4 Best Practices for Automating Contact Record Data Validation

Contact records are one of your most valuable assets. According to Salesforce.com, 70% of your contact records will change in one way or another each year. Making sure that they are accurate and up-to date ensures you are getting the most from them and resources are not wasted attempting to contact customers and prospects through bad or outdated information.

Fortunately, the process of validating and maintaining up-to-date contact information is increasingly easier and can be automated through contact record validation APIs.

Best practices for automating data validation:

Here are four best practices to consider when automating the validation of your contact records within your company.

1. Create a culture where everyone understands and values data quality

Contact records are one of your company’s major assets, touched by multiple departments with different needs and how they use the data. Everyone has a stake in trustworthy contact records. Adapting your company culture to value the importance of genuine, accurate and up-to-date contact details means every employee has a responsibility for improving data quality.

Establishing this philosophy early is important for getting buy-in for implementing and continued support for data validation automation.

2. Establish where the need is

Understanding how and when your contact records are used will drive your data validation needs. A simple exercise is to look at how each department interacts with a contact record and how they use it.

Marketing:

Marketing has two main use cases for data validation; when the prospect is initially captured and subsequent outreach marketing campaigns.

When initially capturing the contact’s information, the type of validation will be largely dependent on the data fields being captured. For example, a whitepaper signup might only require name and email address, whereas a free trial might require name, address, phone, and email. The good news is that there are different validation services to meet each need.

When launching new campaigns, it is best to check the prospect’s contact details for changes. This not only ensures better campaign success but also helps with compliance of privacy regulations, like Telephone Consumer Protection Act (TCPA).

Sales:

For the Sales department, accurate data is key to communicating with prospects quickly and efficiently. Improved contact rates results in increased sales.

Customer Care:

According to Forbes, businesses are losing over $62 billion per year due to poor customer service. For the customer care team to provide great service and timely resolution of issues, they require up-to-date contact information.

Finance:

For the Finance department, it is straightforward: cash flow. Returned invoices and payments due to incorrect addresses require additional resources to resolve and impedes forecasting and cash flow.

3. Validate often

As discussed, 70% of your contact records change over the course of the year. Using real-time data validation APIs to keep them up-to-date, after they are initially captured, allows each department to approach a contact record with confidence. This means no matter when a department reaches out to your contacts, they know the record is accurate.

4. Introduce a data steward

Just because you’ve automated data validation doesn’t mean you don’t need to check in on the process. A data steward can be essential to this process, owning responsibility for data validation.

A data steward is someone who ensures your automated validation processes are running smoothly, tests the data quality and develops front- and back-end checks that are tracked and reported on.

Starting with these best practices helps ensure early adoption and support for integrating automated contact record validation. Continuing to monitor and measure the impacts of these efforts will demonstrate the strong ROI associated with good data quality.

Subscribe to our blog