Do you know if your prospect and customer data quality is high? When was the last time you benchmarked your data? Do you regularly conduct a data audit?

Having CRM and Marketing Automation platforms aren’t enough. Over time your customer data accuracy naturally erodes. Prospects and customers move companies, are promoted, and so on. This is a missed opportunity to effectively nurture your leads and customers.

What can be done to prevent data inaccuracy and incompleteness?

To ensure data accuracy upon entry, standardize your CRM or database so that all fields align with your marketing automation platform. This may require additional integration if you’re using multiple platforms; however, considering the investment already made into these tools, your ROI is going to be limited if your data isn’t synchronized and standardized across channels. Also important is mandating a standardized field entry process. Make essential fields required and communicate with marketing and Salesforce to set expectations for data entry.

You can also leverage third-party tools and plug-ins that automate the completion of empty fields. For example, Microsoft Dynamics has Insights, powered by InsideView, which will fill in account records with targeting intelligence (i.e. account news, social media updates, and company data) pulled from their global company and contact database.

Assign a data team or steward to start to perform regular audits, set standards, and maintain data. The data steward can also identify ways to automate data maintenance and further enrich data.

As personalized and targeted communications have become the new normal for nurturing leads and customers, it’s crucial that customized content reaches the right contacts through the optimal channels. Your touchpoints can come off unprofessional and even damage your company’s reputation if you’re communicating erroneous messaging to the wrong contacts.

If you’re continuously utilizing and enhancing your marketing automation and CRM tools, then it’s worth the investment of time and resources to ensure high data quality.

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