Bad Data Prevention: Best Practices for Developers

Bad data quality creates trust issues. It can destroy the trust your sales team places in sales funnels, the trust your customers place in your company, and the trust executives place in data-driven decision-making. As a developer, you are in a unique position to stop bad data from entering your databases.

Sometimes good data goes bad

The first threat to your databases is natural decay, which occurs at an estimated rate of 31 percent per year. Without a proper data cleansing process in place, natural decay is going to take place due to everyday occurrences like job changes and promotions, contacts moving to different departments or regions, and companies merging or closing.

Sometimes bad data creeps in

The second threat to your databases is dirty data entering your systems due to things like human error at the input source and duplicate data that could have been prevented. This added bad data creates problems for everyone who touches that database or makes decisions based on it.

The problem of bad data is pervasive

No matter how much bad data exists in your database or enters it, it creates issues for developers. Some possible impacts:

  • You may be asked to customize solutions in a Salesforce instance that temporarily or partially deter bad data entry, but don’t really address the underlying problem
  • A lack of trust in the data creates indifference among users, thwarting your attempts to establish and maintain data quality controls
  • You create user interfaces, deploy new software applications, establish testing parameters, or generate analytics that are based on inaccurate or incomplete data
  • A workplace culture complacent with poor data impedes your ability to help Salesforce admins improve CRM data and streamline its maintenance

Recognizing the business need to address bad data

Some companies have a healthy respect for data quality, creating an internal culture that enforces data integrity and an external reputation for achieving it. For many others that don’t, the problem of bad CRM data eventually becomes impossible to ignore.

Company databases grow over time and the teams that rely on those databases to create operational efficiencies or generate important metrics often reach a tipping point concerning data quality. At this critical stage, the organization is forced to acknowledge that bad CRM data is exerting a significant and persistent drag on its operations and ability to meet strategic goals.

What can you do before bad data reaches crisis stage?

  1. Make a solid business case for good quality data. Help your organization and its key players understand that having a competitive advantage with data integrity has never been more important. Getting business executives to take notice and take action doesn’t always require a customer outcry about data breaches or a massive loss in expected revenue due to poor data quality.
  2. Move beyond the native tools of your CRM. Data-driven organizations need more than the standard toolsets. Adopt advanced solutions that integrate with your API and can identify, flag, and fix data issues ahead of time. Investigate third-party options on the Salesforce AppExchange and present recommendations that fit the data requirements and business goals of your organization.
  3. Create a system of prevention. Prevention is about guarding against the pollution of the CRM system. Often, it comes down to education. Work with managers and users on the little things that, together, can prevent bad data from entering the database in the first place.

Preventing bad data in your CRM

From a cultural point of view, prevention works best when policies and guidelines are shared and updated transparently. It is also most successful when developers and data admins foster a supportive atmosphere in which users are comfortable asking questions, discussing problems, and suggesting improvements.

Encourage and work with admins to create an effective system of prevention:

  • Develop clear usage protocols
  • Restrict access as appropriate
  • Train users to check for duplicate records before entering new information
  • Use a real-time deduplication tool to define how you want duplicates handled
  • Use a real-time email verification tool to support more effective digital marketing campaigns
  • Custom code to your business needs and use third-party apps that support your code
  • Rigorously enforce naming conventions and data field requirements

Data cleansing protocols are key

The second piece to this is remediation, which is about keeping the CRM system clean on an ongoing basis. As we have covered, data quality degrades very quickly and exponentially, so it’s vital to continually check it and correct anything erroneous or out-of-date.

Ideally, data health checks should be conducted on a set schedule – perhaps daily or weekly – alongside the use of a real-time duplicate prevention tool. Data cleansing scenarios can be created, customized, automated, and expanded upon as needed with third-party apps.

Be a catalyst for change

The data industry is becoming more complex, as are new technologies to handle databases of all sizes. To stay ahead of the curve, organizations will need to recognize and value the importance of data quality, including investing in the right tools to preserve and enhance the integrity of their information.

Resources for developers

We invite you to check out these additional resources from Validity.

  • Options for advanced developers with Apex Code and Visualforce experience
    • On Validity’s Apex Developer Options page, we provide details for how you can further customize DupeBlocker 3 to fit your specific business needs.
    • On this DupeBlocker settings page, we describe how to bypass records for round robin assignment and tracking (click on the quick link for Insert/Update Action Tracking Fields).
    • On this DupeBlocker scenario details page and in this article from our Knowledge Base, we describe a way to customize the redirect to (existing) Visualforce pages and a custom Apex option for the match on insert action.
    • On this DemandTools page, we describe how you can use regex in matching.
  • Dreamforce presentations: Meet the Validity team during Dreamforce at Booth #216 in the CloudExpo or visit us in the Trailhead Zone (look for your chance to win a Bose speaker). We encourage you to bookmark our presentations today and mark your calendar.
  • Validity Community: If you are not yet a member of the Validity Community, please check out this valuable resource hub filled with product solutions, tips and tricks, FAQs, recorded training webinars, and more.

About the author

Mark Briggs is the Chairman and CEO of Validity, Inc.

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Bad Data Prevention: Best Practices for Developers