Case Study: Lamb Financial Group achieves faster, more accurate data cleansing and revenue growth with Data Ladder

Data cleansing tools drives revenue and saves time

Lamb Financial Group, a fast-growing New York–based insurance broker serving non-profits and social service organizations, faced challenges consolidating data from multiple sources where slight differences in key fields required extensive manual scrubbing and strict standardization. To improve accuracy and speed when importing data into their CRM, they turned to Data Ladder and its DataMatch Enterprise™ solution.

Data Ladder implemented DataMatch Enterprise™ with the Wordsmith™ standardization feature to cleanse, standardize, and link records across datasets, delivering about a 97% record linkage rate versus a ~90% industry average and producing 5–12% more matches than leading competitors in studies. The solution reduced manual data-scrubbing by several hours each week, streamlined CRM imports, and enabled Lamb Financial Group to work leaner and more efficiently.

Lamb Financial Group

Daniel Heller

Chief Financial Officer