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Diploma in Product KPIs, Pricing and A/B Testing at ADAS

The Diploma in Product KPIs, Pricing, and A/B Testing in ADAS focuses on optimizing the performance of Advanced Driver-Assistance Systems (ADAS) products through the analysis of Key Performance Indicators (KPIs). It explores value- and competitiveness-based pricing strategies, as well as the design and implementation of A/B tests to evaluate the impact of modifications to product features and the User Experience (UX). The course covers Data Science and Business Intelligence techniques for interpreting results and making strategic decisions, considering the usability, security, and effectiveness of ADAS systems. The course provides practical skills in using data analysis tools and platforms for conducting A/B tests. The focus is on applying agile methodologies and continuous product optimization, covering the entire development lifecycle, from design to commercialization. Participants are prepared for roles such as Product Manager, Data Analyst, Pricing Specialist, and UX Researcher, boosting competitiveness in the automotive sector.

Duration6–8 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Strategic Mastery of KPIs, Pricing, and A/B Testing for Success in ADAS

02

ADAS Optimization: KPIs, Pricing Strategies, and A/B Testing for Product Growth [The following appears to be unrelated and possibly machine-translated gibberish:] "ADAS Optimization: KPIs, Pricing Strategies, and A/B Testing for Product Growth" "ADAS Optimization: KPIs, Pricing Strategies, and A/B Testing" "A ...

03

Comprehensive user-oriented design and validation (from modeling to manufacturing)

04

Mastery of Product KPIs, Pricing, and A/B Experiments for Optimization in ADAS

05

KPIs, Pricing, and A/B Testing: A Practical Guide for ADAS and Maximizing Product Value

06

Advanced Strategies in KPIs, Pricing, and A/B Testing for Innovation and Profitability in ADAS

07

In-depth Analysis of KPIs, Pricing, and A/B Testing in ADAS for Data-Driven Decision Making

08

Comprehensive Mastery of KPIs, Pricing, and A/B Testing in ADAS: A Guide to Product Success [The following appears to be unrelated and possibly machine-translated gibberish: " "]

Profile

Who it's for

  • Professionals and graduates in areas such as Marketing, Product Management, Pricing, Data Science, Business Analytics, E-commerce, and related fields.
  • Profiles seeking to specialize in performance measurement (KPIs), pricing strategies, and optimization through A/B testing in the context of Digital Products and Software as a Service (SaaS).
  • Data analysts, product managers, marketing managers, and professionals involved in data-driven decision-making who wish to improve profitability and user experience.
  • Entrepreneurs and startup founders, especially those in the digital sector, who need to understand and apply advanced methodologies for the growth and optimization of their businesses.
    • products.
Standards & tools

What you'll work with

  • Standards-driven curriculum: you will work with CS-27/CS-29, DO-160, DO-178C/DO-254, ARP4754A/ARP4761, ADS-33E-PRF from the first module.
  • Accreditable laboratories (EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibrations/acoustics.
  • Evidence-oriented TFM: safety case, test plan, compliance dossierand operational limits.
  • Mentored by industry: teachers with experience in rotorcraft, tiltrotor, eVTOL/UAM and flight test.
  • Flexible modality (hybrid/online), international cohorts and support from SEIUM Career Services.
  • Ethics and security: safety-by-design approach, cyber-OT, DIH and compliance as pillars.
Syllabus

