Apr 2023 | Data Quality |

Data accuracy is the cornerstone to success — without it, organisations will continue to rely on that gut feeling and pass up the opportunity to make better and faster decisions for business growth.

Our 2022 Global Data Management Research Report showed that 85% of organisations indicate that poor-quality contact data for customers negatively impacts their operational processes and efficiency, hindering their ability to be flexible and agile. 

To help you craft a robust data quality management process, we have created a best-practice guide that considers the 5 stages of data quality management.

1. Migrate data to a single system

Departmental data siloes restrict organisational effectiveness. By consolidating all of your data into a single system, you can enjoy greater visibility through a holistic view of your database, identifying and addressing gaps in your data profile. To start, develop a concrete plan for which data needs to be moved, where it’s going, and how you’ll get it there.

2. Validate your data

Once your data is migrated, you’ll want to protect against the pitfalls of bad data. Prevent poor data collection by implementing real-time validation tools that validate data as it is entered across all touchpoints. This ensures your information – postal addresses, emails, and phone numbers – is actionable and correct, saving both time and money. This is also important because consistent outreach to invalid emails can hurt your sender reputation, causing deliverability issues. Furthermore, validated data can protect you against fraud, as sometimes customers do not give their true identity; maybe they want to redeem a special offer twice, or maybe there are more sinister reasons.

3. Enrich your data

Make your raw data more useful by expanding it with additional attributes like financial information, buyer propensity, and more. Combine first-party data from internal sources with third-party data from external sources. Enriched data instantly becomes fuller and more usable for improved segmentation and campaign personalisation.

4. Building and leveraging a single customer view

Implementing a single customer view is one of the fundamental success factors of a thriving, competitive company. It demands cultural and systemic changes if the customer is to drive business priorities and marketing strategies.

5. Routinely cleanse your data

Data needs to be cared for just like other key business assets. Regular review of all the data within your database to either remove or update information that is incomplete, incorrect, improperly formatted, duplicated, or irrelevant. With an automated solution, this can be done quickly and easily, often in the background. 

Experian can help 

Automated data quality tools are essential to achieving and maintaining a healthy database. Our data quality solutions, with your existing technology stack, ensure that accuracy is maintained over time and give you the deep insights required to make smarter, more profitable decisions across your business. 

Our real-time Address Validation, Email Validation, and Phone Validation solutions seamlessly integrate into web forms, customer CRM or checkout carts to ensure validity before the data enters your systems. 

 

 

What’s more, Experian’s data lists and sources are unmatched by almost any other data enrichment and location data service offering. We house a variety of enriched reference data, sourced through our partnerships with multiple data providers. These partnerships allow us to help you derive better insights for decision-making, enhance customer experience, and gain a competitive advantage. 

 

Our data cleansing service can also be seamlessly integrated into almost any database, allowing you to cleanse your existing customer records on-demand and in the format that you prefer. 

 

 

Traditional data migration strategies can be resource-intensive and complex. Eliminate the risk of gaps in your data by choosing an intelligent, self-service data quality and enrichment platform, such as Experian’s Aperture Data Studio. It covers all stages of the data migration journey from migration scoping to post-migration assurance and archival, with minimal administrative overhead. 

Get in touch with our data quality experts to learn how Experian can help you take control of your data for greater performance and stronger customer insights. 
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