We have come a long way since the old term “garbage in, garbage out” was first used to describe flawed –i.e. garbage — data input that produces flawed “garbage” output.

Since then, data management has evolved tremendously; progressing from manually inputting commands on a black screen with lines of green text and a flashing cursor, to today’s sophisticated operating systems with artificial intelligence capabilities built into the tool, these advanced systems can help us find accurate contact information, curate content, and automatically gather and store information in a centralized location. 

Despite all this power and technology at our fingertips, garbage data continues to pile up. People change their names, get promoted, quit their jobs, move to different companies or places. Companies relocate, get acquired, go out of business, change domain names, addresses and phone numbers. If left unattended, the bad data will start piling up in your CRM, leaving a literal “landfill” of garbage data.

So how does this garbage data affect our CRM strategy, and how can we safeguard our CRM from letting in any more garbage?

1. Duplicate Data

Duplicate data occurs when a contact’s information appears more than once in a database or when multiple variations of the same contact appear. This can leave hundreds or thousands of duplicate company or individual records in your ‘landfill’. These duplicates make it extremely difficult to coordinate efforts and activities.

Secondly, duplicate data can seriously harm your firm’s image. It is unlikely that a contact who receives the same information twice will be happy about it. This is a surefire way to annoy customers and prospects and make your organization appear disorganized.

2. Missing or Incomplete Data

Missing or incomplete data can cause your contacts to miss important engagement points with your firm. Without complete and correct data you cannot target or segment your database, and the firm’s communications won’t reach its intended audiences. Similarly to duplicate data, incomplete data can damage your firm’s reputation and overall performance. 

To ensure data is entered in its entirety, firms should establish data capture protocols that require certain felids to be consistently entered. Firms can also utilize AI algorithms or other integrated tools to identify and finalize incomplete records to improve data accuracy.

3. Incorrect or Inconsistent Data

Inconsistent data entry is one of the biggest challenges firms face when it comes to achieving data quality success. This occurs when multiple individuals enter data using different abbreviations, formats or standards when entering new contacts. One person may abbreviate first names (C. Fritsch) while another types names out (Chris Fritsch). This makes it very difficult to maintain consistent and accurate data, and can even disrupt the buyer’s journey.

Creating consistent data entry can be done by establishing clear guidelines informing attorneys and other end-users how data should be entered, and implementing validation rules that enforce standardization. We also recommend regular data quality audits and ongoing data stewardship to help maintain long-term integrity.

4. Too Much Data

Firms with extensive databases can find themselves in, what I like to call, data analysis paralysis. This happens when firms have too much data sitting in disparate, disconnected systems and they don’t know what to do with it.

Having too much data can be overwhelming and unnecessary. It is important to set parameters on incoming data so you collect what is only necessary for your contacts and prospects to receive communications and maintain only that information moving forward.

5. Lack of Data

Too often, firms are willing to spend money on data quality cleanup but don’t budget for other essential resources. Investing in the time and human resources required for success is just as important, if not more, than investing in technology. Dedicated data stewards are not only necessary, they are essential.

Additionally, an estimated 30% of contact data becomes outdated each year as people move, change jobs, get married and have other status changes. This means ongoing data quality support will be required because if attorneys don’t trust the data, they won’t trust the system.

If your firm is hesitant to allocate the funding necessary to maintain the required resources for data quality success, this infographic outlines the significant cost savings outsourcing data quality work can provide your firm.

Ensuring data quality is crucial for leveraging the benefits of CRM systems. While the journey may seem daunting, with a structured approach, maintaining quality becomes feasible.

Put processes in place to make ongoing data reviews routine. Go through bounced emails after each campaign or mailing and, at a minimum, remove them from lists. A better process is to have internal or outsourced data quality resources research the contacts to identify where they are now so you can keep in contact with them.