An analysis of the impact of implementing a new Interactive Voice Response system (IVR) on client experience in the Canadian banking industry
Bibliographic record
Abstract
<p>Banks are constantly competing to find new ways to satisfy clients and meet their growing, heterogenous needs. Clients can access round the clock banking services worldwide. One way to access information is through Interactive Voice Response (IVR) systems. This research is an analysis of the process of implementing an IVR system and the impact on client experience using the case study of a Canadian bank. The research question is: “What is the impact of an IVR system upgrade on client experience in the Canadian banking industry?” The Productivity Paradox and the Unified Theory of Acceptance and Use of Technology model (UTAUT) are leveraged and a thematic analysis of the feedback provided from Net Promoter Score (NPS) surveys is done. The results show that although the IVR system can be an attractive automation interface for clients, there are many unanswered concerns about customer satisfaction as demonstrated by NPS feedback.</p>
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".