How do you handle duplicate, incomplete, or outdated records in your CRM?

Bad data in means bad data out. Bad data out can cause issues with marketing automation in the form of untimely communications, incorrect audiences and errors that embarrass your end users and confuse or irritate your audiences. Having quality data allows you to ensure clean and timely marketing communications that helps to facilitate a positive customer experience and drive business growth.

Garbage in, garbage out. Everyone knows it, yet when the time comes to make sure data is reliable, no one wants to do the work. Every company should have at least one person in charge of your CRM data. Don't compromise on data quality.

Who hasn't heard: Garbage in, Garbage out! Data duplication is one of the biggest challenges I've seen in a company's data. Along with creating confusion, the duplicate data can severely impact the company's analytics, artificially skewing activity and metrics. Setting up methods to prevent data duplication is crucial to ensure you get accurate data and a view of your business.

Top three data quality issues - & what to do about them: Duplicates: set duplicate record alerts; implement a deduplication tool; automate own deduplication logic with an integration platform. Incomplete records: enrich online searchable data points with APIs; setup mandatory fields or counter reports for data Sales needs to collect; prefer rule-based over systematic enrichment. Old data: log enrichment date and source; re-enrich old records before re-assigning them; delete old records.

Reinforcing the importance of entering quality data from the start is key. If the people entering data don’t understand the importance of clean l, up-to-date information, you may forever be counting on these tools. Showing people the result of poor data versus the benefits of clean data can help with understanding.

There are two kinds of Customer Relationships. If your CRM is driven by repeating sales to a ‘regular’ customer, then it is easy to have all the main criteria that the system needs. This happens in B2B relationships. Often it works both ways with the customer also using a Vendor Relationship Management system (VRM.) If the CRM is being used as a customer acquisition tool starting with Leads that convert to qualified Prospects with an ultimate goal of converting them into Sales, the CRM as a tool must be flexible enough to allow data entry over time. In a B2C relationship a lead may not be comfortable giving their name, phone number and email data all at once. The CRM must not be driven by email, text, phone, or in-person visits.

Most CRMs have a native feature to deal with duplicates. Mostly, these are at the person/organization level and can be dealt with manually. There are also dedicated deduplication solutions like Dedupely that make the job a lot easier by defining complex rules for duplicate detection.

In my opinion bad data comes from one of two sources: incorrect entry by users or incorrect imports. And both of these are a direct result of lack of training. The database administrators can set all the rules they want for "standards" and "policies" but at the end of the day if the users aren't properly trained the CRM will fail.

With data coming in from multiple sources that often vary based on the user, it's nearly impossible to ensure that all data coming in is accurate and complete. Data clean up needs to a be a part of every CRM users workflow. Set aside 1 to 2 hours a week to clean up contact records, merge duplicates and hunt down missing data. It may seem like pointless busy-work, but you’ll thank yourself in the long run when your database is squeaky clean and you’re able to work much more efficiently.

To increase the odds of getting quality data from the start (good data in), it's important to take a look at your form strategy. Do all the fields in your forms align? Are you using uniform picklists for segmentation-related questions? If some of your forms are intentionally shortened, do you have a lead enrichment or progressive profiling strategy to populate any missing information over time?

It takes consistent effort to keep your data clean and maximize its usefulness. Everyone in your organization that works in your database needs to know what good quality looks like. You have to establish checks and catchpoints to make sure new data goes in as cleanly as possible and also routinely audit what's already there to maintain its quality. Data quality tools and other software can be very helpful but they don't do much without proactive efforts from your team. The bottom line is that it takes time and effort to keep your CRM or any other data in good order. Without directed effort to maintain it, the natural progression of any system is towards disorganization and entropy, no matter how organized it was at initial setup.

The only way to do this effectively is to get buy-in from the entire team. Data cleanliness doesn't just fall on your CRM admin or Revenue Operations team, just like customer retention doesn't just fall on your Customer Success team. I've found the main reason you don't have buy-in from your team is they don't understanding the impact. If you're a CRM admin or RevOps leader, share with the team how data accuracy impacts their role, department, & paycheck with a compelling story. If everyone takes the few extra seconds to keep CRM data clean, the business will benefit tremendously.