CRM and the Danger of Dirty Data
Time doesn’t stand still. Neither do your customers. Face it. We are a nation on the move, and rapidly growing as well. In 2000, businesses filed 2.6 million change-of-address orders. There are a mind-boggling 140 million deliverable addresses in the United States, and the number is growing by nearly two million annually.
If you are considering a Customer Relationship Management (CRM) system, keep in mind that it will always be in a state of flux. Within just six months, more than eight percent of addresses in a typical database have the potential to be inaccurate due to move changes alone.
It’s not just physical moves businesses need to contend with. ZIP code and area code changes, contact, phone, or email address changes are other examples of how a database can quickly become outdated.
Dealing with Degradation
The message to take from this is data degradation in all CRM applications is huge—and must be dealt with on an ongoing basis. High quality customer data is necessary to achieve the true benefits of an organization’s CRM implementation, according to market researcher Gartner Inc. Without a data quality process in place, Gartner warns, enterprise CRM efforts will not be successful due mainly to missed opportunities and operational inefficiencies.
It is imperative that data in CRM systems is accurate so companies send accurate information to shippers, which helps ensure on-time deliveries. But there is much more to data accuracy—or data quality—than whether a customer’s address is correct.
For example, what is the profile of the address your company is picking up from or delivering to? Is it a residence? A business? An empty lot? It is crucial for companies to understand what that physical address represents.
Delivery point validation—does the address even physically exist?—is another important question that needs to be addressed and could conceivably help in fraud detection. Another consideration might be different shipping rates based on whether the address is a residence or business.
Understand that CRM is all about data. Bad data leads to bad business decisions. The quality of your CRM system’s information affects every aspect of your business. From routine daily transactions to long-term planning, smart and informed decisions depend on accurate and complete information.
The 4-Step Wash
How can you better manage the data that drives your infrastructure? Here are some keys to helping ensure CRM success:
Cleanse the data. All information should be cleansed before it enters the CRM system. Another key place to implement data quality is within the CRM package itself.
Consolidate the data. Combining databases or data sources can be difficult, as each may have been created independently and on different platforms. With a data quality solution, customer and business information such as store customer name, address, and contact data, can be normalized and corrected before it is loaded into the CRM system.
Maintain the data.Data quality is a continuous process. Information becomes dated, people move, businesses relocate, businesses acquire new customers, and postal codes change. You need to continually improve and fine-tune business rules as you learn more about your company and your customers.
Create a single customer view of the data. One of the main principles behind CRM is that there is only one record for each client. Unfortunately, even the most sophisticated CRM systems aren’t capable of maintaining a single record per client without accurate, cleansed data. A single customer view means that everyone can access and use the same information.
The next time you send a delivery truck to a wrong pickup address, take a good look at the data in your CRM system and think about how it is collected and maintained. If you don’t have a process in place to analyze, cleanse, standardize, and consolidate your data on an ongoing basis, consider the fact that some of your key customer information became outdated in the time it took you to read this article.
Isn’t it time to do something about it and come clean?