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Master’s in Sponsorship Analytics & Activation Engineering

Online master's programme of 1,900 hours in sponsorship analytics and activation engineering. 12 modules covering the sponsorship market, brand strategy, media exposure measurement, audience research, fan data analytics, activation, attribution and ROI, rights valuation, contracts, digital content and reporting, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Understand the sports sponsorship market and strategy.

02

Measure brand exposure in traditional and digital media.

03

Design audience research and brand tracking studies.

04

Analyse fan data for segmentation and activation.

05

Calculate return on investment using attribution models.

06

Value sponsorship rights with recognised methods.

07

Produce reports and dashboards for sponsors.

Profile

Who it's for

  • Sports sponsorship analysts measuring exposure and return for brands or rights holders.
  • Brand activation managers planning experiences, content and hospitality.
  • Sponsorship account managers looking after sponsor portfolios.
  • Sports marketing consultants advising brands, teams and series.
  • Fan data analysts working with CRM, ticketing and digital data.
  • Rights valuation managers setting prices and negotiating renewals.
  • Engineering or science graduates seeking to enter motorsport.
Standards & tools

What you'll work with

  • ICC Advertising and Marketing Communications Code (self-regulation of marketing)
  • ISO 10668:2010 (monetary brand valuation)
  • ISO 20671-1:2021 (brand evaluation)
  • Regulation (EU) 2016/679 (General Data Protection Regulation)
  • Spanish General Advertising Act 34/1988
  • Royal Decree 958/2020 (commercial communications for gambling)
  • Spanish General Audiovisual Communication Act 13/2022
  • Blinkfire Analytics
  • Nielsen Sports
  • Tableau
  • Python with scikit-learn
  • Qualtrics
Syllabus

12 modules · 1900 h

  1. 1.1Evolution of sponsorship in sport
  2. 1.2Sponsorship versus advertising
  3. 1.3Categories of sponsorship rights
  4. 1.4Sponsorship in motorsport
  5. 1.5Global investment by sector
  6. 1.6Agencies and rights holders
  7. 1.7Life cycle of a deal
  8. 1.8Ethical framework and the ICC Code
  9. 1.9Market trends
  10. 1.10Case study: a team's sponsor portfolio
  1. 2.1Awareness and consideration objectives
  2. 2.2Image and attribute transfer
  3. 2.3Fit between brand and property
  4. 2.4Sponsorship architecture
  5. 2.5Selecting properties
  6. 2.6B2B sponsorship and hospitality
  7. 2.7Purpose-led sponsorship
  8. 2.8Exclusivities and categories
  9. 2.9The sponsor brief
  10. 2.10Workshop: brief and property selection
  1. 3.1Measuring television visibility
  2. 3.2Computer vision for logo detection
  3. 3.3Exposure quality and adjustment factors
  4. 3.4Media equivalent value
  5. 3.5Social media exposure
  6. 3.6Owned and earned media
  7. 3.7Audience panels
  8. 3.8Limitations of media equivalent value
  9. 3.9Auditing measurement providers
  10. 3.10Lab: automatic logo detection in video
  1. 4.1Brand tracking surveys
  2. 4.2Questionnaire design
  3. 4.3Control and exposed groups
  4. 4.4Unaided and aided recall
  5. 4.5Fan segmentation
  6. 4.6Sentiment analysis
  7. 4.7Qualitative research with fans
  8. 4.8Online panels
  9. 4.9Representativeness and bias
  10. 4.10Practical exercise: sponsor recall survey
  1. 5.1Customer data platforms
  2. 5.2Profile identification and unification
  3. 5.3Ticketing and commerce data
  4. 5.4Digital behaviour analysis
  5. 5.5Propensity models
  6. 5.6Fan lifetime value
  7. 5.7Advanced value-based segmentation
  8. 5.8Data protection and consent
  9. 5.9Sharing data with sponsors
  10. 5.10Lab: fan segmentation with Python
  1. 6.1Activation plans
  2. 6.2On-site event experiences
  3. 6.3Sponsored content production
  4. 6.4Campaigns with athletes
  5. 6.5Promotions and competitions
  6. 6.6Digital and social activation
  7. 6.7Corporate hospitality programmes
  8. 6.8Point-of-sale activation
  9. 6.9Activation budget
  10. 6.10Workshop: activation plan for a Grand Prix
  1. 7.1ROI and ROO in sponsorship
  2. 7.2Multi-channel attribution models
  3. 7.3Marketing mix models
  4. 7.4Experiments and incrementality testing
  5. 7.5Estimating attributable sales
  6. 7.6B2B lead generation
  7. 7.7Hospitality indicators
  8. 7.8Reporting to the sponsor
  9. 7.9Return benchmarks
  10. 7.10Practical exercise: marketing mix model with sponsorship data
  1. 8.1Property valuation methods
  2. 8.2Cost, market and income valuation
  3. 8.3ISO 10668 and ISO 20671 standards
  4. 8.4Asset inventory
  5. 8.5Package pricing
  6. 8.6Rate cards
  7. 8.7Data-driven negotiation
  8. 8.8Renewals and escalators
  9. 8.9Value of naming rights
  10. 8.10Case study: valuing a title sponsorship
  1. 9.1Structure of a sponsorship contract
  2. 9.2Rights and obligations
  3. 9.3Performance clauses
  4. 9.4Preventing ambush marketing
  5. 9.5Brand protection
  6. 9.6Gambling and alcohol advertising
  7. 9.7Broadcast restrictions
  8. 9.8Reputation and morals clauses
  9. 9.9Early termination of the contract
  10. 9.10Practical exercise: review of a sponsorship contract
  1. 10.1Sponsored content strategy
  2. 10.2Creators and influence
  3. 10.3Short-form video platforms
  4. 10.4Live streaming
  5. 10.5Esports and virtual sponsorship
  6. 10.6Engagement metrics
  7. 10.7Creative testing of assets
  8. 10.8Programmatic advertising with sports data
  9. 10.9Season editorial calendar
  10. 10.10Case study: social campaign over a season
  1. 11.1Key sponsorship indicators
  2. 11.2Sponsorship data architecture
  3. 11.3Integrating sources
  4. 11.4Visualisation for executives
  5. 11.5Preparing post-event reports
  6. 11.6Season reports
  7. 11.7Report automation
  8. 11.8Storytelling with results
  9. 11.9Improvement recommendations
  10. 11.10Workshop: sponsorship dashboard in Power BI
  1. 12.1Selecting the property and brand
  2. 12.2Defining objectives
  3. 12.3Measurement design
  4. 12.4Data collection
  5. 12.5Exposure and audience analysis
  6. 12.6Calculating the return
  7. 12.7Proposed activation plan
  8. 12.8Renewal recommendations
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

