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A cluttered customer relationship management (CRM) database is like a cluttered house: it’s tough to find what you need. Accurate input, unsubscribed users, and old information can clog your CRM, significantly impacting your marketing activities, sales efficiency, and customer retention. Data cleanup on a regular basis helps you to concentrate on the contacts that are […]
A cluttered customer relationship management (CRM) database is like a cluttered house: it’s tough to find what you need.
Accurate input, unsubscribed users, and old information can clog your CRM, significantly impacting your marketing activities, sales efficiency, and customer retention. Data cleanup on a regular basis helps you to concentrate on the contacts that are critical to the success of your operations.
Here are some best practices you can use to clean up your CRM on a regular basis, whether you’re cleaning it for the first time or searching for a new method.
Data hygiene is the practice of removing faulty data from your database in order to optimize it and ensure that you only have high-quality, relevant data. So, what constitutes terrible data and what constitutes good data?
Irrelevant or outdated information, inadequate contact information, or data that contradicts each other, such as several phone numbers for two contact inputs, are examples of bad data.
Data that is accurate, current, and consistent is considered good data.
It’s critical to understand that good data is about more than just accuracy. The importance of quality over quantity in CRM data should be emphasized. Remember, you’re paying to store your data, so make sure it’s helping you improve your team, create more effective processes, and increase your company’s ROI.
What’s the best way to get rid of bad data from my CRM?
Part of your data auditing process is determining what is good data and what is bad data. Check the state of your data at this point to see if it is up-to-date, helpful, and relevant to your team. This will help you determine what should be kept and what can be discarded.
Bad data is frequently the result of data input errors, but you should also consider the following possibilities:
Following this procedure, you can create a list of old contacts and delete them from your database.
Identify and eliminate duplicates throughout the cleaning procedure. HubSpot offers a duplicate management solution that employs machine learning to scan for duplicate contacts, companies, and properties, depending on your subscription level.
It’s unavoidable that some contacts will become inactive over time. Although detecting whether or not a contact has unengaged isn’t an exact science, the following are some excellent guidelines for recognizing unengaged contacts:
Each team’s CRM data cleansing will most likely be different. Regardless, establishing a uniform strategy to data cleansing is critical.
You might have a CRM manager who cleans the system on a regular basis. Alternatively, you may make cleanup a team activity to guarantee that each team member is in charge of their own data.
This option is ideal for a larger organization that often inputs large amounts of data that would be difficult for a single team member to manage.
Establish a consistent regimen once you’ve decided who will do the cleanup. Establish a monthly, quarterly, or annual timetable, depending on the amount of data you’re working with, rather than being hypervigilant and reviewing the data each time a set is input.
Because establishing the ideal plan for your company can take some time, you might want to start with an annual check-in. You might time your data cleansing to coincide with other significant annual occasions, such as tax season, and think of it as a data “spring cleaning.”
Your cleansing will result in less clutter and more productive messages to useful contacts, regardless of the timetable.
Standardizing the input process is one method to make data cleanup easier for your team and keep subsequent cleanups to a minimum. Setting up property fields that display automatically when contacts or firms are manually formed is an important approach to standardize the process.
This ensures that the input process is consistent.
When prospects enter their information into a form submission, you can apply the same method. This gives your staff with valuable information in critical fields.
Check your contacts against important fields that a contact would not find useful to ensure that your data is consistent. For example, if a contact does not belong to a given industry, introducing a “industry unknown” condition might help categorize them more correctly.
You can use one or more of HubSpot’s data management integrations to help with the data collection and assessment processes:
Because there is no one-size-fits-all solution for keeping a clean CRM, it’s critical to establish a uniform data input method and stick to your data cleanup practice. At the end of the day, your entire staff should be working with the same data to ensure that solutions are developed and that your clients receive full-service treatment.
Thanks to Mark Ryba at Business 2 Community whose reporting provided the original basis for this story.
