Data quality for sales and marketing
Resolve contact data decay in CRMs, Excel sheets, and other data sources through deduplication and data cleansing to lower customer acquisition costs and increase customer lifetime value goals.
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How bad data affects sales and marketing?
CRM data decay causes significant loss in revenues
High bounce rates
Increased email bounces due to typos, punctuation errors, or data decay can lead to a loss of domain reputation.
Missed or Returned Mails
Unverified or incomplete address details, such as street names and ZIP+4 codes, can result in failed deliveries and returned mail.
Poor Employee Productivity
Sales and management teams spend nearly 50% of their time on basic data quality management tasks.
Lack of personalization
Inaccurate or incomplete information can limit the personalization needed to tailor campaigns to customers’ buyer journeys.
Duplicate marketing efforts
Customers can mistakenly become recipients of campaigns meant for others that can increase attrition rates.
Data Decay
Potential sales losses due to contact details such as email and phone data becoming quickly out-of-date and obsolete.
Solution
DataMatch Enterprise – Convert Reliable Data to Sales
DataMatch Enterprise provides marketing companies with robust list matching and cleansing solutions to prevent losses from data decay. With prebuilt CASS-certified address verification, intuitive data cleansing tools, and fuzzy matching algorithms, obsolete, duplicate, and redundant contact details can be removed to improve campaign engagement and response rates.
Customer Stories
See what marketing organizations are saying...
We obtained 24% higher match rate using DataMatch Enterprise™ versus our standard vendor.
We like the way it speeds up the process on anything we do with data, instead of having to run scripts.
DataMatch™ makes it a lot easier for me to match columns in Excel. My whole reason for getting the software was to match up sold vehicles with leads that we’re working
Business Benefits
What’s in it for you?
Set Data Standards
Standardize account names, contact names, and addresses by adjusting suffixes, initials, or abbreviations to achieve data consistency.
Validate Data in Real-time
Leverage real-time APIs to ensure that data submitted through input forms complies with predefined rules before entering your CRM.
Personalize Customer Experiences
Achieve a single customer view across channels to optimize omni-channel campaigns and customize messaging according to customer lifecycle stages.
Uncover New Revenue Opportunities
Maximize upsell and cross-sell opportunities by utilizing complete and up-to-date customer transaction histories and purchase signals.
Lower Customer Acquisition Costs
Save man-hours on data cleansing and matching, as well as on direct mail packaging and postal costs for duplicate leads, reducing acquisition expenses.
Focus on Strategic Activities
Automate data cleansing and matching routines to save valuable man-hours for core marketing activities such as predictive modeling, marketing stack management, and sponsorships.
Want to know more?
Check out DME resources
Merging Data from Multiple Sources – Challenges and Solutions
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How Customer Data Quality Affects Every Stage of KYC
Last Updated on October 22, 2026 Every KYC check runs on customer records the institution already holds, so screening engines, risk models, and monitoring rules
What Are Entity Graphs and How to Build One You Can Trust
Last Updated on October 8, 2026 An entity graph shows a single match group as a network, with each source record as a node and
How Customer Data Quality Affects Every Stage of KYC
Last Updated on October 22, 2026 Every KYC check runs on customer records the institution already holds, so screening engines, risk models, and monitoring rules
What Are Entity Graphs and How to Build One You Can Trust
Last Updated on October 8, 2026 An entity graph shows a single match group as a network, with each source record as a node and
What’s New in DataMatch Enterprise: REST API, Docker Deployment, and a Rebuilt Matching Engine
Last Updated on September 7, 2026 DataMatch Enterprise just shipped a REST API, a containerized deployment, and a rebuilt matching engine. In internal testing, the
