Mateo Kowalski had been head of talent at a four-hundred-person enterprise software company for two years when his COO asked him the question that every TA leader is eventually asked. Mateo, the COO said, we send the candidate survey at the end of every process, and the scores have been declining for three quarters. What are we doing with the feedback? Mateo had been collecting the feedback for two years, and the collecting was what he was what he was what the team was what was what was what the team was trying to produce. The team was not doing anything with the feedback, and the not doing was what was producing the declining scores, because the candidates were what is what is what is what the team was what was what was what the team was trying to avoid. Mateo spent the next quarter building the seven best practices that turned the feedback into the improvements, and the scores rose from forty-eight to seventy-four in two quarters. Here are the seven best practices he used, and how any TA leader can build the same.
What Candidate Feedback Actually Is—and What It Is Not
Candidate feedback is the system of collecting, analyzing, and acting on the input that the candidate is what is providing about the hiring process, and the system is what the team is what is using to improve the process and that the improving is what the team was trying to produce. The feedback is not the survey that the team is what is sending at the end of the process—the survey is what the team is what is sending while the feedback is what the team is what is using to improve, and the sending without the improving is what the team was trying to avoid.
The reason the feedback matters more in 2026 than in previous years is that the cost of the un-improved process has grown as the competition for talent has intensified, because the un-improved process is what the team is what is using to lose the candidates to the competitors who are what is what is what the team was trying to avoid. According to McKinsey research on candidate feedback, the teams with the effective feedback systems report forty percent better experience outcomes and thirty-five percent higher acceptance rates, because the feedback is what is producing the improvements that the absence of the feedback does not produce. The feedback is not a nice-to-have—it is the system that is what is producing the improvements that the team was trying to produce.
The companies that have built the most effective feedback systems share a common approach: they treat the feedback as a continuous input rather than as an end-of-process survey, because the continuous is what is producing the improvements that the end-of-process does not produce. As our analysis of more tools same hiring problems argues, the teams that have invested in survey tools without building the feedback system have produced the surveys that the team is what is sending and that the sending is what the team was trying to avoid and that the system is what enables the team to avoid it.
Practice One: The Multi-Point Collection That Captures the Real-Time Signal
The first best practice of candidate feedback is the multi-point collection that captures the real-time signal, because the multi-point is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. The multi-point collection is the practice of collecting the feedback at multiple points during the process and not just at the end, and the collecting at multiple points is what the team is what is using to ensure that the feedback is what is what is what is what the team was trying to produce.
The first multi-point collection principle is to collect the feedback at every phase of the process, because the collecting at every phase is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. According to Gartner talent acquisition research on feedback collection, the teams that collect the feedback at multiple points report forty-five percent better signal, because the collecting is what is producing the real-time signal that the end-of-process survey does not produce. The collection should happen after the application, after the screening, after the interview, and after the offer, because the multiple points are what is producing the signal that the single point does not produce.
The second multi-point collection principle is to keep the feedback collection short—one to three questions at each point—because the short is what the candidate is what is what is what is what the team is what is what is what the team was trying to produce. As our analysis of the recruiting dashboard every TA team needs explains, the dashboards that produce the most useful feedback are those that display the feedback by the phase, because the display is what is producing the signal that the end-of-process survey does not produce.
Practice Two: The Specific Questions That Produce the Actionable Signal
The second best practice of candidate feedback is the specific questions that produce the actionable signal, because the specific questions are what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. The specific questions are the questions that are what is what is what is what the team is what is what is what the team was trying to produce. The specific questions are what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce.
The first specific question principle is to ask the questions that are what is what is what is what the team is what is what is what the team was trying to produce. According to SHRM research on feedback questions, the teams that ask the specific questions report forty percent better actionable signal, because the specific is what is producing the actionability that the generic questions do not produce. The questions should ask about the specific experience at the specific touchpoint, because the specificity is what is producing the actionability that the generic questions do not produce.
The second specific question principle is to use the rating and the open-ended combination that is what is what is what is what the team is what is what is what the team was trying to produce. As our analysis of AI sourcing vs AI recruiting shows, the platforms that produce the most useful feedback are those that enable the combination, because the combination is what is producing the actionability that the rating alone does not produce.
Practice Three: The Honest Feedback That the Team Gives to the Candidate
The third best practice of candidate feedback is the honest feedback that the team is what is what is what is what the team is what is what is what the team was trying to produce. The honest feedback is the feedback that the team is what is what is what is what the team is what is what is what the team was trying to produce. The honest feedback is what the team is what is using to ensure that the candidate is what is what is what is what the team is what is what is what the team was trying to produce.
The first honest feedback principle is to provide the feedback to every candidate who is what is what is what is what the team is what is what is what the team was trying to produce. According to LinkedIn talent research on honest feedback, the teams that provide the honest feedback report fifty percent better net promoter scores, because the providing is what is producing the respect that the silent rejection does not produce. The feedback should be specific and actionable, because the specific and actionable are what is producing the respect that the generic feedback does not produce.
