Job Execution Metrics

What is Job Execution Metrics?

Job Execution Metrics is a comprehensive framework for measuring product and service performance based on how effectively they help customers accomplish their Jobs To Be Done. Unlike traditional product metrics that often focus on usage statistics or satisfaction scores, Job Execution Metrics directly measure improvements in the speed, accuracy, and success rate with which customers can achieve their goals when using a solution.

This approach creates a more meaningful measurement system by connecting product performance to customer outcomes rather than product interactions. By establishing metrics that evaluate how well products help customers execute the specific steps in their jobs, companies gain deeper insights into product value, more accurately predict customer behavior, and build more effective improvement roadmaps.

Job Execution Metrics shifts measurement focus from "Are customers using our features?" to "Are customers successfully achieving their goals?" This fundamental reorientation creates stronger alignment between product teams and customer value creation.

Why are Job Execution Metrics important?

Traditional product metrics often fail to provide meaningful guidance for several key reasons:

1. Activity without outcomes

Usage statistics like page views or feature clicks measure activity but provide little insight into whether customers are successfully achieving their goals.

2. Satisfaction without context

General satisfaction scores don't reveal which specific aspects of job execution are driving customer perceptions, limiting their actionability.

3. Disconnection from purchase motivation

Most traditional metrics fail to connect to the fundamental reasons customers buy and use products—to make progress on goals that matter to them.

4. Insufficient innovation guidance

Without understanding how products affect job execution, metrics provide limited direction for meaningful innovation.

5. Lagging behavioral indicators

Traditional measures like retention and churn signal problems only after they occur, without revealing their underlying causes.

What are the key components of effective Job Execution Metrics?

A comprehensive approach to Job Execution Metrics includes these key components:

1. Job Success Metrics

Measurements of overall job completion:

• Success rate (percentage of job attempts that achieve desired outcomes)
• Completion time (how long it takes to execute the entire job)
• Error rate (frequency of mistakes during job execution)
• First-time success (percentage of jobs completed correctly on first attempt)
• Perceived effort (how difficult customers find job execution)

These top-level metrics reveal how well the solution enables overall job accomplishment.

2. Step-Specific Performance Metrics

Detailed measurements for individual job steps:

• Step completion rate (percentage of customers who successfully complete each step)
• Step execution time (how long each job step takes)
• Step accuracy (correctness of decisions or actions within steps)
• Step sequence adherence (whether customers follow optimal step sequences)
• Step iteration frequency (how often steps must be repeated)

These step-level metrics identify specific areas for improvement within the job flow.

3. Need Satisfaction Metrics

Assessments of how well specific customer needs are met:

• Need importance ratings (how crucial each need is to customers)
• Need satisfaction scores (how well current solutions address each need)
• Satisfaction gap analysis (difference between importance and satisfaction)
• Comparative need satisfaction (performance versus alternatives)
• Need satisfaction trends (how scores evolve over time)

These need-level metrics reveal the most valuable improvement opportunities.

4. Job Context Metrics

Measurements related to job execution circumstances:

• Job frequency (how often customers attempt the job)
• Job trigger analysis (what circumstances prompt job execution)
• Context variation impact (how performance varies across situations)
• Environmental factor effects (how external conditions affect execution)
• Job abandonment patterns (when and why customers give up)

These contextual metrics provide essential understanding of real-world job execution.

5. Economic Impact Metrics

Measurements connecting job execution to customer value:

• Time savings value (economic impact of faster job completion)
• Error cost reduction (financial benefit of fewer mistakes)
• Output quality improvement (value of better job outcomes)
• Resource optimization (efficiency gains in job execution)
• Opportunity enablement (new possibilities created by better execution)
• These economic metrics translate job improvement into tangible customer value.

How do you implement effective Job Execution Metrics?

