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With Great Data Comes Great Responsibility

With Great Data Comes Great Responsibility

We all know the phrase “with great power comes great responsibility”, what most people are unaware of is that data is the new world power.

With companies all over the world implementing CRM systems such as Dynamics 365, the power of high quality customer data is quickly being realised by many.

Data is however a tool, if applied correctly you wield the power to revolutionize your business. Used incorrectly it can have disastrous effects. It therefore is your responsibility to be the master of your data.

The Golden Record – your weapon of choice

With infinite ways to collect customer data into Dynamics 365 and even more ways to apply it, it’s easy to feel overwhelmed. However, fear not because the way you manage this data in your CRM can turn it from a garbage heap to a goldmine with relative ease.

Within the world of data management, there is a concept called ‘The Golden Record’. According to whatis, the golden record is a “single, well-defined version of all the data entities in an organizational ecosystem.” It is also known as a single version of the truth (Single Customer View), as it gives you a single record with the purest and most complete set of a customer’s data.

By making sense of your data to create a Single customer view and creating a golden record for each database entry, you will be well on your way to data mastery. Ensuring you have complete, accurate and GDPR compliant Customer Data. Data cleansing software or master data management software is often the first port of call in achieving this.

Creating a Single Customer View

In order to create a single customer view, duplicate records must be matched and merged into a single place. This involves various intelligent processes.

First let’s consider the process of matching.

Various smart rules must be set in place so that software can iterate through the database and identify which records are actually duplicate entries. The most common example which causes error in a system is when a person is entered into a database twice. Each entry however, with slight variations of the same name.

Consider the instance below:

Duplicate data example

With the use of fuzzy matching software and various other intelligent processes it becomes clear that these two records are in fact the same person. Rob is an abbreviation of Robert, the last name is Smith in both cases, the first five digits of each phone number are the same and the postcodes are very similar. Good matching software will have a wide variety of intelligent tools available in order to identify matches in the database.

Now that the records are matched, the next step in the process is Merging, to create a Single accurate version of the two records above.

This step, like matching also requires intelligent rules and workflows to assess which record is the most trustworthy. For example, we can see that the first five digits of each phone number are the same however only record 1 is complete so it is likely that the phone number from record 1 is correct. This is the phone number that will be used in the “Golden Record”.

Likewise the software will know that Rob is an abbreviation of Robert, so Robert would be used.

Lastly, because both postcodes are in the correct format, a series of Verification, Validation and Authentication steps could be employed in order to work out which postcode is correct. However, for the sake of this example we will say that the owner of the data base trusts record 1 because it is from a more trusted source. Thus the postcode and home number from record 1 will be used in the “Golden Record”.

After these rules have been applied, the records above are merged into one:

Records merged examples

This is known as the “Golden Record” it is complete, accurate and trustworthy.

With all of your records in this format, you will unlock the full potential of your CRM and its data, allowing numerous benefits such as: increased customer satisfaction, less wasted money on marketing campaigns, GDPR Compliant Data and finally statistically driven decisions can be made based on reliable customer data.

Customer data is not static, it’s dynamic and constantly evolving. Whilst some view this as a nuisance, we see it as an opportunity to keep on top of your customers information. To consistently deliver high quality customer service and boost your businesses reputation.

If you’re concerned about the quality of your Customer Data, book a DQ Diagnostic with us today

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Written by Hayden Law

As a Customer Success Manager, Hayden is our front-of-house contact for most clients. He supports them on their data quality improvement journey, optimising the customer experience and feeding insights back into the R&D and product development cycle to help us continually innovate with clients in mind.