SharkNinja and Questrom Launch AI & Analytics Lab: What Product Teams Can Use Today
November 20, 2025
SharkNinja and Boston University's Questrom Consulting Lab have created the SharkNinja AI & Analytics Lab to turn academic AI and analytics into practical tools for consumer product development. The partnership pairs faculty and graduate talent with SharkNinja's product expertise to speed up data-driven decisions across the product lifecycle.
Why this matters for product development
- Shorten the path from consumer signal to product spec with structured data pipelines, reusable models, and clear decision gates.
- Improve forecast accuracy and inventory planning by linking demand signals to promotions, seasonality, and retail data.
- Cut experiment costs by simulating designs and prioritizing tests before committing to tooling.
- Create repeatable delivery patterns (templates, governance, evaluation) so wins scale across categories.
How the lab operates
The lab runs a faculty-led model with dedicated graduate teams embedded in real business problems. Work moves in sprints with crisp problem framing, measurable KPIs, and go/no-go criteria for handoffs to engineering and operations.
SharkNinja brings context, data, and constraints; Questrom brings analytical design, modeling, and experiment discipline. Leadership on both sides tracks ROI, risk, and adoption so prototypes don't stall.
Early focus areas product teams will care about
- Voice of customer at scale: NLP on reviews, service notes, and social to map needs to specs and catch defects early.
- Predictive quality: anomaly detection on field telemetry and accelerated life test data to flag failure modes pre-launch.
- Demand sensing and supply: probabilistic forecasts tied to promotions, macro signals, and retailer inputs to reduce stockouts and write-offs.
- Design-to-value: feature set optimization using conjoint, price elasticity, and BOM constraints.
- Intelligent experimentation: active learning to prioritize tests, plus A/B infrastructure for firmware and app experiences.
- AI-assisted concept exploration: create briefs, variant lists, and testable options that feed industrial design and engineering.
What to copy into your roadmap
- Define data contracts for product telemetry, reviews, and warranty data so models stay stable release over release.
- Set a decision cadence: monthly portfolio reviews where model outputs drive cut/continue choices with clear owners.
- Adopt model governance: versioning, bias checks, and human-in-the-loop signoff for any consumer-facing automation.
- Create shared components: feature stores, prompt libraries, and evaluation suites to cut one-off builds.
- Upskill PMs and engineers on practical AI so problem framing and acceptance criteria improve each sprint.
Leadership perspective
According to CEO Mark Barrocas, the initiative connects academic insight with real business challenges to make smarter decisions and move ideas into action faster. Professor Peter Howard underscores the hands-on setting for students to deliver measurable value, and Dean Susan Fournier highlights the focus on experiential learning that produces day-one-ready talent.
About the partners
SharkNinja is a global product design and technology company with highly rated household solutions across the Shark and Ninja brands. Headquartered in Needham, Massachusetts, the company employs more than 3,600 people and sells through major retailers, online and offline, around the world.
The Center for Action Learning at Boston University's Questrom School of Business equips students with real-world skills, professional networks, and career readiness through hands-on projects. The Questrom Consulting Lab fields dedicated student teams, led by faculty advisors, to help solve strategic business problems.
Questrom Experiential Learning (QXL) moves beyond the classroom with tracks such as QXLconsult, QXLinvest, QXLlaunch, and QXLexplore. Each experience builds practical problem-solving and confidence by working on live challenges.
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