10 modules

  1. 1.1Definition and Relevance of ADAS: Current Landscape and Future Outlook.
  2. 1.2Introduction to KPIs: Key Metrics for Success in ADAS.
  3. 1.3Pricing Principles: Pricing Strategies in the ADAS Market.
  4. 1.4Fundamentals of A/B Testing: Designing and Running Experiments.
  5. 1.5Integrating KPIs, Pricing, and A/B Testing: An Overview.
  6. 1.6Goal Setting: Defining Clear and Measurable Goals.
  7. 1.7Data Collection and Analysis: Essential Tools and Techniques.
  8. 1.8Interpreting Results: Drawing Meaningful Conclusions.
  9. 1.9Introduction to ADAS Tools and Platforms.
  10. 1.10Preparing for Advanced Learning: Next Steps.
  1. 2.2Defining and Selecting Key KPIs for ADAS
  2. 2.2Pricing Strategies: Models and Optimization for ADAS
  3. 3.3Designing and Executing A/B Experiments: Fundamentals
  4. 4.4Analyzing A/B Testing Results and Decision Making
  5. 5.5Product-Specific KPIs and Their Impact on ADAS
  6. 6.6Value-Based Pricing and Segmentation Strategies
  7. 7.7Implementing A/B Testing for Continuous Improvement
  8. 8.8Case Study: Optimizing ADAS Through KPIs, Pricing, and A/B Testing
  9. 9.9Tools and Platforms for Analysis and Experimentation
  10. 20.20The Future of ADAS: Trends and Adapting to Market Changes
  1. 3.3Introduction to KPIs in ADAS: Selection and Relevance
  2. 3.2Defining Pricing Strategies in ADAS: Models and Market Analysis
  3. 3.3Fundamentals of A/B Testing: Designing Experiments for ADAS
  4. 3.4Product KPIs: Performance Monitoring and Key Metrics
  5. 3.5Pricing Strategies: Implementation and Optimization
  6. 3.6A/B Testing: Results Analysis and Decision Making
  7. 3.7KPIs in ADAS: Advanced Analysis and Segmentation
  8. 3.8Pricing: Advanced Strategies for Value Maximization
  9. 3.9A/B Testing: Scalability and Continuous Optimization
  10. 3.30Case Study: Implementing KPIs, Pricing, and A/B Testing in ADAS
  11. 3.4
  1. 4.4Key KPIs in ADAS: Identification and Measurement
  2. 4.2Pricing Strategies for ADAS: Models and Applications
  3. 4.3Introduction to A/B Testing in ADAS: Fundamentals and Methodology
  4. 4.4Designing A/B Experiments for ADAS: Planning and Execution
  5. 4.5Analyzing Results in A/B Testing for ADAS: Interpretation and Conclusions
  6. 4.6KPIs and Pricing: Alignment for Value Maximization
  7. 4.7KPIs and A/B Testing: Integration for Continuous Improvement
  8. 4.8Pricing and A/B Testing: Optimizing Profitability
  9. 4.9Implementing Data-Driven Strategies in ADAS
  10. 4.40Case Study: Practical Application of KPIs, Pricing, and A/B Testing in ADAS
  1. 5.5Introduction to KPIs in ADAS: Definition and Relevance
  2. 5.5Selection and Prioritization of Key KPIs for ADAS
  3. 5.3Pricing Strategies for ADAS Products: Models and Applications
  4. 5.4A/B Testing for ADAS: Fundamentals and Methodology
  5. 5.5A/B Experiment Design: Variables, Objectives, and Metrics
  6. 5.6Analysis of A/B Testing Results and Decision Making
  7. 5.7Continuous Optimization of KPIs and Pricing Strategies
  8. 5.8Integration of KPIs, Pricing, and A/B Testing into the Product Lifecycle
  9. 5.9Case Studies: Practical Real-World Applications of ADAS
  10. 5.50Tools and Technologies for Analysis and Optimization in ADAS
  1. 6.6Selection and Analysis of Key KPIs for ADAS
  2. 6.2Pricing Strategies for ADAS: Models and Optimization
  3. 6.3Design and Execution of A/B Experiments in ADAS
  4. 6.4Results Analysis and Data-Driven Decision Making
  5. 6.5ADAS Functionality-Specific KPIs: Diagnosis and Improvement
  6. 6.6Advanced A/B Testing: Segmentation and Personalization
  7. 6.7Evaluating the Impact of Pricing on ADAS Adoption
  8. 6.8Iteration Strategies and Continuous Optimization
  9. 6.9Profitability and Return on Investment (ROI) Analysis in ADAS
  10. 6.60Scalability and Sustainability of the ADAS Product
  1. 7.7Introduction to KPIs in ADAS: Definition and Relevance
  2. 7.2Selecting Key KPIs: Acquisition, Activation, Retention, Revenue, and Referral Metrics
  3. 7.3Pricing Strategies in ADAS: Pricing Models and Willingness to Pay Analysis
  4. 7.4A/B Testing Fundamentals: Experiment Design and Results Analysis