1. Start with comprehensive job mapping

Build the foundation for meaningful measurement:

• Define the overall job customers are trying to accomplish
• Break down the job into discrete steps (typically 15-20)
• Identify specific needs within each step (usually 5-10 per step)
• Validate the job map with diverse customers
• Document the job execution context and variations

This job mapping creates the structure for all subsequent metrics.

2. Establish baseline measurements

Capture current job execution performance:

• Measure how customers execute the job before using your solution
• Document execution with competitive or alternative approaches
• Capture quantitative data on time, accuracy, and completion rates
• Gather qualitative insights on pain points and workarounds
• Create segment-specific baselines reflecting different customer groups

These baselines provide the comparison point for measuring improvement.

3. Design job-centered measurement systems

Create mechanisms to capture job execution data:

• Implement analytics that track job step completion
• Design surveys focused on job execution experiences
• Create observational studies of actual job performance
• Develop feedback mechanisms tied to specific job steps
• Build customer interview protocols centered on job execution

These systems provide ongoing data about job performance.

4. Analyze job execution patterns

Identify meaningful patterns in measurement data:

• Look for steps with highest failure or abandonment rates
• Identify bottlenecks that slow overall job completion
• Discover error-prone decision points or actions
• Find variations in performance across customer segments
• Detect relationships between different metrics

This analysis reveals the most significant job execution insights.

5. Connect metrics to product decisions

Translate job execution data into action:

• Prioritize product improvements based on job step struggles
• Design features specifically to address high-impact metrics
• Set quantitative targets for job execution improvement
• Create dashboards that highlight key job performance indicators
• Implement review processes that connect metrics to roadmaps

These connections ensure metrics drive meaningful product enhancement.

6. Implement continuous measurement cycles

Establish ongoing improvement processes:

• Schedule regular metric review sessions
• Implement A/B testing focused on job execution improvements
• Create feedback loops that capture evolving job execution patterns
• Refine measurement approaches based on new insights
• Develop comparative analyses across product versions

These cycles create sustainable job-centered improvement.

What frameworks help with Job Execution Metrics?

The Job Step Performance Dashboard

This framework visualizes execution across job steps:

• Horizontal axis represents sequential job steps
• Vertical axis shows performance metrics for each step
• Color coding indicates performance levels (good/fair/poor)
• Trend lines show changes over time
• Segment comparison reveals performance variations

This dashboard provides a comprehensive view of where job execution succeeds or struggles.

The Need Satisfaction Matrix

This framework maps needs to satisfaction levels:

• Rows represent specific customer needs
• Columns show importance and satisfaction scores
• Calculated opportunity scores highlight improvement priorities
• Competitive comparisons show relative performance
• Trend indicators track satisfaction changes

This matrix identifies which specific needs represent the greatest opportunities.

The Job Execution Funnel

This framework tracks progression through job steps:

• Shows percentage of customers who successfully complete each step
• Identifies where customers abandon the job
• Highlights conversion between sequential steps
• Compares performance across customer segments
• Tracks improvement over time

This funnel reveals where customers struggle to progress through the job.

The Execution Efficiency Scorecard

This framework measures job execution productivity:

• Shows time required for each job step
• Tracks resources consumed during execution
• Calculates error rates and correction costs
• Measures iteration and rework frequency
• Compares actual versus optimal execution

This scorecard quantifies the efficiency of job execution.

The Progress Milestone Map

This framework tracks achievement of key job outcomes:

• Identifies critical success milestones in job execution
• Shows percentage of customers achieving each milestone
• Measures time to milestone achievement
• Tracks abandonment before key milestones
• Compares milestone achievement across segments
• This map reveals how effectively customers reach meaningful job outcomes.

What are common challenges in implementing Job Execution Metrics?

Measurement complexity

Tracking detailed job execution can require sophisticated analytics and research. Starting with the most critical job steps and gradually expanding measurement helps manage this complexity.

Attribution difficulties

Determining how much product improvements versus other factors affect job execution can be challenging. Controlled experiments and comparison groups help isolate the impact of specific changes.

