When was the last time you really cleaned out your company's data? Customer data can go stale after a while, and if you haven't been regularly going in and checking on the quality of your data, your data might not be as clean as you think. Performing a data quality check every quarter or so is a good way to ensure the customer data your sales and marketing teams are working with is as clean and accurate as possible.
A data quality check doesn't have to be something overwhelming for your team. By following these steps, you can quickly and easily confirm that your data is clean and update anything inaccurate or out of date.
1. Define your goals.
How are you planning to use your data? This is always your first step when you do anything with your data. You need to know what you plan to use it for so that you know which data you need to be collecting, which fields should be filled out, and when you might have missing or inaccurate data.
2. Assess your data.
Based on what you've learned in step one by defining your goals and understanding exactly what data you should be collecting, it's time to do an overall assessment. Jump into your CRM or data management software so that you can get an idea of what your data looks like.
Take a look at what your company currently has in place when it comes to input processes, opt-ins, manually inputting data, and more. Be sure that there aren't any issues with the data that's being input that are causing problems with your marketing automations and sales processes.
3. Analyze your data.
Now it's time to actually go in and look at your data. How many entries are there? How old are some of your oldest entries? How many are missing fields? Are those fields required for your automations or sales and marketing processes? If so, you're going to have challenges reaching those customers or leads.
Look at addresses and email addresses to ensure that there are valid entries in those fields, especially if you rely on email or direct mail for lead nurturing and/or customer retention. Check for valid phone numbers as well.
4. Clean your data.
Determine a date for when your data entries are too old to be used for your company. Be sure to purge all old data every quarter or so when you're doing your data quality checks. Purge any entries that are missing pertinent information, like contact info, full name, etc. Also be sure to remove any entries that don't have a valid email, mailing address, phone number, or another way to get in contact with them.
If you have a way of double-checking information to ensure its accuracy, manually run a few of the most recent entries up against your records to be sure it's being input correctly. Data cleaning is an important step, and your data quality checks aren't complete until this has been done.
You don't have to suffer from dirty data anymore. By regularly performing data quality checks within your CRM or data management software, you can help your company improve its automations and sales processes that use this customer data. Learn more about your data by requesting a complimentary data health assessment to find out just how dirty your data is.