Travis Knepper

At Quicken Loans, Travis led a major redesign of the mortgage fulfillment process focused on post-sale logistics. Once mortgages were printed, Travis identified inefficiencies in the pick, pack, and ship process, which was slowing down order fulfillment and increasing errors. He conducted discovery sessions with fulfillment teams and mapped out the entire post-sale workflow. After identifying bottlenecks, Travis introduced process automation and restructured the packaging workflow to increase accuracy and reduce processing time. He worked closely with UPS to implement an optimized shipping strategy that improved delivery times and reduced costs. These changes led to a 76% increase in productivity, faster loan completion, and improved customer satisfaction. The project demonstrated Travis’s ability to optimize fulfillment processes and align operational teams for improved efficiency.

At 7-Eleven, I conceptualized and led the vision and strategy for an AI-powered agent designed to optimize customer support operations. The initiative consolidated support processes across three customer support teams and two CRMs (Zendesk and ServiceNow), streamlining workflows and improving operational efficiency.

To evaluate vendor and technology capabilities, I conducted vendor selection and POC demonstrations, leveraging rapid prototyping to assess alignment with organizational goals and technical feasibility. The solution was designed to automate real-time resolution of late and missing orders while enhancing multilingual support capabilities, achieving a projected ROI of 361%.

This project highlights my ability to design transformative customer support solutions, lead cross-functional teams, and integrate advanced AI technologies to align with strategic business objectives.

At 7-Eleven, Travis led the development of a rules-based engine to resolve late and missing orders, improving fulfillment accuracy and customer satisfaction. He partnered with the data team to analyze customer behavior and order fulfillment patterns using SQL, Mixpanel, and Power BI. Based on this analysis, Travis designed a set of predefined business rules that automated the resolution of common order issues without requiring manual intervention. He worked with engineering and customer support teams to integrate the rules engine into existing workflows, ensuring seamless order resolution. This project reduced customer complaints, lowered cost per ticket, and improved order accuracy by streamlining the fulfillment process. Travis’s ability to translate business challenges into technical solutions resulted in significant operational improvements and enhanced customer experience.

Partnered with the data science team to develop and implement AI-generated product review summaries aimed at improving the decision-making process for online shoppers. Initially deployed on the flagship site, this innovative solution synthesized reviews from multiple online sources into concise, actionable summaries, directly addressing customer needs during the consideration phase.

As the founder and CEO of RideHop, a SaaS startup, I utilized Lean/Agile methodologies to lead the company from ideation to product launch and iterative growth. We developed and launched multiple mobile apps, hardware integrations, and web applications, leading cross-functional teams of developers, designers, and QA throughout the product lifecycle. We achieved profitability in 24 months.

Led the creation of a scalable innovation program that fostered ideation and market validation for the first-mile/last-mile transportation industry. I conducted user research, competitor analysis, and beta testing to ensure product-market fit. Also, I managed cross-functional teams to develop go-to-market strategies and deliver new SaaS solutions. Further, I partnered with the Senior Leadership team to align innovation initiatives with organizational goals. Additionally, I oversaw the successful launch of products that generated measurable ROI, positioning the company as a leader in safety and incident management.

I led a project that significantly reduced chargebacks and refunds by creating real-time transaction screening rules and partnering with Stripe for fraud detection analytics. I then aggregated data from logistics partners and payment processors to create automated API integrations with a chargeback dispute service. This culminated in a streamlined chargeback process and an automated customer appeasement protocol, combining mobile app workflows, back-end verification, and refund processing.

Led a personal safety-related IoT initiative involving IoT-connected safety vests for rail workers. This wearable technology alerted workers of oncoming trains and tracked the wearer's position in GPS-denied areas. The project required the integration of IoT sensors into the safety vests and the development of a mobile app that fed data into and out of the physical products. This experience demonstrates my expertise in designing wearables and IoT apps and my ability to collaborate effectively with hardware engineers.

Led the discovery, validation, and strategic planning phases of an ongoing project aimed at integrating HeyGen's AI Avatar platform with Unreal Media Server and RTMP-based video distribution technologies. I conducted extensive market research to define user needs and validate the business model. I also designed a phased roadmap prioritizing an MVP to test market demand and gather early user feedback, de-risking future automation investments in phase 2. Additionally, I delivered a comprehensive go-to-market strategy emphasizing scalability and iterative development. The solution is poised to address privacy and engagement challenges, enabling innovative use of AI in live streaming for the education and coaching industries.

The RideHop platform displayed context-relevant advertisements to transportation users. These ads were targeted by rider type, time of day, geofence, and transit route. Examples include promoting a discount on coffee to morning commuters or promoting the destinations like the Florida Keys to skiers in Colorado.

Travis served as product manager and project manager for a 0-to-1 initiative to develop a training management system for transit workers, including bus drivers and fleet mechanics. Starting with discovery, he conducted user workshops and stakeholder interviews to define requirements and collaborated with cross-functional teams to create and refine prototypes.

He managed the product roadmap and backlog, translating business needs into actionable technical specifications while prioritizing development efforts. The system streamlined scheduling, tracked certifications and renewals, recommended learning paths, and automated resource reservations such as buses and classrooms.

He also oversaw integrations with learning management systems (LMS) and Microsoft Calendar, enabling seamless content management and coordination for trainers. Additionally, I facilitated business acceptance testing (BAT) to ensure the product met user expectations and aligned with organizational goals.

His leadership and hands-on involvement delivered a scalable, efficient solution that improved training workflows and operational readiness, providing significant value to the client and its users.