Data integration issues

Job execution often spans multiple systems and touchpoints, making data collection and integration difficult. Creating unified customer identifiers and integrated analytics platforms helps address this challenge.

Baseline establishment

Without clear "before" measurements, improvement impact is difficult to assess. Investing in baseline research before implementing changes provides essential comparison points.

Metric proliferation

Too many metrics create confusion and dilute focus. Selecting a vital few metrics tied to the most important job steps prevents metric overload while maintaining comprehensive job coverage.

How do you use Job Execution Metrics to drive product improvement?

1. Identify critical improvement opportunities

Use metrics to discover high-impact enhancement targets:

• Focus on steps with lowest completion rates
• Target needs with highest importance-satisfaction gaps
• Address steps that create bottlenecks in overall job execution
• Prioritize errors with greatest economic impact
• Identify segments with poorest job execution performance

These targeted opportunities create the foundation for meaningful improvement.

2. Set quantitative improvement targets

Establish clear goals for job execution enhancement:

• Define specific metric improvements for each initiative
• Set timelines for achieving target performance levels
• Create segment-specific objectives where appropriate
• Establish competitive benchmarks as targets
• Balance short-term improvements with long-term objectives

These clear targets create accountability for customer outcomes.

3. Design solutions focused on job metrics

Create product enhancements directly tied to job execution:

• General concepts specifically addressing metric deficiencies
• Evaluate concepts based on potential metric improvement
• Prototype with instrumentation to measure job execution impact
• Test variations to optimize metric performance
• Implement monitoring to verify production performance
• This job-centered design process ensures solutions address genuine customer needs.

4. Implement measurement-driven development

Integrate metrics throughout the development process:

• Include job execution metrics in requirements and specifications
• Set acceptance criteria based on job performance improvements
• Create development environments that simulate job execution
• Implement continuous testing focused on job metrics
• Release based on job execution improvements rather than feature completion
• This integration ensures development directly enhances customer job execution.

5. Create continuous improvement cycles

Establish ongoing processes for job execution enhancement:

• Schedule regular metric review sessions
• Implement systematic A/B testing for job optimization
• Create rapid response processes for metric degradation
• Develop cross-functional improvement teams for complex job steps
• Celebrate meaningful metric improvements

These continuous cycles create sustained job execution enhancement.

How do you measure the business impact of Job Execution Metrics?

Customer Success Metrics

These connect job execution to customer outcomes:

• Retention differential - Higher retention among customers with better job execution
• Expansion correlation - Relationship between job success and additional purchases
• Advocacy linkage - Connection between job execution and referral behavior
• Support reduction - Decreased support needs with improved job metrics
• Onboarding acceleration - Faster time to successful job execution for new customers

These metrics reveal how job execution affects customer relationship value.

Market Performance Metrics

These show how job execution affects market position:

• Competitive win rate - Success in competitive situations based on job execution advantage
• Market share growth - Expansion correlated with job execution improvements
• Price premium sustainability - Ability to maintain higher prices based on superior job execution
• Category leadership - Recognition for excellence in enabling job accomplishment
• Market influence - Impact on market expectations for job execution

These metrics demonstrate the market advantages of superior job enablement.

Financial Impact Metrics

These connect job execution to financial outcomes:

• Revenue growth - Increases attributable to better job execution
• Customer acquisition efficiency - Lower costs to acquire customers based on job reputation
• Lifetime value enhancement - Higher customer value from improved job satisfaction
• Development ROI - Better return on investment for job-focused improvements
• Valuation multiple impact - Effect on company valuation from job execution leadership

These metrics translate job execution into financial performance.

Organizational Capability Metrics

These measure how metrics enhance organizational effectiveness:

• Decision quality - Improvement in product decisions based on job metrics
• Development efficiency - Enhanced resource utilization through clearer priorities
• Cross-functional alignment - Better coordination around job execution objectives
• Innovation effectiveness - Higher success rates for new features and products
• Learning acceleration - Faster organizational adaptation based on job insights

These metrics reflect the operational benefits of job-centered measurement.

