Consumer Decision-Making Models in Marketing

Consumer decision-making models seek to explain how individuals recognise need states, gather and process information, evaluate alternatives and arrive at purchase decisions, before assessing satisfaction post-purchase. Traditional frameworks assume a largely rational actor who optimises utility by weighing costs and benefits across product attributes. Behavioural and cognitive approaches have since enriched this perspective by incorporating bounded rationality, heuristics, emotion, social influence and contextual factors. Contemporary models often adopt a dual-process view, distinguishing deliberate, analytical thinking from fast, intuitive judgments. Non-compensatory rules such as lexicographic ordering or elimination-by-aspects operate alongside compensatory strategies that trade off high performance on some attributes against lower performance on others. Recent advances combine discrete-choice econometric models with psychological constructs, neuroeconomic evidence and machine-learning techniques to capture heterogeneity in preferences and decision processes. This integrated perspective underpins personalised marketing, dynamic pricing, product design and socially responsible branding, with growing attention to digital touchpoints and sustainability considerations.

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Technical terms

Compensatory decision strategy: A rule whereby a poor score on one attribute can be offset by a strong score on another, allowing trade-offs among features.

Non-compensatory decision rule: A heuristic that eliminates options failing to meet critical criteria, without trade-offs among attributes.

Two-stage decision process: A framework where consumers first screen out unacceptable options and then choose from the remaining set using a compensatory rule.

Attribute alignability: The ease with which features of competing options can be directly compared, influencing reliance on alignable versus non-alignable attributes.

Multinomial logit model: An econometric model of discrete choice that estimates the probability of selecting among multiple alternatives based on the exponential transformation of utility.

Choice-based conjoint analysis: A survey-based method that infers consumer preference structures by observing choices among systematically varied product profiles.

References

1. Analyzing learning effects in the newsvendor model by probabilistic methods. Decision Analytics Journal (2023).
2. The Effect of Attribute Alignability on Product Purchase: The Moderating Role of Product Familiarity and Self-Construal. Frontiers in Psychology (2021).
3. Too much, too little? A CBC approach accounting for screening from both sides. Journal of Choice Modelling (2024).