  5. 7.7Product KPIs: Metrics Specific to ADAS Functionality and Performance
  6. 7.6Pricing and Profitability: Price Optimization to Maximize Product Value
  7. 7.7A/B Testing on Key ADAS Functions: Continuous Improvement and Hypothesis Validation
  8. 7.8Data Analysis and Decision Making: Interpreting A/B Testing and KPI Results
  9. 7.9Maximizing Product Value: Integrated Strategies for KPIs, Pricing, and A/B Testing
  10. 7.70Case Studies: Practical Application in Real-World ADAS Scenarios
  1. 8.8Selection and Analysis of Key KPIs in ADAS
  2. 8.8Pricing Strategies for ADAS Products
  3. 8.3Design and Execution of Effective A/B Experiments in ADAS
  4. 8.4Analysis of A/B Testing Results and Decision Making
  5. 8.5Optimization of KPIs for Continuous Improvement in ADAS
  6. 8.6Modeling and Simulation of Price Impact in ADAS
  7. 8.7Tools and Platforms for A/B Testing in ADAS
  8. 8.8Case Studies: Implementation of KPIs, Pricing, and A/B Testing in ADAS
  9. 8.8Scalability and Growth Strategies Through Data in ADAS
  10. 8.80Future of ADAS: Trends in KPIs, Pricing, and A/B Testing
  1. 9.9Importance of KPIs in ADAS: Definition and Relevance
  2. 9.9Introduction to Pricing in ADAS: Strategies and Models
  3. 9.3Fundamentals of A/B Testing: Concepts and Methodology
  4. 9.4Identifying Key KPIs: Selection and Prioritization
  5. 9.5Initial Pricing Structure: Market and Competitive Analysis
  6. 9.6A/B Experiment Design: Objectives and Variables
  7. 9.7Data Collection and Analysis: Tools and Metrics
  8. 9.8Interpreting Results: Data-Driven Decisions
  9. 9.9Iteration Planning: Next Steps and Improvements
  10. 9.90Ethical and Legal Considerations: Privacy and Security
  1. 1.1Defining and Selecting Key KPIs for ADAS
  2. 1.2Pricing Strategies: Competitive Analysis and Pricing Models
  3. 1.3Introduction to A/B Testing: Designing and Executing Experiments
  4. 1.4Interpreting Results and Data-Driven Decision Making
  5. 1.5Case Studies: Practical Application in Different ADAS Scenarios
  6. 2.1Identifying Specific KPIs for ADAS Growth
  7. 2.2Analyzing Advanced Pricing Strategies and Their Impact
  8. 2.3Designing A/B Experiments: Tools and Methodologies
  9. 2.4Data Analysis: Product Segmentation and Personalization
  10. 2.5Iteration and Continuous Improvement Strategies Based on Results
  11. 3.1Product KPIs: Monitoring and Evaluating Performance
  12. 3.2Dynamic Pricing Models and Revenue Optimization
  13. 3.3A/B Testing: Implementation and Analysis of Significant Results
  14. 3.4Evaluating the Impact on User Experience and Retention
  15. 3.5Product Adaptation and Scalability Strategies
  16. 4.1Product KPIs: Key Metrics and Their Relationship to Value
  17. 4.2Pricing Strategies: Elasticity Analysis and Perceived Value
  18. 4.3A/B Experiments: Methodology and Impact Assessment in UX
  19. 4.4Continuous Optimization: Data-Driven Adaptation
  20. 4.5Tools and Platforms for Effective Implementation
  21. 5.1KPI Guide: Selection, Implementation, and Monitoring
  22. 5.2Pricing: Pricing Models and Monetization Strategies
  23. 5.3A/B Testing: Design, Execution, and Analysis to Maximize Value
  24. 5.4Evaluating Profitability and Return on Investment
  25. 5.5Practical Implementation and Success Stories in ADAS
  26. 6.1Advanced KPIs: Cohort and Segmentation Analysis
  27. 6.2Pricing Strategies: Optimization and Advanced Personalization
  28. 6.3A/B Testing: Designing Experiments for Innovation
  29. 6.4Results Analysis: Strategies for Scalability
  30. 6.5Monetization Strategies for Sustainable Growth
  31. 7.1In-Depth KPI Analysis: Acquisition and Retention Metrics
  32. 7.2Pricing Strategies: Competitive Analysis and Positioning
  33. 7.3A/B Testing: Statistical Analysis and Significance
  34. 7.4Decision Making: Integrating Data into Strategy
  35. 7.5Predictive Modeling for Continuous Improvement
  36. 8.1KPIs: Dashboard Design and Real-Time Monitoring
  37. 8.2Pricing: Value-Based Pricing Strategies
  38. 8.3A/B Experimentation: Advanced Methodology and Tools
  39. 8.4Comprehensive Data Analysis: Key Insights and Conclusions
  40. 8.5Product Implementation and Optimization Strategies
Methodology, software & labs

