Customer Data Quality

When customer data quality is faulty, this can have a negative effect on the company or business. Employees end up doing and redoing their work, customers become dissatisfied and can complain day in and day out to your employees, and chaos can become a daily occurrence at work. This can drive the customer relations manager crazy and when consumers are unhappy and complaining, employees can in return be irritable and tired, then productivity becomes scarce and profits decrease.

So where exactly does the trouble lie? Every day, customers interact with the company in various ways. They interact through Emails, forums, sales, online shopping, etc. Customer data is acquired through each of these transactions and this data can be used to monitor quality customer service. However, through all these avenues, customer data becomes lost in chaos, duplicates are made, and inconsistencies occur. When a customer information database on consumer behavior is made with much inconsistency, this can result to a disastrous return on investment analysis.

With the increasing demands of customers and the expansion of customer data silos, company managers now know that CRM data quality has become an absolute must. However, even with these occurrences, data quality management issues are still left unaddressed.

The nature of the problem makes it difficult to fix, after all, it is always easy to pass the blame to the next person. (The blame tends to go to the IT people who configured each system). Nevertheless, top companies have risen to the challenge and they have identified that customer data management and quality should become one of their top priorities. Taking action on this, they in turn have really made this one of their top priorities.

Studies have shown that it is the best performing companies that are most likely to identify data quality as a priority. Significantly, it is these companies who are dedicated to improving customer data quality, that also are at least four times more likely than other companies tostate gains in their performance, customer or oganizational key indicators. It is these top performing companies that have better results in improvement of usability of customer data, customer data integrity and time it takes to prepare customer data destined for business use. Other companies who haven't taken any action in improving data quality are the ones who suffer the losses.

To get these results, these top companies have a methodical and organized line of attack when it comes to customer data quality initiatives. These companies invest in data process management, data collection, cleansing and analysis tools. These companies have also, most of the time, a dedicated data manager or a data steward that hold accountability for data quality initiatives. Plus a process is made on how to get cross-functional agreement on data quality goals, actions and priorities.

Another thing that places top performing companies a cut above the rest is the propensity measure operational key performance indicators or KPI's, as well as link customer and revenue KPI's to data quality initiatives

Here are some suggested steps that other companies should take in order to keep up with, and attain the success of top performing companies in customer data integration and management: note that for these steps to give you the desired results they need to be part of the best customer retention strategies implemented in your organization.

•    Learn by doing. Like any endeavor, you learn best by doing it. This principle also applies to attaining customer data quality. Companies who don't have an established, cross-functional, data quality programs must start with a pilot program and have benchmarks and quantifiable success criteria to improve the process and ensure success when the data quality software is finally run.

•    Top performing companies have linked successful customer data quality programs to improvements in both financial and customer key performance indicators or KPI's. Other companies that are just starting out with these initiatives must measure the KPIs as a basis to calculate the return on investment of their data quality software.

•    Customer data quality is a cross-functional problem. Because of this, someone, such as the data manager, should be able to cross organizational boundaries to be able to negotiate and handle program priorities.

•    Finally, the top performing companies are the ones that invest in data quality technologies, and process enablers for data gathering, analysis, cleansing, storage and archival. Companies, that want to achieve what top companies have to invest in such technologies or include these costs in their next budget planning.

Ultimately, leaders in marketing and sales should realize that customer data quality is a business issue. If they get it right, that would make a massive difference in their competitiveness. Unfortunately for other companies, though, there is a long way to go before they can become like the top companies.

These top companies are foreseen to implement enterprise data management solutions, and formal master data management programs. With sophisticated customer data quality solutions, it is absolutely critical to put an investment in the basics and plan the right structure and put it to place before other companies can finally reach where the top performing companies are now.