About Todd Hoeft
I am a Product Data Analyst, Product Manager, and Software Engineer with extensive experience transforming customer, operational, and product data into actionable business insights across SaaS, ERP, fintech, healthcare, mining, telecommunications, insurance, and higher education software organizations.
My career combines product management, software engineering, business intelligence, analytics, and customer engagement. This unique blend enables me to bridge business objectives, customer needs, and technical implementation while using data to drive strategic decision-making.
Throughout my career, I have led product strategy, customer analytics, KPI reporting, dashboard development, SQL analysis, roadmap prioritization, customer advisory programs, survey analytics, and executive reporting. I have supported software platforms serving more than 100,000 users across multiple industries while delivering measurable improvements in customer satisfaction, operational efficiency, and product adoption.
Key accomplishments
- Increased customer satisfaction by 18% through customer feedback programs, Customer Advisory Board leadership, product analytics, and roadmap prioritization.
- Improved operational efficiency by 20% through process optimization, reporting enhancements, and workflow improvements.
- Delivered 105 product enhancements and new capabilities through customer analytics, feature adoption analysis, and strategic product planning.
- Prioritized and delivered 12 APIs and multiple automation solutions using customer demand analysis, business value assessments, and operational metrics.
- Increased customer satisfaction at SubItUp through survey analysis, customer feedback programs, and data-driven product improvements.
- Reduced operational effort by 15% through workflow optimization, incident management improvements, and process redesign initiatives.
My technical expertise includes Microsoft Stack, SQL Server, Power BI, Excel, SSRS, AWS, Azure, Power Platform, Power Automate, Power Apps, Logic Apps, ETL, REST APIs, Jira, Confluence, Google Analytics, and Agile product development methodologies.
I recently completed Applied Statistics for Data Analytics, expanding my expertise in statistical inference, confidence intervals, hypothesis testing, probability distributions, sampling methodologies, simulation techniques, and exploratory data analysis.
Areas of interest include Product Analytics, Product Data Analysis, Business Intelligence, Product Strategy, Data Visualization, SQL data extraction, Customer Insights, and Analytics Leadership.