How do Job Execution Metrics differ from traditional product metrics?

Versus Usage Metrics

Traditional usage metrics like active users or session duration measure product interaction without revealing job success. Job Execution Metrics directly measure whether customers achieve their goals, providing more meaningful indicators of product value.

Versus Satisfaction Scores

Traditional satisfaction measurements like NPS or CSAT provide general sentiment without explaining its causes. Job Execution Metrics reveal precisely which aspects of job performance drive satisfaction, creating more actionable insights.

Versus Feature Adoption Metrics

Traditional feature tracking measures how many customers use specific functionality. Job Execution Metrics assess whether that functionality actually helps customers make progress, connecting adoption to outcomes.

Versus Engagement Metrics

Traditional engagement metrics like time in app or interaction frequency can actually indicate struggle rather than success. Job Execution Metrics distinguish between productive engagement and frustration by focusing on outcomes.

Versus Conversion Funnel Metrics

Traditional funnels measure progression through predetermined application flows. Job Execution Metrics track progress through the customer's natural job sequence, which may not match the designed application thrv helps with Job Execution Metrics

thrv provides specialized methodologies and tools to help companies implement effective Job Execution Metrics centered on customer jobs and outcomes. The thrv platform enables teams to map customer jobs, identify critical success metrics, implement measurement systems, analyze job execution patterns, connect metrics to product decisions, and create continuous improvement cycles.

For organizations struggling with ineffective metrics, unclear product direction, or disconnection from customer outcomes, thrv's approach to Job Execution Metrics provides a clear path to more meaningful measurement based on a deeper understanding of what truly matters to customers. The result is better product decisions, higher customer success rates, and stronger business performance—all derived from measuring how effectively products help customers execute their most important jobs.

Need Satisfaction Score

What is a Need Satisfaction Score?

A Need Satisfaction Score is a quantitative measurement that indicates how well a product or service satisfies specific customer needs within their Job To Be Done. Unlike traditional satisfaction metrics that measure general sentiment or feature preferences, Need Satisfaction Scores directly assess how effectively solutions help customers execute the actions and decisions required to accomplish their goals.

This metric typically combines customer ratings of both the importance of a need and their satisfaction with current solutions, creating a clear picture of which needs represent the greatest opportunities for innovation and improvement. By systematically measuring satisfaction across all needs in a customer's job, companies can identify precisely where to focus product development resources for maximum impact.

Need Satisfaction Scores transform subjective customer feedback into actionable, quantitative data that guides strategic decisions about product direction, feature prioritization, and competitive positioning—all grounded in genuine customer value creation rather than internal assumptions or competitive feature matching.

Why are Need Satisfaction Scores important?

Traditional satisfaction metrics often fail to provide actionable guidance for several key reasons:

1. Insufficient specificity

General satisfaction scores don't reveal which specific aspects of the product drive satisfaction, limiting their value for improvement decisions.

2. Missing importance context

Without understanding how important different needs are to customers, satisfaction alone doesn't indicate which areas deserve attention.

3. Lack of prioritization framework

Traditional metrics rarely provide clear guidance on which improvements will create the most customer value.

4. Disconnection from job execution

Most satisfaction measures don't connect directly to how customers use products to accomplish their goals.

5. Limited competitive context

Traditional metrics often measure satisfaction in isolation, without showing how performance compares to alternatives.

What are the key components of effective Need Satisfaction Scores?

A comprehensive approach to Need Satisfaction Scores includes these key components:

1. Well-Defined Customer Needs

The foundation for meaningful measurement:

• Clear articulation of specific needs within each job step
• Needs formulated as actions and variables (e.g., "determine the optimal route")
• Solution-independent need definitions
• Consistent granularity across needs
• Validation of needs with diverse customers

These properly defined needs create the units for satisfaction measurement.

