Feb 2024 | Data Quality |

Data quality within a CRM system shouldn’t be an afterthought. It should be a key piece of the planning and implementation cycle when investing in a new CRM.

Data Quality is a key component of any successful data management program. And because your CRM contains vast amounts of important data, CRM data quality should be a key priority.

Given its role in your wider enterprise data management strategy, the number of stakeholders that interact with it, and the value of the information it holds, it makes sense to look after your investment.

In this article, we’ll explore why you should protect the integrity of your CRM data and offer some helpful tips on how to get started.

A significant investment that sits at the heart of an organisation

Organisations spend countless hours deliberating over which CRM system to implement. They then spend even longer planning and executing a painstaking strategy to imbed it within their current infrastructure (which probably included a painful migration).

The focus then typically turns to people and adoption, ensuring the correct training and resources were available to ensure a successful launch. And yet, all too regularly organisations struggle to maximise their CRM investment and get serviceable, actionable data to flow around their organisation.

The CRM sits at the heart of an organisation and is therefore best placed for implementing data quality best practices which, in turn, will help retain customers, win new ones and run a tight ship operationally.

Data quality within a CRM system shouldn’t be an afterthought. It should be a key piece of the planning and implementation cycle when investing in a new CRM.

Who uses the CRM system in your organisation?

Below we’ve listed some of the typical users of the CRM system and discussed their reliance on data:

  • Sales – Often the most active user in the CRM system. They rely on customer and prospect information to be up-to-date and accurate in order to segment and approach new customers
  • Marketing – Similarly to Sales, Marketing relies on accurate data so they can better target new customers (Check out our market-leading consumer segmentation tool, Mosaic, if this topic is of interest)
  • Customer Service – The customer service function is another heavily reliant user. They use the CRM to track customer relationships and deal with new customer issues or queries
  • IT – IT has a slightly nuanced role when working with the CRM system. It’s their job to ensure technically everything works and is secure. They interact with the CRM system in order to ensure smooth business processes.
  • Finance – Plotting financial projections and analysing past performance are the main duties for Finance when interacting with the CRM system. All of which feeds into the broader business strategy.
  • HR – Many organisations keep their employee records on their CRM system as well and although it doesn’t decay at the same rate as customer information, issues with employee data can impact downstream processes.

As you can see, there is a broad range of stakeholders who have an active relationship with your CRM system and therefore maintaining the accuracy of the data within it should be a paramount priority.

 

How can you protect the data in your CRM?

Improving data quality in your CRM system is crucial for ensuring accurate insights, effective decision-making, and better customer relationships.

Here are some steps you can take to enhance data quality:

Define data standards: Establish clear guidelines and standards for data entry, ensuring consistency across all users. This includes formats for names, addresses, phone numbers, but also governance structures, roles and responsibilities.

Train power users: Provide comprehensive training to CRM users on the importance of data quality and how to input data accurately. Emphasise the impact of accurate data on business outcomes and ensure processes are easy to adopt.

Implement data validation: Implement validation rules within the CRM system to enforce data integrity. This can include mandatory fields, data format checks, and logic-based validation to prevent erroneous entries.

Perform regular data cleansing: Schedule regular data cleansing activities to identify and correct errors, duplicates, and inconsistencies in the CRM database. Use data cleaning tools or manual review processes as needed.

Enrich your data: Augment existing data with additional information from external sources to enhance its completeness and accuracy. This could involve integrating with third-party data providers or using data enrichment services.

Visualise DQ reporting: Define and track key metrics related to data quality, such as accuracy, completeness, and consistency. Use these metrics to monitor performance over time and prioritise areas for improvement.

Data Quality tools and services for your CRM

Experian has a range of data quality solutions and services that will help you protect the integrity of your CRM.

From advance duplicate matching, to data enrichment, our solutions can help you embed data quality practices, ensuring your CRM remains a valuable and insightful resource.

For more information contact the Experian team today

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