What organizations already measure
These measures can tell leadership whether something happened, how many people participated, or whether a target was reached.
- Awareness
- Attendance
- Participation
- Engagement activity
- Satisfaction
- Sales
Proprietary Research Case Study
LA READINESS INDEX™ Building a Local Trust Intelligence Baseline for Los Angeles
Los Angeles is not one audience. It is a layered civic and commercial environment shaped by neighborhoods, cultural ecosystems, social communities, institutional histories, and lived local experience.
Icon Element built the LA Readiness Index™ to establish an initial trust-intelligence baseline for how organizational credibility is interpreted across Los Angeles's diverse communities, and how trust-related perceptions connect to participation, support, loyalty, resilience, and stated economic behavior. V1 was designed as a broad first iteration, not an exhaustive profile of every neighborhood or community.
National trust research established why trust matters. It did not answer the local question we wanted to investigate in Los Angeles.
The Intelligence Gap
Organizations can measure activity.Activity does not always explain meaning.
Activity can tell leadership what happened.Trust Intelligence investigates what it meant.
What makes organizational behavior feel credible in Los Angeles, and what happens when people believe it?
What We Set Out to Understand
Four questions shaped the research.
What appears to support credibility?
What behaviors, signals, and conditions do Angelenos associate with authentic, accountable organizational engagement?
What appears to undermine credibility?
What causes engagement to be interpreted as performative, self-serving, inconsistent, or disconnected from actual community need?
How does credibility relate to stakeholder response?
When respondents report stronger trust-building conditions, what else do they report being more willing to do?
What should leadership understand because of it?
If meaningful relationships exist between trust-related perceptions and stakeholder response, what changes about how leaders should think about trust?
The goal was not to create another opinion survey. It was to investigate the relationship between organizational behavior, stakeholder interpretation, and reported response.
The Research
We designed the study to capture measurable patterns and human meaning.
The question required both measurable patterns and human interpretation. The LA Readiness Index™ V1 therefore combined quantitative survey research with qualitative interviews: quantitative research helped show what respondents reported and which responses moved together, while qualitative research helped us examine how people interpreted organizational behavior and why credibility was being granted or withheld.
V1 was the first iteration of a broader measurement program. Its role was to test the underlying hypothesis and establish a foundation that future iterations can deepen across Los Angeles's communities, geographies, and stakeholder environments.
Measured trust-related perceptions, engagement, participation, support, purchase intentions, loyalty, resilience, and other reported stakeholder responses.
Used a defined interview methodology to explore how Angelenos described credibility, authenticity, organizational motive, accountability, presence, and follow-through.
Compared measurable patterns with qualitative evidence to understand not only what respondents reported, but how they made sense of the organizational behaviors being evaluated.
Converted the evidence into implications about how leaders should understand organizational credibility, stakeholder response, and local trust conditions.
Explore the Research Methodology+
Quantitative component
- 402 completed respondent records
- Los Angeles Designated Market Area (LA DMA)
- March 2026 field period
- Survey domains included trust, authenticity, participation, purchasing behavior, loyalty, resilience, and ethical community engagement
- Respondent-level data were demographically calibrated toward an LA DMA adult benchmark approximation before interpretation of weighted estimates
Qualitative component
- 15 qualitative interviews
- Icon Element co-founder Gattison led and conducted the qualitative research
- The interviews explored credibility, authenticity, organizational motive, community presence, accountability, and follow-through
- The qualitative evidence was used to deepen interpretation and surface recurring themes and meanings
The qualitative interviews were designed to deepen interpretation and surface recurring themes and meanings. They were not treated as a statistically representative sample of all Angelenos.
The Analysis
We did not stop at percentages.
Once fieldwork was complete, the analysis was designed around four practical questions: could the estimates be interpreted responsibly, were the favorable responses isolated or part of a broader pattern, did those responses connect to outcomes leaders care about, and how far could the evidence responsibly take us?
