For companies looking to grow, one of the most common business goals is to get more contacts into their databases. If only you had 10,000 more email addresses from promising leads, you'd be guaranteed sustainable business growth, right? Well, not exactly.

While having a huge customer database can be a valuable asset to a business, this isn't always a guarantee of business growth and success. In fact, growing your database without the right strategy in place can quickly become a huge liability for your company.

If you have poor quality data, you risk annoying your leads with inaccurate messaging or delivering subpar experiences that discourage customers from coming back. Corrupted data also has repercussions for your business operations: it gives you a false view of performance and can lead you down the wrong path wasting valuable time, energy, and resources.

A smaller database that's accurate, consistent, and complete is more valuable than a huge database you're struggling to tame. In short, one of the best goals for any business is data integrity.

The opposite of data integrity is data corruption, which becomes a risk when poor quality data enters a database, the database is hacked, or information decays over time without proper maintenance and cleaning.

There are two main types of data integrity: physical integrity and logical integrity:

Physical Integrity

Physical integrity relates to the protection of your data as it's stored, used, and moved between apps. When your data has physical integrity, it means it's not compromised by physical threats such as hackers, power shortages, or natural disasters. Most businesses reduce this risk by choosing cloud-based storage with a reputable provider.

Logical Integrity

You're more likely to need to pay attention to logical data integrity, or the correctness and rationality of your data. Challenges to logical data integrity include software bugs, design flaws, and most common of all: human error. You can reduce the risk of these with reliable systems, documented processes, check constraints that require data to be inputted in a certain format, and other run-time sanity checks. Using two-way data syncing to ensure a single source of truth in every app is another valuable tool for logical integrity and consistency.

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Why Data Integrity is Important

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:

  • Deliver strong customer experiences that are personalized to every individual
  • Trust the information in your apps
  • Maximize your return on investment with relevant data insights
  • Make the most informed business decisions and have faith in your reporting
  • Avoid wasting money on storage for poor quality data

How to Ensure Data Integrity

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.

Make Data Optimization and Integrity a Priority

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.

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Originally published Oct 5, 2020 12:36:15 PM, updated June 24 2021