(I'm) Happy to Help (You): The Impact of Personal Pronoun Use in Customer–Firm Interactions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In responding to customer questions or complaints, should marketing agents linguistically “put the customer first” by using certain personal pronouns? Customer orientation theory, managerial literature, and surveys of managers, customer service representatives, and consumers suggest that firm agents should emphasize how “we” (the firm) serve “you” (the customer), while de-emphasizing “I” (the agent) in these customer–firm interactions. The authors find evidence of this language pattern in use at over 40 firms. However, they theorize and demonstrate that these personal pronoun emphases are often suboptimal. Five studies using lab experiments and field data reveal that firm agents who refer to themselves using “I” rather than “we” pronouns increase customers’ perceptions that the agent feels and acts on their behalf. In turn, these positive perceptions of empathy and agency lead to increased customer satisfaction, purchase intentions, and purchase behavior. Furthermore, the authors find that customer-referencing “you” pronouns have little impact on these outcomes and can sometimes have negative consequences. These findings enhance understanding of how, when, and why language use affects social perception and behavior and provide valuable insights for marketers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.035 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it