Your organization's most important asset is data about your customers and prospects: the people who supply the revenue that makes your business sustainable.
Even if you have a tiny flower stall with ten regular customers, you need to treat their contact data like gold. Otherwise, you'll struggle to deliver experiences in a timely, personalized, and memorable way that encourages your customers to return and recommend you to friends.
The same applies to every other business: no matter your industry or the size of your organization, data integrity is a key foundation for smooth operations and sustainable revenue.
Data integrity enables your organization to:
Achieving data integrity requires more than just a few tweaks to your database. It means looking at data lifecycle management (DLM) as a whole and optimizing your processes, rules, and standards everywhere.
Let's take a closer look at the different stages of DLM and how you can ensure data integrity for each one.
Collection – Are you collecting data in an ethical way that meets data protection regulations? This means only capturing data that you have permission to store and making sure it's accurate, complete, and relevant, ideally with the help of validation checks. This goes hand-in-hand with ensuring data quality, or the relevance of the data you collect.
Storage – Are you storing data in a standardized way? Remember the three pillars of accuracy, completeness, and consistency for data integrity. Data safety is another prerequisite for data integrity, so it's essential to make sure information is stored securely with minimal risk of hacking or corruption.
Maintenance – Are you doing regular data housekeeping? What about syncing data between the right apps to enrich your other tools? One of the best ways to guarantee data integrity and consistency is with the right integration in one place. One that shares data between your apps in real-time, rather than relying on error-prone CSV import and exports.
Usage – Are you creating reports to understand and optimize your data? Businesses with high data integrity use their data to inform business decisions rather than leaving it in a siloed app to gather virtual dust.
Cleaning – Are you purging data that no longer serves your business, such as outdated, incorrect, and duplicate data? It's also important to clean data that no longer complies with data protection regulations to uphold your data integrity.
Auditing – Are you unsure of the types of data issues that are in your database? Analyzing your CRM data for common types of errors is an important part of maintaining data integrity, and there are free tools available that can identify data issues and grade the quality of your CRM data.
Data integrity is an ongoing project that doesn't have a finish line. It starts with the data you capture and continues with how you store, maintain, move, and clean it. While data optimization is not the most glamorous part of your business, it's a vital one.
With strong foundations and processes for data integrity, your organization is in the best position to deliver memorable customer experiences, make insightful decisions, and achieve the highest long-term performance and return in all areas.
Originally published Oct 5, 2020 12:36:15 PM, updated June 24 2021