How can you maintain CRM data quality and hygiene?

CRM data quality and hygiene are essential for any marketing operation that relies on accurate and relevant customer information. Poor data quality can lead to wasted resources, lost opportunities, and damaged reputation. How can you maintain CRM data quality and hygiene in your marketing operation? Here are some tips to help you.

1 Define data standards

Before you collect, store, and use any customer data, you need to define clear and consistent data standards. Data standards are the rules and guidelines that specify how data should be formatted, validated, and updated. For example, you might have data standards for naming conventions, email addresses, phone numbers, and lead stages. Data standards help you ensure that your data is reliable, consistent, and usable across your marketing operation.

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Blaine Tetterton

Marketing Operations Fanatic | PMP, Sales Ops, Revenue Growth, Lead Generation
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A good way to find your data standards is to identfy your target persona. Review the information you would need to reach out to them in a wqay that they respond to, ex if they are not on linkedin then your don't need that as a field. After outlining your required fields, find the variations that can occur when that info is updated. Country and state are some of the most common to give issues. Next review all sources that input the data into your CRM and adjust as many of them to align to your standard.

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2 Implement data governance

Data governance is the process of managing and monitoring your data quality and hygiene. Data governance involves assigning roles and responsibilities, setting policies and procedures, and establishing metrics and indicators. Data governance helps you ensure that your data is compliant, secure, and aligned with your business goals. For example, you might have data governance roles for data owners, data stewards, and data users. Data governance policies and procedures might include data entry, data cleansing, data enrichment, and data auditing. Data governance metrics and indicators might include data accuracy, completeness, timeliness, and relevance.

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Blaine Tetterton

Marketing Operations Fanatic | PMP, Sales Ops, Revenue Growth, Lead Generation
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Do not ignore GDPR or Can-Spam laws. You need to know what they are for your target areas and have your unsubscribe and opt out options set accordingly. Always check that your rules in your marketing automation and CRM match and connect! Forms should have privacy policy information, emails should have opt out features and your systems should be storing and accounting for those.

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3 Use data quality tools

Data quality tools are software applications that help you automate and optimize your data quality and hygiene. Data quality tools can help you perform various tasks, such as data validation, data deduplication, data standardization, data enrichment, and data analysis. Data quality tools can help you save time, reduce errors, and improve efficiency. For example, you might use data quality tools to verify email addresses, merge duplicate records, normalize data fields, append demographic data, and identify data issues.

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4 Train data users

Data users are the people who access, manipulate, and leverage your customer data for various purposes, such as marketing campaigns, sales outreach, and customer service. Data users need to be trained and educated on how to use your data quality and hygiene practices. Training data users can help you increase data literacy, awareness, and accountability. For example, you might train data users on how to follow your data standards, adhere to your data governance policies, use your data quality tools, and report data problems.

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5 Review data regularly

Data quality and hygiene are not one-time events, but ongoing processes. Data changes constantly, as customers interact with your brand, provide feedback, update their preferences, and move along their journey. You need to review your data regularly to ensure that it reflects the current state and needs of your customers. Reviewing data regularly can help you identify and fix data errors, gaps, and inconsistencies. For example, you might review your data monthly, quarterly, or annually, depending on the volume and velocity of your data.

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Blaine Tetterton

Marketing Operations Fanatic | PMP, Sales Ops, Revenue Growth, Lead Generation
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Reviewing your data has many points. Is your data updated and current? Do you have your unsubscribe contacts properly segmented? Are you removing spam/junk/test records that aren't needed? These are the normal questions to a healthy database. However you also want to measure the database stage. What % of database is marketable? What % is in your ICP? Are your contacts the proper personas you need to target? What stage are they in? By knowing your database inside and out you will be able to contribute to sales and marketing on what type of programs should be run, where they need to target, who engages, and if there will be enough pipeline.

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6 Seek feedback from data stakeholders

Data stakeholders are the people who have an interest or influence in your customer data, such as your customers, prospects, partners, vendors, and employees. Data stakeholders can provide valuable feedback on how to improve your data quality and hygiene. Seeking feedback from data stakeholders can help you understand their expectations, needs, and challenges. For example, you might seek feedback from data stakeholders through surveys, interviews, focus groups, or online forums.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you maintain CRM data quality and hygiene?

1

2

3

4

5

6

7

1 Define data standards

2 Implement data governance

3 Use data quality tools

4 Train data users

5 Review data regularly

6 Seek feedback from data stakeholders

7 Here’s what else to consider

Marketing Operations

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How can you maintain CRM data quality and hygiene?

1

2

3

4

5

6

7

1 Define data standards

2 Implement data governance

3 Use data quality tools

4 Train data users

5 Review data regularly

6 Seek feedback from data stakeholders

7 Here’s what else to consider

Marketing Operations

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