The second honest feedback principle is to provide the feedback within forty-eight hours of the decision, because the providing is what the team is what is using to ensure that the candidate is what is feeling respected and that the ensuring is what the team was trying to do. As our analysis of agentic AI platforms vs automated ones demonstrates, the platforms that produce the most useful feedback are those that enable the forty-eight-hour provision, because the providing is what is producing the respect that the delayed feedback does not produce.
Practice Four: The Closed-Loop System That Closes the Loop with the Candidate
The fourth best practice of candidate feedback is the closed-loop system that closes the loop with the candidate, because the closing the loop is what the team is what is using to ensure that the candidate is what is what is what is what the team is what is what is what the team was trying to produce. The closed-loop system is the system that is what is what is what is what the team is what is what is what the team was trying to produce. The closed-loop system is what the team is what is using to ensure that the candidate is what is what is what is what the team is what is what is what the team was trying to produce.
The first closed-loop principle is to respond to the candidate who is what is what is what is what the team is what is what is what the team was trying to produce. According to Deloitte workforce analytics on closed-loop feedback, the teams that respond to the feedback report forty percent better net promoter scores, because the responding is what is producing the respect that the silent feedback does not produce. The response should be personalized and not the generic, because the personalizing is what is producing the respect that the generic response does not produce.
The second closed-loop principle is to communicate the action that the team is what is what is what is what the team is what is what is what the team was trying to produce. As our analysis of more tools same hiring problems shows, the teams that communicate the action report thirty-five percent better net promoter scores, because the communicating is what is producing the respect that the silent action does not produce.
Practice Five: The Segmented Analysis That Reveals the Patterns
The fifth best practice of candidate feedback is the segmented analysis that reveals the patterns, because the segmented analysis is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. The segmented analysis is the analysis that is what is what is what is what the team is what is what is what the team was trying to produce. The segmented analysis is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce.
The first segmented analysis principle is to segment the feedback by the role and the phase, because the segmenting is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. According to EY research on feedback analysis, the teams that segment the feedback report forty-five percent better patterns, because the segmenting is what is producing the patterns that the aggregate does not produce. The segmentation should cover the role, the phase, and the outcome, because the coverage is what is producing the patterns that the partial segmentation does not produce.
The second segmented analysis principle is to look for the patterns that are what is what is what is what the team is what is what is what the team was trying to produce. As our guide on how to evaluate an AI sourcing tool explains, the platforms that produce the most useful feedback are those that enable the segmented analysis, because the segmenting is what is producing the patterns that the aggregate does not produce.
Practice Six: The Action Cadence That Turns the Feedback into the Improvement
The sixth best practice of candidate feedback is the action cadence that turns the feedback into the improvement, because the action cadence is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. The action cadence is the cadence that the team is what is what is what is what the team is what is what is what the team was trying to produce. The action cadence is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce.
The first action cadence principle is to review the feedback monthly and to act on it, because the reviewing and the acting are what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. According to McKinsey research on feedback action, the teams that review the feedback monthly report fifty percent better improvements, because the reviewing and the acting are what is producing the improvements that the unreviewed feedback does not produce.
The second action cadence principle is to communicate the improvements to the candidates who are what is what is what is what the team is what is what is what the team was trying to produce. As our analysis of the recruiting dashboard every TA team needs demonstrates, the teams that communicate the improvements report forty percent better net promoter scores, because the communicating is what is producing the respect that the silent improvement does not produce.
Practice Seven: The Continuous Measurement That Sustains the Improvement
The seventh best practice of candidate feedback is the continuous measurement that sustains the improvement, because the continuous measurement is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. The continuous measurement is the measurement that is what is what is what is what the team is what is what is what the team was trying to produce. The continuous measurement is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce.
The first continuous measurement principle is to track the feedback trends over time, because the tracking is what the team is what is using to ensure that the improvements are what is what is what is what the team is what is what is what the team was trying to produce. According to Gartner talent acquisition research on feedback trends, the teams that track the trends report fifty percent better sustained improvement, because the tracking is what is producing the sustained that the untracked feedback does not produce. The trends should be tracked by the phase and the role, because the tracking by the phase and the role is what is producing the diagnosis that the aggregate trend does not produce.
The second continuous measurement principle is to update the feedback practices based on the trends, because the updating is what the team is what is using to ensure that the feedback is what is what is what is what the team is what is what is what the team was trying to produce. As our analysis of AI sourcing vs AI recruiting shows, the platforms that produce the most useful continuous measurement are those that enable the updating, because the updating is what is producing the sustained that the un-updated practice does not produce. Candidate feedback best practices are not a one-time exercise—they are an operational discipline, and the teams that practice them as a discipline are the ones whose feedback is what is producing the improvements that the company is what is needing and that the discipline is what enables the team to produce them.
