How To Ensure that Your Customer Data Is Timely and Accurate

Computer programmers have two proverbs that every sales manager with a CRM system should know. The first proverb is: “Garbage in, garbage out.” In other words, if the information that you put into your system is flawed, everything else that comes out of the system – reports, action items, etc. – will be flawed as well. The second proverb is: “Data has a tendency to rot over time.” This means that even data that is accurate when entered can become out-of-date, or (worse), be rendered inaccurate through careless updating and typographical errors.

These proverbs apply to CRM, probably more than any other type of software, because CRM is more likely to end up with bad data in the database. The problem isn’t in the software itself, but in the fact that the “owners” of the data entry process are typically sales reps whose primary skills involve human relationships rather than computers. Most sales reps – even those who sell for high tech companies – do not want to become computer programmers, much less data entry clerks. Not surprisingly, reps generally want to get on and off the CRM system as quickly as possible and thus aren’t likely to quibble over the occasional typo – not realizing that that typo might someday result in a lost sale.

Because of this inherent cultural tendency, every successful CRM application must have the integrity of the data in the system as a primary area of concern, according to CRM guru Barton Goldenberg. “Every CRM implementation should, from its inception, have a strategy for data integrity, which includes documenting the current data inventory, developing data standards, consistent cleansing of existing data, and developing processes to maintain, change and enhance the quality of that data.”

Here are the key steps for building a data quality strategy:

1. Understand the information needs of your company’s sales reps and use that understanding to set up a master enterprise data architecture that provides a unified view of your customer base. Then secure executive commitment to make sure that your subsequent data quality efforts are supported.
   
2. Determine the cost/benefit of integrating data from different sources prior to commencing work on the master data structure. You may discover that it is less expensive and time-consuming to recreate or reenter the data than to integrate your existing data sources. This may especially be true if your current data is in poor shape.
   
3. Implement data integrity toolsets to help ensure that data is entered in a consistent fashion. These tool sets should be integrated into any enterprise application (i.e. not just CRM!) that utilizes and updates your customer data. These tools also contain business logic to make sure that the data follows naming conventions (such as addresses, product names, components, order numbers).
   
4. If your company is global, ensure that the data integrity tools provide local language comprehension, for example, the local word and abbreviations for “Street” versus “St.”, “Avenue” versus “Ave.”, etc.
   
5. Set up a data quality audit task force of employees who use customer data at various levels of your organization. Require them to develop and maintain an ongoing data quality standard and review customer data quality on a regular basis.

The above is adapted from information provided by well-known CRM expert and consultant Barton Goldenberg, who has helped numerous companies to select and implement successful CRM systems. He can be contacted at 301-656-8448 or through www.ismguide.com.