Issues with substandard Data Quality
Quality of data plays a major critical role in industries like retail, telecommunications & financial services with large customer base.
Most organizations falling under these industries in a rush to capture market share and to add new customers give secondary thought to quality of data captured, leading to substandard customer data with inaccurate, duplicate & outdated customer details.
Inaccurate or poor customer data is due to non standardization of data capturing process or format, multiple data capturing points across the organization & data storing in incompatible systems and formats.
Organizational impacts due to poor data quality
- Business performance – Due to duplication of data it’s difficult for marketing to cross sell other products and services, profiling and segmentation of customers leading to decrease in business performance
- Customer retention – Due to poor data quality cost of customer retention is high as it requires multiple interactions with customers to understand their actual requirements which would have been solved with accurate data and past transaction details
- Customer Mapping – Due to multiple entries of same customer with contradicting details it would lead to wrong mapping of customer s with wrong product or service leading to valuable customer loss and revenue to organization
So organizations with large customer data should ensure their data capturing methods are standardized across all data capturing points with latest data integration software for a satisfied customer and profitable organization.
