Bennett Proegler

Business Intelligence Analyst

OTAVA

08.2023 - Current

Foundational Data Analytics: Promoted from Internal Helpdesk Lead to serve as the 1st Data Analyst in OTAVA's history
Business Process Automation: Collaborated with Sales Operations, Finance, and Deployments teams to design and implement a new system for the lead generation to order deployed and billing, aimed at automating, simplifying, and removing duplicate processes; ultimately reducing monthly invoicing and per order deployment delays by ~50%
Project Management: Spearheaded efforts to migrate and consolidate 2 custom-built customer relationship programs into Salesforce, resulting in automating the entire Sales, Financial, and Deployment aspects of the customer lifecycle
Salesforce Adv Administrator: As owner of our Salesforce platform, led many projects that work to expand our use of the tool, reduce the amount of data pollution by 60%, and enable myself and other teams to use this database tool to gain OTAVA’s clients, the products we sell, and how our clients feel through surveying automations based on client NPS/other ratings
Salesforce CPQ Module Implementation: Assisted with and now leading a Salesforce Configure, Price, Quote contracts implementation; aiming to streamline our contracts and billing management and will function as the source of truth and foundation of data center deployment automation
Directed the implementation of a new Customer Experience surveying tool and its integration with operational data. This data combined with sales and support information allows our product team to make data-driven decisions on products to develop.
Conducted deep-dive analysis, uncovering discrepancies of our support team resources. Restructuring of the support resources has since improved our CSAT by three points and 15% improved SLA adherence.
Cross-Functional Collaboration: Collaborate with cross-functional teams including Product, Business Development, and Data teams to ensure data accuracy and realistic reporting across departments
Utilized SQL and Python to automate data extraction from our operational data store, enabling reporting on information previously segregated in disparate systems.

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