We used age, gender, and an available race/ethnicity proxy to better align the respondent data with an LA DMA adult benchmark approximation before interpreting the weighted estimates.
Isolated, or Part of a Broader
Pattern?
Respondents were asked to indicate their level of agreement with six statements about a business that consistently shows up for their community. Those statements covered recommendation, choice, willingness to pay more, defense, loyalty, and forgiveness. We tested whether those different forms of support tended to move together as part of a broader stakeholder support and commitment pattern.
We examined whether support, commitment, and trust-related responses were meaningfully associated with engagement, purchase, participation, willingness to pay, and other reported outcomes.
We separated what V1 could support from what it could not, including the distinction between trust conditions, trust itself, stakeholder support and commitment, and downstream response.
What the Deeper Testing Allowed Us to Conclude
The value of the analysis was not only finding patterns. It was knowing which conclusions those patterns could support.
Respondents were reacting to the same scenario: a business that consistently shows up for their community. Their agreement with statements about recommendation, choice, willingness to pay more, defense, loyalty, and forgiveness moved together strongly enough to support reading them as one broader support and commitment pattern.
What the testing added: The six percentages did not need to be interpreted as disconnected favorable reactions. Together, they provided evidence of a broader support and commitment pattern.
We statistically tested the relationship between selected trust-related responses and stated purchase response. Respondents reporting stronger trust-related responses also tended to report stronger stated purchase responses across related scenarios.
What the testing added: V1 provided enough evidence to treat the trust-purchase relationship as a meaningful association worth leadership attention, while stopping short of a causal claim.
The results support a coherent support and commitment pattern and meaningful associations with relevant outcomes. They do not establish causation or turn the six responses into a complete measure of trust.
What the testing added: The case became stronger by distinguishing what the evidence established from what would have been an overclaim.
Rigor came from testing whether the pattern held together statistically, testing how it related to relevant outcomes, and limiting the conclusion to what the evidence could support.
See the Technical Analysis+
Support / commitment reliability
Weighted α = .883. After demographic calibration, the six-item support and commitment battery remained highly internally consistent.
Dimensionality
One shared dimension. The six items behaved like indicators of a common stakeholder support and commitment disposition rather than six unrelated favorable opinions.
Trust to purchase relationship
Weighted Spearman r = .582. Respondents reporting stronger trust-related responses also tended to report stronger stated purchase responses across the related scenarios.
Demographic calibration
Age, gender, and an available race/ethnicity proxy were used to calibrate the respondent data toward an LA DMA adult benchmark approximation. Calibration improves demographic alignment but does not create a probability sample.
Reliability testing
Internal consistency was evaluated for the six responses to this shared business/community scenario, including weighted analysis.
Dimensionality testing
The same six responses were tested to determine whether they behaved like one coherent underlying dimension rather than six unrelated favorable reactions.
Relationship testing
Selected support, commitment, and trust-related measures were tested against engagement, purchase, participation, willingness to pay, and other theoretically relevant outcomes.
Evidence boundary
The analysis supports association, reliability, dimensionality, and preliminary validity evidence. It does not establish causation or a validated multi-item Trust Scale.
Proprietary methodology
This case study reports the evidence needed to evaluate the work without publishing the full instrument mapping, item-level diagnostics, weighting implementation, scoring logic, or future measurement architecture.
What We Found
Four findings changed how we think about trust in Los Angeles.
Percentages shown below use the calibrated V1 estimates from the weighted analysis.
People judge the credibility of engagement, not just its visibility.
Across the study, respondents evaluated more than whether an organization showed up. The pattern pointed to motive, real community stake, consistency, and follow-through as part of how engagement is interpreted.
See the recurring concerns +
Hidden political or financial agendas
Showing up only when it benefits the brand
No follow-through after promises
Not addressing actual community needs
Using community engagement mainly for marketing or PR
Trust-related responses are meaningfully associated with willingness to purchase.
