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SondaIntel

SONDAINTEL / FOUNDATIONS

Depth in analysis.
Clarity in decisions.

A survey starts with a question. A sound assessment needs design, mathematics, interpretation, and criteria for recognizing what the data cannot tell us.

Explore our foundations
BEHAVIORSTRATEGYSTATISTICSCRITICAL THINKING

01 / METHODOLOGICAL FOUNDATIONS

From reference to procedure.

These are conceptual lenses and families of analysis. Their inclusion does not mean they are all automatically applied to every study.

01Daniel Kahneman

Systems 1 and 2

Kahneman distinguishes fast, intuitive processes from deliberate, effortful ones. This lens helps examine judgment, wording, and cognitive load.

Does the question require recall, calculation, or an immediate impression?
IN PRACTICE

Review response effort, wording, and anchors. A stated response does not directly identify a mental system.

Kahneman’s Nobel lecture
02John Nash

Strategic interdependence

Game theory provides a framework for studying decisions whose outcomes also depend on other agents’ choices.

Which incentives and possible responses belong in the scenario?
IN PRACTICE

State the agents, incentives, and scenario assumptions. The result is not a guaranteed prediction.

Nash’s work on game theory
03Karl Popper

Testable hypotheses

A critical assessment of hypotheses requires seeking evidence that could contradict them and stating the limits of conclusions.

What evidence would make us revise this interpretation?
IN PRACTICE

Record the hypothesis and the evidence that would lead us to reject it. A single survey does not establish causation.

The Logic of Scientific Discovery
04Critical assessment of the sample

Survivorship bias

Looking only at cases that remain visible can exclude important experiences. The design must consider who was left out of the sample.

Are we only listening to people who stayed as customers?
IN PRACTICE

Document who was invited, who responded, and which experiences may have been left out.

05Statistical tools

Multivariate analysis

Studying variables together can help investigate relationships and profiles. Model selection depends on the design, variables, and available data.

Is this model appropriate for these data and this decision?
IN PRACTICE

Define variables, usable sample size, and model diagnostic criteria before interpreting relationships.

06Nassim Nicholas Taleb

Sensitivity of the assessment

Nassim Nicholas Taleb studies uncertainty, model error, and extreme events. His work encourages caution with extrapolation and conclusions that depend on fragile assumptions.

Does the interpretation hold when assumptions change?
IN PRACTICE

Compare plausible scenarios and disclose when a conclusion depends heavily on an assumption.

Taleb’s research on model error
07Priming and context

Effects of preceding questions

Earlier questions can influence later answers. Reviewing the sequence and testing alternative orders helps investigate this effect in the instrument.

Is the preceding question suggesting what the person should consider?
IN PRACTICE

Record question order and justify changes between rounds. Priming is not an automatic platform index.

Question order and wording — Pew Research Center
08Pretesting and equivalence

Quality before collection

Testing comprehension, answer choices, and the flow before collection helps identify problems. Instruments in another language need their own review and pretest.

Do people interpret this question as intended?
IN PRACTICE

Review each translation with the intended audience before treating it as equivalent.

Survey best practices — AAPOR
09Richard Thaler

Behavioral economics

Richard Thaler studies economic decisions with psychological factors in view. His work helps frame hypotheses about preferences, self-control, and choice context.

Can the choice context help explain the gap between intention and behavior?
IN PRACTICE

Distinguish stated intentions from observed behavior and test hypotheses before recommending an intervention.

Richard Thaler — contributions to behavioral economics

02 / FROM FOUNDATIONS TO THE STUDY

The method needs
to leave a trail.

To assess a conclusion, you need to understand how it was produced. This structure guides the new SondaIntel experience.

  1. 01

    Decision and hypothesis

    Record what we want to understand, for whom, and in which context.

  2. 02

    Instrument and recruitment

    Define questions, participation criteria, and how people will be invited.

  3. 03

    Data and analysis

    Document processing, exclusions, chosen methods, and conditions of use.

  4. 04

    Interpretation and review

    Connect conclusions to evidence and state uncertainty, limitations, and required review.

  5. 05

    Publication and follow-up

    Present the assessment in context and record hypotheses for action in a new round.

03 / TRANSPARENCY IN DELIVERY

A useful conclusion
knows its limits.

The sample matters+

One hundred voluntary responses do not automatically represent all customers. Results must include recruitment sources, selection, and participation details.

Precision requires design+

Conventional margins of error and confidence levels should not automatically be assigned to opt-in samples.

Association does not establish causation+

A relationship between variables can guide investigation. Demonstrating the effect of an action requires an appropriate design.

Complexity needs a purpose+

A more sophisticated model only makes sense when it better answers the question and meets its conditions of use.

A HERITAGE THAT EVOLVES

SondaIntel evolves.
Its foundations remain.

SAES, SAGS, historical instruments, and analyses are part of the collection guiding this rebuild. Modernization requires preserving versions and examining each method’s application in new contexts.

The app demo uses fictional data, counts, proportions, and percentage-point differences. It does not yet run the advanced models presented in these foundations.

Explore the demo assessment