2. Importance Ratings

Assessment of need priority from the customer perspective:

• Customer ratings of how important each need is
• Consistent measurement scale (typically 1-10)
• Segment-specific importance analysis
• Contextual importance factors
• Relative importance rankings

These importance ratings identify which needs matter most to customers.

3. Satisfaction Measurements

Evaluation of current solution performance:

• Customer ratings of satisfaction with current approaches
• Same measurement scale as importance ratings
• Competitive benchmarking of satisfaction
• Segment-specific satisfaction analysis
• Satisfaction trends over time

These satisfaction assessments reveal how well current solutions perform.

4. Opportunity Score Calculations

Analysis that combines importance and satisfaction:

• Calculation of basic gaps (Importance - Satisfaction)
• Weighted opportunity scores (Importance + (Importance - Satisfaction))
• Normalization methods for consistent analysis
• Segmentation of scores across customer groups
• Visualization of opportunity landscapes

These calculations transform raw ratings into strategic insights.

5. Competitive Comparison Framework

Contextual evaluation against alternatives:

• Competitive satisfaction benchmarking
• Relative performance on high-importance needs
• Identification of comparative advantages and disadvantages
• Market coverage of unmet needs
• Emerging competitor analysis

This competitive context provides essential strategic perspective.

How do you implement effective Need Satisfaction Scores?

1. Start with comprehensive job mapping

Build the foundation for meaningful measurement:

• Define the overall job customers are trying to accomplish
• Break down the job into discrete steps (typically 15-20)
• Identify specific needs within each step (usually 5-10 per step)
• Formulate needs as actions and variables
• Validate the job map with diverse customers

This job mapping creates the structure for all subsequent scoring.

2. Design effective measurement instruments

Create research tools to capture accurate data:

• Develop survey instruments with clear need explanations
• Create consistent rating scales for importance and satisfaction
• Design sampling approaches for representative data
• Include segmentation variables for targeted analysis
• Incorporate competitive usage questions for context

These instruments ensure reliable and valid measurement data.

3. Collect baseline satisfaction data

Establish current performance levels:

• Gather ratings from diverse customer samples
• Include both current and potential customers
• Capture data across different usage contexts
• Collect ratings for both your solution and competitors
• Establish consistent measurement timing

This baseline data provides the foundation for tracking and improvement.

4. Calculate and analyze opportunity scores

Transform raw ratings into actionable insights:

• Calculate basic satisfaction gaps (Importance - Satisfaction)
• Compute weighted opportunity scores for prioritization
• Segment scores by customer characteristics
• Analyze patterns across job steps
• Identify the highest-opportunity needs

This analysis reveals where product improvements will create the most value.

5. Innovation into decision processes

Embed satisfaction scores in product development:

• Create dashboards showing key satisfaction metrics
• Develop review processes centered on opportunity scores
• Establish improvement targets for high-priority needs
• Train teams on interpreting and using satisfaction data
• Link development priorities to satisfaction improvement

This integration ensures scores drive meaningful action.

6. Implement continuous tracking systems

Establish ongoing measurement processes:

• Schedule regular satisfaction measurement
• Create consistent tracking methodologies
• Implement systems to detect satisfaction changes
• Develop competitive benchmarking processes
• Build capabilities for rapid research cycles

These systems ensure satisfaction insights remain current and valuable.

What formulas and frameworks help with Need Satisfaction Scores?

The Opportunity Algorithm

This calculation identifies needs with the greatest innovation potential:

• Opportunity = Importance + (Importance - Satisfaction)

Where:

• Importance is rated on a scale (typically 1-10)
• Satisfaction is rated on the same scale
• Scores range from 0-19 (on a 10-point scale)
• Scores above 15 indicate significant opportunities

This formula weights needs by both absolute importance and the gap between importance and satisfaction.

