks on all data entry points will help ensure that the input data is unique and meet all data quality standards. In addition, such configuration should identify that the incoming data is duplicated and filter out its copies still present in the database. This will make your data valid, complete, and accurate in the longer run.

●     Use automated duplicate checker tool

The latest self-service data duplication software helps businesses identify and clean duplicate data. These applications are dedicated to finding all exact and non-exact matches to standardize the data quality. Using such an automated system scraps out the need for human help and saves your business thousands of dollars. When choosing a duplicate checker tool, make sure you can easily import data from various sources like CRM databases, excel sheets, lists, etc.

●     Use data-specific duplicate checking technique

Identifying duplicate data is complex; marketers should be cautious while deducing data because one piece of information can mean different things at different sources. For instance, finding two matching email sources might mean that both entries belong to the same person. However, entries with two same addresses will not follow this theory because two individuals from the same building can have two separate subscriptions of your product. So, make sure your data purging activity is in accordance with your database.

Duplicate data can blur the customer view for your company and make it difficult to conduct any marketing operation; such a database only drains your resources. If not handled properly, it can lead to many missed sales opportunities and lost income.

Prevention is better than Cure

The Pretectum approach to duplicate record avoidance, identification and remediation factors in several important aspects of the Customer Master Data Management process. The first of these is recognizing that duplicate records are not always possible to avoid.

One of the reasons duplicates may exist is that they might be the legacy nature of some of the systems in use. When this is the case, the next best alternative is to retain the duplicates but provide an external key that can group the records that refer to the same customer across different sources. This approach is supported by the platform.

A second approach is the preferred approach, it is preventative which has the Pretectum platform as the de facto authority on who the customer is and is used for origination and as the hub supporting syndication and synchronization with other systems in the landscape.

Contact us today to find out how you can improve your current system landscape

RJ