Radar Chart Examples & Use Cases

Example 1: Smartphone Comparison

Industry: Technology / Consumer Electronics

Use Case: Comparing three flagship smartphones across key features to help consumers make informed purchasing decisions.

Variables measured (all normalized 0-10):

• Camera Quality: Based on DxOMark scores and professional reviews
• Battery Life: Normalized from actual battery capacity and screen-on time tests
• Performance: Benchmark scores from Geekbench and AnTuTu
• Display Quality: Resolution, brightness, color accuracy, refresh rate
• Build Quality: Materials, durability testing, water resistance rating
• Value for Money: Price normalized inversely (lower price = higher score)

Key insights revealed:

• Phone A excels in camera and display but is expensive, creating a premium profile
• Phone B offers the best balance across all categories with strong value
• Phone C has outstanding battery life but lags in performance
• No single phone dominates all categories, helping buyers identify trade-offs

Example 2: Software Platform Evaluation

Industry: Enterprise Software / SaaS

Use Case: IT department evaluating three project management platforms for company-wide adoption.

Variables measured (all normalized 0-10):

• Features & Functionality: Task management, reporting, integrations, automation
• Ease of Use: User interface intuitiveness, learning curve, mobile experience
• Collaboration Tools: Real-time editing, comments, file sharing, communication
• Integration Ecosystem: Number and quality of third-party integrations
• Customization: Workflow templates, custom fields, branding options
• Value for Money: Price per user normalized against feature set
• Support Quality: Response times, documentation quality, training resources

Key insights revealed:

• Platform A has the most features but requires significant training investment
• Platform B excels in ease of use and support, ideal for non-technical teams
• Platform C offers the best integration ecosystem for companies with complex tech stacks
• All three platforms score similarly on collaboration, making other factors decisive

Example 3: Competitive Brand Positioning

Industry: Market Research / Brand Strategy

Use Case: Marketing team analyzing how consumers perceive their brand versus two main competitors.

Variables measured (survey data, 0-10 scale):

• Quality Perception: Average rating of product/service quality
• Innovation: "How innovative is this brand?" rating
• Trustworthiness: Consumer trust and reliability scores
• Customer Service: Support experience ratings
• Value for Money: Price-to-quality perception
• Brand Awareness: Unaided brand recall percentage, normalized

Key insights revealed:

• Your Brand leads in innovation but lags in awareness and trust
• Competitor A dominates awareness and trust but is perceived as less innovative
• Competitor B excels in value perception but trails in quality ratings
• All brands score similarly on customer service, suggesting industry parity

Example 4: Employee Skills Assessment

Industry: Human Resources / Professional Development

Use Case: Manager conducting performance review and identifying development opportunities for a senior developer.

Variables measured (manager assessment, 0-10 scale):

• Technical Expertise: Coding skills, system design, technology breadth
• Problem Solving: Debugging, algorithm design, troubleshooting ability
• Communication: Written docs, presentations, explaining complex concepts
• Collaboration: Code reviews, pair programming, team coordination
• Leadership: Mentoring, decision-making, project ownership
• Initiative: Proactive improvements, learning new skills, process optimization

Two datasets compared:

• Current performance (actual assessment)
• Senior role expectations (target profile)

Key insights revealed:

• Technical skills and problem-solving already exceed senior-level expectations
• Leadership and communication scores lag behind requirements for promotion
• Clear development path: focus training on soft skills rather than technical depth
• Visual representation helps employee understand gaps objectively

Example 5: University Program Comparison

Industry: Higher Education

Use Case: Graduate student comparing three MBA programs to make enrollment decision.

Variables measured (0-10 scale):

• Academic Reputation: Rankings, faculty credentials, research output
• Career Outcomes: Post-graduation salary, placement rates, alumni network
• Specialization Strength: Quality of desired concentration (Finance)
• Location Appeal: City attractiveness, proximity to industry hubs, lifestyle
• Affordability: Total cost of attendance normalized inversely
• Program Flexibility: Part-time options, online components, pace choices

Key insights revealed:

• Program A leads in reputation and career outcomes but is most expensive and inflexible
• Program B offers best flexibility and affordability with solid but not elite outcomes
• Program C has strongest finance specialization with moderate scores across other areas
• Location preferences create different trade-offs for each program

Example 6: Soccer Player Scouting

Industry: Professional Sports / Soccer

Use Case: Scout evaluating three potential striker signings for transfer.

Variables measured (statistical analysis, 0-10 scale):

• Finishing: Goals per shot, conversion rate in scoring positions
• Movement: Runs into box, positioning, off-ball intelligence
• Passing: Assist rate, link-up play, key passes per game
• Physical Attributes: Speed, strength, stamina, aerial ability
• Pressing & Work Rate: Defensive actions, distance covered
• Consistency: Performance variation across season, big game reliability

Key insights revealed:

• Player A is elite finisher but contributes less to overall play
• Player B excels in movement and link-up, fitting team's possession style
• Player C offers well-rounded profile with high work rate for pressing system
• All three players have different strengths matching different tactical approaches

Example 7: Patient Wellness Assessment

Industry: Healthcare / Preventive Medicine

Use Case: Doctor tracking patient's overall health metrics over time during wellness program.

Variables measured (clinical data, 0-10 normalized):

• Cardiovascular Health: Blood pressure, resting heart rate, cholesterol levels
• Metabolic Health: Blood sugar, A1C, insulin sensitivity
• Physical Fitness: VO2 max, flexibility, strength assessments
• Body Composition: BMI, body fat percentage, muscle mass
• Sleep Quality: Hours, sleep efficiency, restfulness ratings
• Stress Levels: Cortisol, self-reported stress, heart rate variability
• Nutrition: Diet quality scores, micronutrient levels

Three datasets compared:

• Baseline assessment (program start)
• 3-month progress check
• 6-month results

Key insights revealed:

• Cardiovascular and metabolic health showed dramatic improvement
• Physical fitness gains were more gradual but consistent
• Sleep quality improved significantly after stress management training
• Visual progress motivated patient to continue healthy behaviors

Example 8: Web Framework Comparison

Industry: Software Development

Use Case: Development team selecting frontend framework for new application.

Variables measured (0-10 scale):

• Performance: Bundle size, rendering speed, optimization capabilities
• Developer Experience: Learning curve, tooling, debugging, documentation
• Community & Ecosystem: Library availability, community size, job market
• Maturity: Stability, backwards compatibility, long-term support
• Flexibility: Use case versatility, architectural freedom
• Team Familiarity: Existing skills, similar patterns to current stack

Key insights revealed:

• Framework A offers best performance but requires learning new paradigms
• Framework B has strongest ecosystem and team familiarity
• Framework C provides most flexibility but is less mature
• Trade-offs between short-term productivity and long-term optimization