Industrial Deafness Hearing

Industrial Deafness Hearing, encountered challenges with HubSpot data quality, including duplicate records, incomplete information, and outdated entries. These issues led to inefficiencies in sales and marketing operations, affecting customer engagement and reporting accuracy.

Solution Approach

A detailed audit of the HubSpot database identified duplication patterns, inconsistent data structures, and missing fields. A data enrichment plan was developed to enhance data accuracy and completeness. Data cleaning and deduplication processes were executed using Python scripts and Google Spreadsheet functions to detect and clean duplicate records. Data formats were standardized, while outdated and irrelevant records were removed to improve CRM efficiency.

The prepared dataset was formatted and validated before import to minimize errors. Data fields were mapped correctly to align with HubSpot’s CRM structure, and HubSpot’s import tools were utilized to merge and update existing records without discrepancies.

Post-import, a quality check was performed to ensure data integrity and accuracy. Workflows were implemented to maintain data hygiene, and sales and marketing teams were provided with solution guidelines for CRM data management.

Results

• Reduction in Data Duplication – A cleaner dataset enhanced efficiency for sales and marketing teams.
• Improvement in Data Completeness – Standardized data formatting improved usability.
• Error-Free HubSpot Import – A seamless transition minimized previous import errors.
• Enhanced Operational Efficiency – Improved segmentation, lead tracking, and customer engagement.

Conclusion

By applying structured data analysis, cleaning, and CRM import processes, Industrial Deafness Hearing significantly improved the quality and usability of their HubSpot database. The elimination of redundant records and the establishment of data hygiene practices optimized internal workflows, resulting in improved efficiency across sales and marketing teams.