If you read my previous blog Garbage In, Garbage Out – The Real Cost of Poor Customer Data, we established that customer data quality problems are impacting many organizations whether small or large, domestic or international, private or public.
The problem is large. Experian research on the effect of dirty data on business showed most businesses, 84%, experienced data quality challenges. In economic terms, D&B cited it was a $600 Billion impact or 5% of the U.S. GDP in 2001, The Cost of Poor Data Quality – Dun & Bradstreet.
Recognizing that we need to “take the trash out” of the data, pun intended, how do we improve our customer data?
Most organizations lack a customer data strategy – Experian research cited “74% of companies do not have a sophisticated approach to data quality and could improve upon their strategy.” So here’s an opportunity gap most companies can take advantage of.
See Also: Garbage In, Garbage Out – The Real Cost of Poor Customer Data
There are a number of important concepts to help your business start improving customer data quality:
1. Drive data quality from within – make data quality a top organizational priority. If it’s important to the leadership team, it will be important to the entire team. Accordingly, resources will be allocated to support data quality initiatives.
Centralize data management under a single leader – singular focus and responsibility will establish a cohesive and systematic approach to data management throughout the organization.
Determine who will lead, develop and implement the data quality process and assign authority and responsibility to the role.
2. Establish a centralized data quality process – data collection, integration and leverage are the core elements of the process. Subcategories important in developing the process include definition, education and maintenance to achieve quality data.
Build the process with your customers at the center of the process, mapped to your customer touch points. This is a customer-centric approach that enables the company to engage with customers where they want to interact with the organization.
3. Measure, quantify and report the impact from the investment in data quality – define data quality metrics, execute solutions and calculate improvement and share your results. Performance measurement is imperative. What you don’t measure, you can’t improve!
Data quality metrics include duplicate records, partial records, bounced emails, returned mail, etc. Define them and establish a baseline before implementing your quality program.
Execute data quality programs in a defined period of time. This should start after the data quality tools and processes have been implemented real time. Set the time period start measuring both positive and negative results.
Share your results. Objective and proactive reporting will help determine success or failure of the quality processes and tools, but more importantly, there will be insights to continuously improve.
In my next blog, I will expand on the data quality process. If you are dealing with “taking the trash out of your data”, please let me know how you are doing it.
I would like to acknowledge that some of the research and quotes included in this blog come from white papers at Experian Data Quality of Boston, MA.
See Also: Why Your Business Needs Analysis
The post Take Out the Garbage … Improving Your Customer Data appeared first on Marketing In Color.
