Data quality for sales and marketing

Trusted By







Trusted By







Did you know?
How bad data affects sales and marketing?
CRM data decay causes significant loss in revenues

High bounce rates
Increased email bounces due to email typos, punctuation errors or data decay, causing loss in domain reputation

Missed or Returned Mails
Unverified or missing address details such as street name and ZIP+4 can lead to failed deliveries and returned mails.

Poor Employee Productivity
Sales and management teams waste nearly 50% of their time handling basic data quality management tasks.

Lack of personalization
Inaccurate and incomplete information can restrict the level of personalization needed to tailor campaigns according 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Potential sales losses due to contact details such as email and phone data becoming quickly out-of-date and obsolete.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

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 names of accounts, contact names, and addresses by adding or removing suffixes, initials, or abbreviations to achieve data consistency.
Validate Data in Real-time
Leverage real-time API flows to validate data coming directly from input forms to your CRM database using specific rules.
Personalize Customer Experiences
Have a single customer view across multiple marketing channels to leverage omni-channel campaigns and tailor messaging specific to customers’ lifecycle stages.
Uncover New Revenue Opportunities
Make use of complete and up-to-date customer transaction history and purchase signals to capitalize on up-sell and cross-sell opportunities.
Lower Customer Acquisition Costs
Save man-hours cleansing and matching data and on direct mail packaging and postal costs targeting duplicate leads to lower acquisition costs.
Focus on Strategic Activities
Automate cleansing and matching routines to save crucial man-hours for core marketing activities such as predictive modelling, marketing stack or sponsorships.
Want to know more?
Check out DME resources

Merging Data from Multiple Sources – Challenges and Solutions
Oops! We could not locate your form.

The Truth About Data as a Service (DaaS): Why It All Breaks Without Data Matching
Everyone’s Talking About DaaS, Few Are Ready for It The concept of Data as a Service (DaaS) is having its moment. On paper, it’s easy

Big Data Analytics Is Booming – But Is Your Data Ready for It?
Amazon generates 35% of its revenue from data-powered recommendations. Netflix enjoys an 89% retention rate by personalizing every experience using viewer behavior, preferences, and interaction

The Truth About Data as a Service (DaaS): Why It All Breaks Without Data Matching
Everyone’s Talking About DaaS, Few Are Ready for It The concept of Data as a Service (DaaS) is having its moment. On paper, it’s easy

Big Data Analytics Is Booming – But Is Your Data Ready for It?
Amazon generates 35% of its revenue from data-powered recommendations. Netflix enjoys an 89% retention rate by personalizing every experience using viewer behavior, preferences, and interaction

Data Ethics in the Age of AI: Why Responsible Matching Matters More Than Ever
When AI systems deliver inaccurate or inequitable results, many people immediately assume that something went wrong in the algorithms. Rarely do we look upstream –