The Satisfaction Matrix

This framework maps needs by importance and satisfaction:

• Horizontal axis represents satisfaction levels
• Vertical axis represents importance levels

Plotting needs creates four quadrants:

• High importance/low satisfaction: Primary opportunities
• High importance/high satisfaction: Maintain performance
• Low importance/low satisfaction: Secondary considerations
• Low importance/high satisfaction: Possible overserving

This visual representation helps identify priority improvement areas.

The Net Satisfaction Index

This calculation creates a single metric for tracking:

• NSI = (% Highly Satisfied - % Dissatisfied) / Total Respondents * 100

Where:

• Highly Satisfied = ratings of 8-10 on a 10-point scale
• Dissatisfied = ratings of 1-4 on a 10-point scale

This index provides a simplified metric for tracking over time.

The Competitive Satisfaction Map

This framework compares performance across competitors:

• Rows represent high-opportunity needs
• Columns represent different competitors
• Cells contain satisfaction scores for each need-competitor combination
• Color coding highlights relative performance
• Summary scores show overall competitive position

This comparison reveals strategic opportunities and threats.

The Satisfaction Driver Analysis

This analytical approach identifies what drives overall satisfaction:

• Statistical correlation between specific need satisfaction and overall satisfaction
• Regression analysis to determine satisfaction impact weights
• Factor analysis to identify related need clusters
• Predictive modeling of satisfaction changes
• Scenario planning for satisfaction improvement

This analysis helps focus on the needs with greatest satisfaction leverage.

What are common challenges in implementing Need Satisfaction Scores?

Survey fatigue

Comprehensive need measurement can require lengthy surveys. Rotating need sets across different survey waves and using progressive questioning can help manage respondent burden.

Sampling bias

Satisfaction data collected only from current customers misses critical insights from non-customers. Including both users and non-users of your solution provides more complete market understanding.

Inconsistent question interpretation

Different customers may interpret need statements differently. Clear need formulation, examples, and consistency checks help ensure reliable responses.

Overreliance on averages

Mean satisfaction scores can hide important variations across segments. Always examining score distributions and segment-specific patterns prevents missing valuable insights.

Static measurement

Satisfaction expectations evolve over time as solutions improve. Regular measurement updates and trend analysis help maintain current understanding of satisfaction dynamics.

How do you use Need Satisfaction Scores to drive product improvement?

1. Prioritize product development investments

Use scores to focus resources on high-value opportunities:

• Rank needs by opportunity score to identify top priorities
• Group related high-opportunity needs into theme clusters
• Allocate development resources proportional to opportunity size
• Set improvement targets based on satisfaction gaps
• Track ROI of investments in satisfaction improvement

This prioritization ensures resources create maximum customer value.

2. Design targeted product enhancements

Create improvements specifically addressing satisfaction gaps:

• Generate solution concepts focused on high-opportunity needs
• Evaluate concepts based on potential satisfaction improvement
• Test prototypes with specific satisfaction metrics
• Implement features with clear satisfaction objectives
• Measure post-release satisfaction impact

This targeted approach ensures improvements address genuine customer needs.

3. Develop competitive differentiation strategies

Leverage satisfaction insights for positioning:

• Identify needs where your solution outperforms competitors
• Discover unaddressed needs where no competitor excels
• Develop messaging highlighting satisfaction advantages
• Create comparisons based on need satisfaction rather than features
• Monitor competitive responses to satisfaction improvements

These strategies create meaningful market differentiation.

2. Guide customer segmentation and targeting

Use satisfaction patterns to refine market approach:

• Identify segments with distinct satisfaction profiles
• Target segments with greatest improvement potential
• Customize solutions for segment-specific satisfaction gaps
• Align marketing with segment satisfaction priorities
• Develop segment-specific onboarding focused on key needs

This targeted approach maximizes impact across diverse customer groups.