The programme is delivered 100% online on the SEIUM campus, with downloadable materials, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so you can combine it with your job.

Each module combines theory, guided reading of the original standards and applied exercises. The working software is Blinkfire Analytics, Nielsen Sports, Tableau, Python with scikit-learn and Qualtrics, in free, academic or evaluation versions. Exercises are based on real procedures: measuring brand exposure in a TV broadcast, calculating the return of a season-long sponsorship and designing an on-site activation plan. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: the ICC Advertising and Marketing Communications Code, ISO 10668:2010, ISO 20671-1:2021, Regulation (EU) 2016/679 (GDPR), Spanish General Advertising Act 34/1988, Royal Decree 958/2020 and Spanish General Audiovisual Communication Act 13/2022.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the ICC Advertising and Marketing Communications Code, ISO 10668 and ISO 20671-1 applied to real cases, not as a theoretical annex.
Industry software:Blinkfire Analytics, Nielsen Sports, Tableau, Python with scikit-learn and Qualtrics, in free, academic or evaluation versions.
Master's Thesis with defence:a full evaluation of a real sponsorship, with measurement design, exposure and audience analysis, return calculation and activation plan, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Automatic logo detection
Measure brand exposure in broadcast video using computer vision.
Sponsor recall survey
Design and analyse a sponsor recall survey with control and exposed groups.
Marketing mix model
Build a marketing mix model to estimate the return of a sponsorship.
Title sponsorship valuation
Value a title sponsorship using cost, market and income methods.
Master's Thesis
A full evaluation of a real sponsorship, with return calculation, activation plan and renewal recommendations, defended before a panel.
Career opportunities

Where this takes you

Sports sponsorship analystBrand activation managerSponsorship account managerSports marketing consultantFan data analystRights valuation manager
Admissions & scholarships

Requirements

  • A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • An internet connection and a computer capable of running the programme's software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with Blinkfire Analytics, Nielsen Sports, Tableau, Python with scikit-learn and Qualtrics, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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