The effect of matching strategies and advertising performance: the roles of perceived goal progress and customer search behaviors
Bibliographic record
Abstract
Purpose The search advertising market continues to grow rapidly, making it increasingly important for companies to choose the appropriate matching strategy to advertise their products. This study aims to examine the impact of matching strategies on search advertising performance and how consumer search behaviors moderate the relationship. Design/methodology/approach This study employs a mixed-method approach. An experiment is carried out to examine the effect of matching strategies and the mediating effect of perceived goal progress. Subsequently, using secondary data collected from a car loan company, we conduct ordinary least squares regressions to explore the impact of matching strategy and the moderating effect of consumer search behaviors. Robustness tests are conducted, including alternative model specifications, three-stage least squares model and entropy balance matching. Findings The empirical results indicate that employing an exact matching strategy contributes to improved advertising performance and perceived goal progress plays a mediating role. Moreover, customer search behavior plays an important role in this relationship. Specifically, the positive effect of the exact matching strategy is weakened when consumers conduct searches using branded keywords, mobile devices and on weekdays. Practical implications Our study provides guidance for marketing managers on designing search advertising matching strategy to better tailor customers’ search states, thus enhancing advertising performance. Originality/value The study offers a novel contribution to the well-established realm of interactive marketing, specifically in search advertising, by examining the impact of exact matching strategies from the perspective of consumer search behaviors and proposing the mediating role of perceived goal progress underlying the relationship between matching strategies and search advertising performance.
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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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".