77.7% of respondents said trust-building behaviors would make them more likely to purchase.
The weighted analysis also found that stronger trust responses tended to move with stronger stated purchase responses across related scenarios.
See the statistical relationship +
Weighted Spearman r = .582
In plain language: respondents reporting stronger trust-related responses also tended to report stronger stated purchase responses. This association does not establish causation.
Respondents said they would accept more cost or less convenience for businesses investing meaningfully in their community.
84.1% said they would pay some amount more for a local LA business investing meaningfully in their community.
46.0% said they would choose that business over a more convenient national brand.
Stakeholder support appears to extend beyond a single transaction.
For a business that consistently shows up for the community, 78.4% agreed they would stay loyal over time.
For that same type of business, 77.5% agreed they would be more likely to forgive a mistake if it were addressed properly.
Why that distinction matters +
These six responses all came from the same scenario: how respondents would react to a business that consistently shows up for their community. The battery covered recommendation, choice, willingness to pay more, defense, loyalty, and forgiveness. Because those responses moved together strongly, the loyalty and forgiveness findings should not be read as isolated reactions. Together, they show a broader pattern of stakeholder support and commitment. That is different from claiming the six responses are a complete measure of trust.
Technical note: Weighted reliability for the six-item support and commitment battery was α = .883.
What This Case Means for Leadership
What did this work change about the leadership question?
The research does not tell every organization that it is trusted. It shows why credibility deserves to be measured, how trust-related perceptions can connect to consequential outcomes, and where assumption is no longer enough.
Visibility is not credibility.
People evaluate the behavior behind engagement. Motive, local stake, consistency, and follow-through can shape whether presence is interpreted as meaningful or performative.
Trust-related perceptions are commercially relevant.
People who reported stronger trust responses also tended to report stronger purchase responses. And 84.1% said they would pay some amount more for a local LA business investing meaningfully in their community. Together, those findings make trust a business question, not only a reputation question.
Support can extend beyond the transaction.
Loyalty and forgiveness sit inside a coherent support and commitment pattern. That suggests stakeholder relationships can carry value beyond a single purchase or moment of engagement.
Measure your own trust footprint.
The LA Readiness Index identifies patterns worth investigating across Los Angeles. It does not diagnose a specific organization. Leaders need organization-specific evidence to understand where credibility is creating value, friction, or risk in their own stakeholder environment.
If trust-related perceptions are connected to purchase, willingness to pay more, loyalty, forgiveness, and willingness to accept convenience tradeoffs, mistrust is not just a reputation problem. It can become an operating and economic cost.
The leadership implication
Visibility, participation, and positive sentiment should not automatically be treated as evidence of trust. The more consequential question is how stakeholders interpret organizational behavior and whether those interpretations connect to the outcomes leadership cares about.
Why the Measurement Architecture Matters +
Trust conditions are not trust. Trust is not commitment. Commitment is not behavior.
V1 clarified why those layers should remain distinct rather than being collapsed into one score.
A useful Trust Intelligence system should distinguish what an institution does, what people believe, what level of support develops, and what stakeholder response follows.
What the Case Required
The work moved from aconsequential question toevidence leadership could use.
The case required four disciplines working together.
The work began by turning a broad question about trust into specific questions that could actually be investigated: what people were interpreting, what appeared to shape that interpretation, and what those perceptions connected to behaviorally.
Quantitative evidence showed measurable patterns. Qualitative evidence helped explain how people made sense of organizational behavior. The leadership question required both.
Promising results were pressure-tested before they were translated into conclusions. When the evidence required narrower language, the language changed.
The work did not end with a dataset. The final task was determining what the evidence changed about the leadership question and what leaders should understand because of it.
That is where research becomes decision-ready Trust Intelligence.
The objective is not more information. It is less uncertainty around consequential decisions.
