The Confirmation Nudge: Prompts to Change or Confirm Initial Preferences Steer Consumer Choice
Bibliographic record
Abstract
Abstract Across two field experiments and several preregistered lab experiments, we demonstrate that confirmation nudges, which ask consumers whether they would like to confirm or change their initial choice, impact choice. First, consumers navigating a subscription company’s smartphone app were randomized to a control or confirmation nudge condition, which asked them to either confirm their initial choice or switch to an annual subscription. Confirmation nudges increased subscribers’ choice of the annual subscription by over 8 percentage points—an effect size similar to default effects tested by the same company. In experiment 2, conducted by a jewelry retailer, confirmation nudges had countervailing effects, increasing purchases of a nudged service plan add-on but decreasing originally planned jewelry purchases likely because it added a step and thus frictions to the purchase process. Confirmation nudges had larger effects when nudged options were desirable and among consumers who would benefit from the nudge (experiments 3 and 4). However, they were perceived as more manipulative than comparison conditions (experiment 5). We suggest that confirmation nudges undo tendencies to focus on initially preferred options, shifting attention toward alternatives relative to control conditions. Consistent with this, confirmation nudges were especially effective when the wording of the confirmation prompt focused on the “switch” option.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".