CRM Deduplication Software
CRM deduplication is a specific area that DQ Global® has been involved in for over 20 years now. As our business roots can be traced back to CRM databases, we have a unique understanding of the problems companies face when using CRM systems and have designed our software to specifically meet these needs in the most efficient and cost effective manner. We understand the challenges of preserving data integrity when cleansing, cross-matching merging/purging and deduplicating CRM systems.
Over 80% of CRM implementations fail due to poor data quality; this can be attributed to a host of reasons, including: Customer details which are incorrect or inconsistent with other data, duplicate records, incomplete or inaccurate addresses, deceased or gone away records, multiple database synchronisation problems.
Your CRM system will only work affectively if the data it contains is accurate and up to date. Whatever system you use, we have the means to keep your data consistent, duplicate free and provide a single customer view that can be trusted.
We offer a Free Trial Download of our CRM Deduplication Software and we are happy to discuss your data quality challenges and offer solutions.
Our Match™ Software is a deduplication and cross matching data quality software tool designed to work directly with your databases or CRM applications. It is fast but simple to operate and can be used in the English, French, German, Italian and Spanish languages. Our Match™ Software uses extensive data transformation and synonym libraries for advanced standardisation and matching.
Cleanse for Infor CRM
Cleanse for Infor CRM this bundle makes advanced data management really simple. Covering accounts, contacts, leads and opportunities, it ensures that records are intelligently merged, re-assigned and correctly synchronised.
Capture for Infor CRM
Capture for Infor CRM if you’ve invested in Infor CRM, you want to get the most out of it. Using DQ Global’s Capture bundle will prevent your users from introducing duplicates into your data by mistake. It uses fuzzy searching before records are saved as well as formatting and standardising data.