The Do’s and Don’ts of Data Cleaning – Don’t Drown in Bad Data

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Bad CRM data can compound exponentially, impacting marketing and business development. It’s essential to understand the scope of  your data problems and follow a plan for regular data cleaning.  

Have you ever heard the saying, “No man ever steps into the same river twice”? Because a river’s water is constantly flowing and changing, the water you step in today will be different from yesterday. The same is true for the data in your CRM system: people are constantly changing roles, relocating, retiring; companies are opening, closing, moving and merging.

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On top of that, new data isn’t always entered correctly. As a result, a database with clean, correct information today will not necessarily be accurate tomorrow. Over time, this bad data can compound exponentially, resulting in ineffective marketing, events and communication campaigns because as your data degrades, you reach fewer members of your target audience.

For professional services firms, poor data quality in your CRM system can also translate into a decline in system adoption. Once your professionals see bad data, they won’t trust the system as a whole and ultimately may outright refuse to use it. This is why we stress the importance of ongoing data cleaning.

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Data Cleaning Do’s and Don’ts

Simply put, data cleaning involves identifying incorrect, incomplete and/or dated data in your systems and correcting and enhancing it. If you have a large database with thousands, or hundreds of thousands, of records, the data quality process can seem daunting and overwhelming.

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While there’s no magic bullet or quick fix for poor data quality, ignoring data problems until there’s a crisis is not a strategy. Good data quality requires ongoing effort that never ends. The good news is that this means you have forever to get better at it. So, start now. Begin by assessing the scope of your data quality issues. Then, because it’s not always cost-effective or even possible to clean all your data, start by focusing on the highest priority projects.

Identify and Prioritize Your Most Important Data

All contact records are not created equal. For instance, client data is typically more important than non-client data. Additionally, individuals who have recently subscribed to your communications or attended an event are more important than those who last interacted with your firm years ago. Whatever segmenting scenario you select, it’s important to find ways to divide your contact data into manageable pieces because it makes the process more manageable and allows you to better measure progress.

Eliminate Stagnant Records

Related to prioritizing your data, don’t be hesitant about removing records that have been inactive for an extended period. Search your system for contacts that have not been updated for a few years, are not related to or known by any of your professionals, are not clients or alumni, and have not opened a communication or invitation in two to three years. Chances are good these records are not only outdated but also may not be worth the resources it would take to update them. Identify these records and consider removing them from the system. Less mess in your database makes cleanup a bit more manageable.

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Your Plan Is Your Life Preserver

Once you’ve prioritized subsets or segments of contacts, identifying and prioritizing your most common data errors can help you decide on the best way to tackle ongoing data cleaning. For example, if you have an important email that needs to be sent to clients, you need to focus on email addresses. Identify records that don’t have an email address, have incorrectly formatted email addresses or have bounced recently.

In addition, if there are contacts you haven’t sent a communication or invitation to for an extended period of time, it’s entirely likely that their email may no longer be valid. It’s important to regularly test emails on your lists because not doing so can cause you to be blacklisted by anti-spam entities or have your account blocked by your eMarketing provider.

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Initial Cleaning Cycle

The best place to start your data cleaning cycle is with a contact and list verification and cleansing service such as TrueDQ. This service will evaluate your list data, identify potentially harmful “honeypot” email addresses and even automatically update many of your contacts with current, complete contact information. The data can then also be enhanced with additional missing information, such as industries and locations, to help with targeting and segmenting.

Rinse and Repeat

When one segment or list has been cleaned, move on to the next one – bearing in mind that what’s important on the next list may be different from the last one. For example, maybe you need to send a hard copy postal mailing, so it will be important to ensure the accuracy of physical mailing addresses rather than email addresses.

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Bounces and Returns

One of the most common data quality failures at law and other professional services firms is ignoring bounced emails and returned hard copy mailings. Bounces and returns are real-time indicators that can help you keep on top of your data quality. Researching and correcting them is important because sometimes they involve important former clients who could potentially hire the firm again at their new company.

Returned hard mail will often include the forwarding address of the recipient, which should be corrected in your CRM. For emails, use a central email address to collect automatic email replies, since these frequently tell you when a recipient no longer works at an organization.

Ideally, data stewards should regularly review all bounces to take the onus off the professionals. However, it can also be helpful to generate reports on bounced communications and circulate them to professionals or their assistants who may be able to provide updated information – or will at least appreciate knowing which of their contacts have moved on or changed roles.

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Finally, if your eMarketing and/or CRM system has a process for automatically isolating bounced records, be sure you have a reciprocal process that automatically reinstates bounced records when the email field is updated.

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Prevent Invalid Data

There are multiple ways to encourage good data habits, depending on your system and method of contact entry. If your firm relies on manual data entry, implement a firmwide Data Standards Guide to inform users how data should be entered (e.g., does your firm spell out or abbreviate job titles?). It can also be helpful to use system validation rules wherever possible to require certain information in new records such as last name, city and email address to ensure your contacts are relevant.

Finally, regularly review newly added records for consistency and completeness. This process can reveal issues such as users who may require additional training on contact input best practices. It can also help to catch spam or other potentially dangerous entries that can sometimes flow into your database from online forms that are filled out by bots.

Never, Ever Stop

Just as rivers keep flowing, so does the data in your CRM system – and the data will always need cleaning to ensure that it is fresh. While this may feel like a relentless and burdensome task, never stop – just go with the flow –  because when you’re not regularly cleaning the data, your CRM “river” can become stagnant, and the more polluted it becomes, the longer the eventual cleanup will take.

Article By Christina R. Fritsch JD and Rachel Fields of CLIENTSFirst Consulting

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