5. Establish performance management systems

Create accountability for satisfaction improvement:

• Set team objectives based on satisfaction metrics
• Develop incentives tied to satisfaction improvement
• Implement regular review processes for satisfaction scores
• Create cross-functional responsibility for satisfaction
• Celebrate meaningful satisfaction enhancements

These systems embed satisfaction improvement in organizational culture.

How do you measure the business impact of Need Satisfaction Scores?

Customer Behavior Metrics

These connect satisfaction to customer actions:

• Purchase correlation - Relationship between satisfaction and buying decisions
• Retention impact - How satisfaction affects customer loyalty
• Expansion connection - Link between satisfaction and additional purchases
• Referral behavior - Relationship between satisfaction and recommendations
• Price sensitivity - How satisfaction affects willingness to pay

These metrics reveal how satisfaction influences customer relationship value.

Operational Effectiveness Metrics

These show how satisfaction measurement improves operations:

• Development efficiency - Improved resource utilization through clearer priorities
• Issue resolution - More effective problem identification and resolution
• Release quality - Enhanced customer reception of new features
• Support reduction - Decreased support needs with improved satisfaction
• Onboarding success - Better initial customer experience

These metrics demonstrate operational benefits from satisfaction focus.

Market Performance Metrics

These connect satisfaction to competitive position:

• Win rate improvement - Increased success in competitive situations
• Market share growth - Expansion attributable to satisfaction advantages
• Category leadership - Recognition for satisfaction excellence
• Competitive response - Competitor reactions to satisfaction initiatives
• Customer acquisition efficiency - Improved acquisition metrics from satisfaction reputation

These metrics show how satisfaction creates market advantages.

Financial Impact Metrics

These link satisfaction to business outcomes:

• Revenue growth - Increases attributable to satisfaction improvement
• Margin enhancement - Pricing power from superior satisfaction
• Development ROI - Return on investment in satisfaction initiatives
• Valuation impact - Effect on company valuation from satisfaction leadership
• Cost reduction - Decreased expenses from more efficient development

These metrics translate satisfaction into financial performance.

How do Need Satisfaction Scores differ from traditional satisfaction metrics?

Versus Net Promoter Score (NPS)

NPS measures likelihood to recommend without revealing why customers would or wouldn't recommend. Need Satisfaction Scores identify precisely which aspects of the solution drive or hinder advocacy, providing actionable improvement guidance.

Versus Customer Satisfaction (CSAT)

Traditional CSAT measures general satisfaction with products or experiences. Need Satisfaction Scores assess specific job execution aspects, creating clearer connections between satisfaction and customer goals.

Versus Customer Effort Score (CES)

CES measures how easy it is to use a product or service, but doesn't identify which specific needs require less effort. Need Satisfaction Scores pinpoint exactly where effort reduction would create the most value.

Versus Feature Satisfaction Ratings

Traditional feature ratings assess satisfaction with product elements without connecting to customer goals. Need Satisfaction Scores evaluate how well products help customers execute job steps, regardless of which features enable that execution.

Versus Sentiment Analysis

Traditional sentiment tracking measures positive or negative feelings without explaining their causes. Need Satisfaction Scores reveal precisely which job execution aspects drive sentiment, creating clear priorities.

How thrv helps with Need Satisfaction Scores

thrv provides specialized methodologies and tools to help companies implement effective Need Satisfaction Scores centered on customer jobs and outcomes. The thrv platform enables teams to map customer jobs, identify critical needs, design measurement instruments, collect satisfaction data, calculate opportunity scores, visualize satisfaction landscapes, and connect satisfaction insights to product decisions.

For organizations struggling with unclear priorities, ineffective metrics, or disconnection from customer value, thrv's approach to Need Satisfaction Scores provides a clear path to more impactful product development based on a deeper understanding of what truly matters to customers. The result is better development decisions, higher customer satisfaction, and stronger business performance—all derived from measuring how effectively products help customers satisfy their most important needs.