Data is your company’s most valuable asset. It can be used to make executive decisions, streamline marketing campaigns, increase customer retention, and develop winning ideas that increase overall growth. But if the quality of your data is poor, it can have the opposite effect.
A strong data quality plan is crucial to your business’s success—and the best place to start is with data profiling. Let’s dive into what profiling consists of, why it’s important, and how it is essential to maintaining your data quality.
Data profiling involves sorting through, examining, analyzing, and summarizing data into a high-level overview. This helps you understand the current state of your data and is the foundation of any solid data quality plan. After all, you can’t take steps to maintain or improve your data quality if you don’t know where you’re starting from!
Not all data profiling is the same. There are three types:
Combined, each type of profiling helps you understand how you’re currently working with your data. You can then use these insights to improve (and maintain) your overall data quality.
Profiling has always been important, but it is especially necessary in today’s climate. Here are a few of the main reasons why:
As people change roles (or leave the workforce entirely), their data changes with them. Failure to keep up with the changes can have a negative impact on your data quality. In a recent study by Validity, 79 percent of CRM users agreed that data decay has increased as a result of the pandemic. Profiling can help you identify where your pain points are and adjust the way you manage your data, so you don’t fall behind.
Now that we know what profiling is, let’s take a closer look at how exactly it helps you maintain the quality of your data.
From underperforming marketing campaigns to inaccurate sales forecasts, low-quality data can cause all sorts of problems throughout a company. Profiling helps identify the errors that are causing your data quality to plummet and your business to suffer, such as misspelled contact information, missing values, duplicates, outliers, and unnecessary values.
Ninety-six percent of CRM users agree that accurate CRM data improves their conversion rates. By taking this opportunity to fix any errors and make note of how often you spotted them, you’ll be able to improve the quality of your data, prevent the same errors from being made in the future, and set your business up for success.
When multiple departments are entering and updating data in the CRM, inconsistencies are likely to occur. For example, Sales may use “x” to denote an extension number, while Finance may use “ext.” As trivial as this may seem, even the smallest inconsistencies can build up over time and destroy the quality—and value—of your data.
Profiling spotlights these inconsistencies and presents the perfect opportunity to create standardization rules. Standardization helps keep formats consistent across all data and systems, improving the quality of your data and making analysis much more feasible.
One of the biggest benefits of profiling is increased data literacy.
Since the profiling process involves learning about how the data in your CRM is structured, what it contains, and what connections exist between datasets, completing this process will leave you well-equipped to speak about what the data in your CRM means. You’ll also gain an increased awareness of your responsibility for collecting, integrating, preparing, and protecting the data in your CRM.
The more data literate you and your team are, the less likely you are to make mistakes in the future that could tarnish the quality of your data.
Profiling can help shed light on process inefficiencies that may be tarnishing your data quality.
For example, you may discover there are certain processes you’re completing manually (e.g., deduping records) that aren’t producing the desired results. Deciding to automate these processes can greatly reduce errors and oversight and help you improve the overall quality of your data.
Business rules outline the relationships between objects, such as customer names and their corresponding orders, and are applied within workflow tools to enable process automation. In other words, business rules empower a company to automate decisions that it makes in its day-to-day operations. Profiling helps ensure the data in your CRM meets any business rules that are currently in place.
Profiling also helps you see which data points are used with system integrations. Knowing which data points support integrations and allow them to successfully execute processes, both within and outside of the CRM, is helpful for tracking down the problem if a process fails.
The quality of your data can make or break your business. To survive (and thrive) in today’s unpredictable climate, implementing a strong data quality plan is essential—and this starts with profiling your data.
For greater insight into the data management process, from profiling and standardization to automation and monitoring, download The Dirt on Data Quality eBook today.