Home > Customer Data Management | Digital Solutions | eClerx

Delivering Integrated Customer Data Quality Assurance Offshore

Customer Data Management

Many companies and industries are moving from product-focused to customer-focused marketing and sales efforts. Customer data is one of the most, if not the most, vital types of data in any organization. The reality is that most firms suffer quality issues in their prospect and customer data - inconsistencies, duplicates, multiple systems and “sources of truth” - that ultimately hamper the sales and marketing teams and their goals. 
Whether you are managing a formal master data management and customer data integration project, or cleansing and de-duplicating data for a marketing campaign, eClerx enables companies to focus on the core strategy (driving business), by taking on key projects and ongoing maintenance to improve our clients’ customer data quality. With years of experience in master data management and across industries, eClerx utilizes industry best practices and deploys a “Customer Data Quality Management” framework to improve data quality and manage business processes more effectively.  
We enable our clients to strategically improve the quality of their customer data. By addressing these parameters through a structured and rigorous execution, our clients’ broader business goals experience significant lift, including: 
  • Contact reach
  • ROI on marketing and sales campaigns and initiatives
  • Reduced total cost of owning and maintaining data
  • Reduced costs / better ROI on acquisition of 3rd party lists and contacts


  • ​Disparate data sources with missing links within and across databases
  • Lack of governance / no clear process on addition, updates and EOL of records
  • Lack of business rules to maintain and manage customer data
  • Data exchange between systems (ERD) not documented, dated or incomplete
  • Lack of data quality measures or dashboards
  • Lack of time to generate new suspects and prospects for marketing and sales team
  • Big investments in digital analytics, sales and marketing automation systems, but unable to leverage or reconcile data from and across these multiple systems
  • Inability to track customer lifecycle and leverage customer analytics
  • Single customer receiving multiple, concurrent campaigns
  • Lower-than-average industry open rates, click through's and bounce rates
  • Sales team frustration with inability to close opportunities due to bad data
  • Despite multiple touch points and interactions with customers across marketing, sales, web, customer care, etc., no single view of the customer exists


  • Account, contact and prospect data augmentation to improve data quality
  • Data enrichment and attribution
  • Data cleansing and stewardship to ensure consistency across multiple data sources
  • Data quality insights –
      • Data visualization
      • Descriptive analytics on pre- and post-data quality efforts
  • Account, contact and prospect lead generation services
  • Multi-channel data integration to enable one view of the customer
  • Customer and account hierarchy and taxonomy
  • Best of breed benchmarking to drive strategic roadmap on customer data quality


  • Improved data quality and improved process efficiency through matching and de-duplication plus automation
  • Aligned processes and business rules drive consistency in customer hierarchies, enabling better targeting and enhanced customer experience, increased effectiveness of sales and marketing teams and most importantly, fuller pipelines and more sales
  • Reduced total cost of ownership as clients drive toward consolidated systems, one source of truth and the ability to focus on the data that matters
  • Standardized reporting and data quality dashboarding that drives increased visibility and insights, resulting in higher confidence and decision support and direct revenue lift on sales and marketing programs and initiatives
  • Core client in-house team focused on strategic initiatives, while eClerx team takes on the critical, yet time-consuming data governance and quality processes