During the execution of an outbound prospecting campaign, CRM data hygiene is important. I’m going to share one of the processes we use internally to make sure users have a good way to “flag” inaccurate contact records.

When we come across an unworkable LEAD, a Salesforce.com or a ZOHO CRM field must be used for data quality reporting.  For instance, we use Salesforce.com’s “Lead Status” field with custom values in the pick list: Bounce, Wrong Number, No Longer with Company, etc. A pick list is the best way to do this because it standardizes reporting options.

Each month, we generate a report containing unworkable lead and contact data. That report is then sent to our Data Hygiene department (also known as “Karen”) where we use JigSaw, ZoomInfo and LinkedIn to correct and update the data. Once each unworkable email address is researched and corrected, we import the new data, delete the old data and begin prospecting anew. To avoid duplication during the import process, we export data with a unique identifier (such as a lead ID#). We then import the data using the same identifier. This helps ensure that any notes and or contact history are saved.

The Lead Status field is then reset to COLD so that sales reps know the LEAD is ready to be contacted again.

Data, like unrefrigerated milk, goes bad fast. In fact, by conservative estimates 25% of  the database will sour within a year. Add poor import practices and other minor mistakes and bad things quickly snowball. It isn’t until senior management realizes it is making strategic decisions on the back of sub-par data that heads begin to roll.

But head rolling is a complicated task. Do you get rid of the person responsible for cleaning the data in use or the person responsible for preventing low quality data from getting into the system in the first place? Do sales people bear some of the blame for not updating contact info? The marketing department for not scrubbing the unworkable e-mail addresses? Or should the executive team take a hard look in the mirror because clean data was not a strategic priority?

Some organizations try to fix the problem by assigning an intern to scrubbing the data instead of committing to a permanent process change. Others will look longingly for new gadgets, tools, hosted software, widgets, mobile apps or various marketing automation tools to fix the problem.

These items provide a wonderful, shiny distraction and maybe an incredible technology advantage, but they are no substitute for actually changing the process. Need to rationalize it to upper management? The ROI for clean data is simple.  All things being equal, a company with a larger database of clean prospects will close more business than a company with a smaller database of clean prospects.

Barry Trailer, co-founder of CSO Insights, confirms in an upcoming report what we all know: “The 2800 companies participating in CSO Insights’ 2010 Sales Performance Optimization survey confirmed what everyone knew: 2009 was the toughest year yet. But it was harder on some firms than others,” Trailer says. He adds: “Those implementing higher levels of sales process implementation, enjoying higher levels of relationship with their customers, and leveraging enabling technologies fared better than the rest. Of course, having accurate data to inform your systems and processes is key.”

Data quality is not a one-shot deal. Cleaning your data will cost money and so will the improvements to process that are needed to support ongoing data quality. But in the end, it’s worth it. Although the option to continue working harder not smarter is always appealing, a fast way to improve sales and marketing success is to fix things that can be fixed. Data quality is one of those items.