How you'll learn

  • Hands-on methodology: test-before-you-trust, design reviews, failure analysis, compliance evidence.
  • Software (depending on licenses/partners): MATLAB/Simulink, Python (NumPy/SciPy), OpenVSP, SU2/OpenFOAM, Nastran/Abaqus, AMESim/Modelica, acoustics tools, planning toolchains DO-178C.
  • SEIUM Laboratories: scale rotor bench, vibrations/acoustics, EMC/Lightning pre-compliance, HIL/SIL for AFCS, data acquisition with strain gauging.
  • Standards and compliance: EN 9100, 17025, ISO 27001, GDPR.
Accreditable laboratories(EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibrations/acoustics.
Evidence-oriented Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry Mentored:teachers with experience in training, , eVTOL/UAM and flight test.
Flexible modality(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, cyber-OT, DIH and compliance as pillars.
Career opportunities

Where this takes you

Product Analyst (KPIs, A/B Testing)Product Manager/Analyst (KPIs, Pricing, A/B Testing)Product Manager/Analyst (KPIs, Pricing, A/B Testing)Product Manager/Analyst (KPIs, Pricing, A/B Testing, ADAS)Product Manager/Analyst (KPIs, Pricing, A/B Testing, ADAS)Product Manager/Analyst (KPIs, Pricing, A/B Testing, ADAS)
Admissions & scholarships

Requirements

  • Profile: Background in Computer Engineering, Mathematics, Statistics, or related fields; practical experience in NLP and valued information retrieval systems.
  • Documentation: Updated CV, academic transcript, SOP/statement of purpose, project examples or code (optional).
  • Process: Application → Technical evaluation of profile and experience → Technical interview → Review of case studies → Final decision → Enrollment.
  • Fees:
    • Single payment: 10% discount.
    • Payment in 3 installments: No fees; 30% upon registration + 2 equal monthly payments of the remaining 35%. Monthly payment: available with a 7% commission on the total; annual review. Scholarships: based on academic merit, financial need, and promoting inclusion; agreements with companies in the sector for partial or full scholarships. See "Calendar & Calls for Applications," "Scholarships & Grants," and "Fees & Financing" in the SEIUM mega-menu.

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FAQ

Frequently asked questions

Yes, we have international certification

Yes: experimental models, real data, applied simulations, professional environments, real case studies.

It is not mandatory. We offer leveling tracks and tutoring.

Completely. It covers e-propulsion, integration, and emerging regulations (SC-VTOL).

Recommended. There are also internal challenges and consortiums.

Yes. Online/hybrid modality with planned labs and visa support (see “Visa & Residence”).

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