How People Live and Spend

How people spend money follows predictable patterns. Spending style, brand loyalty, purchase motivation, and impulse buying all have documented relationships with personality traits. Research on the tightwad-spendthrift spectrum¹ established that spending pain (the discomfort of parting with money) varies across individuals in stable, measurable ways. Other work on maximizing versus satisficing² shows that some people compulsively comparison-shop while others make quick, "good enough" decisions.

Brand loyalty is linked to personality dimensions like extraversion and openness.³ Compulsive buying behavior follows patterns related to neuroticism and self-esteem.⁴ Every one of these connections has been replicated in peer-reviewed research.

PreFlight derives consumer traits from upstream personality and demographic factors. This means the spending style of a generated profile is consistent with their personality, income, and age, because in real people, these things are connected. Consumer behavior data from large-scale surveys⁵⁶ provides the empirical baselines that anchor these derivations.

Financial behavior is one of the most predictive behavioral domains for audience modeling. Savings behavior, debt attitudes, investment style, and financial stress shape purchase capacity, brand preference, messaging receptivity, and product category interest.

Research from large-scale household financial surveys⁷⁸ provides the empirical foundation for financial modeling. Financial capability data from large-scale national studies⁹ adds depth on financial literacy, confidence, and planning behavior.

The personality-finance connection is well-documented. Research on personality and financial outcomes¹⁰ shows that conscientiousness predicts savings behavior, extraversion correlates with lower savings rates,¹¹ and neuroticism predicts financial stress. Investment style varies with personality in ways that a study of over 3,000 investors¹² found to be both significant and consistent. PreFlight models these interdependencies rather than treating financial behavior as a set of independent variables.

Health behaviors predict spending patterns, media consumption, and brand affinity at a level demographics will never reach. Someone who exercises daily, tracks their sleep, and buys organic food is a fundamentally different audience than someone of the same age and income who does none of those things.

The personality-health link is one of the most robust findings in behavioral science. A meta-analysis of conscientiousness and health behaviors¹³ found consistent effects across dozens of health-related outcomes. Exercise frequency is predicted by personality traits¹⁴¹⁵ with effect sizes large enough to matter for audience targeting. Dietary patterns,¹⁶ sleep quality,¹⁷ and mental wellness openness¹⁸ all connect back to the same personality infrastructure.

National health surveys tracking hundreds of thousands of respondents annually¹⁹ provide the population-level baselines. PreFlight layers personality-driven adjustments on top of these baselines to produce health profiles that reflect both the demographic reality and the psychological drivers.

Life events are the highest-leverage moments in consumer behavior. People who recently moved, changed jobs, had a child, or experienced a financial shock are in fundamentally different decision-making states than people in stable periods. These windows of change are when brand relationships form or break, purchase categories shift, and messaging receptivity spikes.

PreFlight models life events probabilistically based on age, income, life stage, and geography. Migration data,²⁰ household financial surveys,⁷ and demographic research inform the likelihood that a given profile is currently experiencing a major life transition. These events introduce temporary behavioral shifts that override baseline personality traits, and the model accounts for that interaction.