From Los Angeles to Anywhere
What Icon Element built in Los Angeles can be rebuilt for another city, market, or organization.
The methodology is portable. The intelligence is local. We bring the same research discipline to a new environment, then build the evidence around its people, history, geography, organization, and leadership decision.
What stays consistent
We bring the same research discipline.
- Research architecture
- Evidence standards
- Mixed-method capability
- Statistical discipline
- Human interpretation
- Executive translation
The repeatable method Define the leadership question, gather the right evidence, test what it supports, and translate the findings into decision-ready intelligence.
What changes
We rebuild the evidence for the local environment.
- Your organization
- Your initiative
- Your stakeholders
- Your geography
- Your institutional history
- Your decision context
The local intelligence The methodology travels. The findings do not. A new stakeholder environment requires new evidence built for that place and decision.
Example research questions
A different client produces a different research design.
Why is participation lower than expected?
How are our community investments being interpreted, and what do they mean for institutional credibility?
What is shaping resistance to this initiative?
What do stakeholders need before they will support this decision?
Why This Team
Two different ways of seeing the same evidence.
Icon Element's approach is built on two complementary disciplines: understanding the human meaning underneath stakeholder response and determining which conclusions the evidence can responsibly support.
Gattison
Meaning
Human Behavior + Cultural Interpretation
Gattison focuses on the human layer of the work: how organizational behavior is interpreted, what people mean when they describe credibility or mistrust, what qualitative evidence reveals about lived experience, and what those patterns mean for leadership.
Jose
Signal
Research Architecture + Measurement Integrity
Jose focuses on the analytical system: research design, quantitative analysis, measurement architecture, statistical rigor, documentation, and the boundary between what the evidence suggests and what it actually establishes.
MEANING+SIGNAL→DECISION
One founder asks, "What does this mean?" The other asks, "What evidence allows us to say that?"Humanity in the data, discipline in the system.
Research Integrity
A hypothesis is not a finding.
V1 provides a meaningful empirical starting point for Icon Element's Los Angeles trust research. It also clarified exactly where the evidence ends.
V1 supports
- A highly consistent stakeholder support and commitment pattern
- Meaningful relationships between that support and commitment pattern and relevant engagement, purchase, participation, and willingness-to-pay responses
- Meaningful relationships between selected trust-related responses and stated purchasing responses
- A clear analytical distinction between trust conditions, stakeholder support / commitment, and downstream response
- Candidate trust-building conditions worthy of further study
V1 does not establish
- A fully validated multi-item scale for measuring trust
- That trust causes purchase, loyalty, or willingness to pay
- A probability sample representative of all adults in the Los Angeles DMA
- That every favorable stakeholder response should be called trust
Rigor is not certainty.
Rigor is knowing exactly where certainty ends.
View Research Limitations +
- The panel-based sample is not equivalent to a probability sample of all LA DMA adults.
- Demographic calibration improves alignment but cannot eliminate all selection or coverage bias.
- The available race/ethnicity calibration variable was a proxy rather than a Census-standard race/ethnicity item.
- Most behavioral outcomes are stated intentions or scenario responses rather than observed real-world behavior.
- Cross-sectional relationships do not establish causation.
Additional technical documentation can be provided for appropriate procurement, research, or due-diligence review.
V1 is the starting point, not the ceiling. Future iterations can deepen the Los Angeles baseline with larger samples, more deliberate geographic and subgroup analysis, and organization-specific studies designed around the communities, stakeholders, and decisions at stake.
A Different Organization. A Different Question.
What would this reveal about your organization?
Your leadership question may be different. Perhaps you need to understand why participation is weak. Why an initiative is meeting resistance. How stakeholders are interpreting your presence. Whether community investment is translating into stronger support. Or what conditions need to exist before a consequential initiative moves forward.
Those are not communications questions alone. They are intelligence questions.
And when the consequences are significant, leadership should not have to answer them through assumption.