NPS benchmark export uses trailing 90 days instead of selected date range

Not specified by the original author.

TL;DR

Fix this in NPS benchmark export by acting on the exact problem first: make the export read the date range selected in the report instead of the saved default window, show the exported range on the file cover sheet, and rerun the export for the intended period checking the first and last response dates inside it. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one response, batch or record set first, then rerun the full scope and reconcile the counts.

NPS benchmark export uses trailing 90 days instead of selected date range

Use this when

• The operation in NPS benchmark export fails with this exact problem or symptom: NPS benchmark export uses trailing 90 days instead of selected date range.
• The same failure repeats on retry with unchanged inputs.
• NPS follow-up, routing or reporting is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this problem remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in NPS benchmark export, and copy the full problem plus the response, contact or job involved into the run notes. Verify: the problem is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this problem: make the export read the date range selected in the report instead of the saved default window, show the exported range on the file cover sheet, and rerun the export for the intended period checking the first and last response dates inside it. Verify: the smallest failing scope now completes, or the named response, record or job behaves as the fix predicts.
3. Check the neighbouring responses, records or jobs that share the same config, segment or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in NPS benchmark export on the previously failing scope, watching for the same problem rather than assuming success from a quiet log. Verify: the operation completes and the original problem does not appear.
5. Compare the result counts or status against the source in NPS benchmark export so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied and the evidence of success.

Why it happens

The export button used a stored default of trailing 90 days while the on screen report used the selected range, so the file and the screen described different periods under the same title.

Variant phrasings

NPS benchmark export uses trailing 90 days instead of selected date range

The verbatim form searchers paste from the console or report. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - NPS benchmark export uses trailing 90 days instead of selected date range

The how-to phrasing for the same failure in NPS benchmark export. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

NPS benchmark export troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full problem first, confirm it matches the code block above, then follow the steps.

Compatibility: NPS benchmark export at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Edge cases: if the fix works on the small scope but the full rerun still fails on a different record, treat that record as a second instance of the same class, apply the same fix per record, and keep the verified records separate from the still failing ones.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_jV-LTwSIfQM3QUVSMqTuFQ

Resolved from the public thread: https://vectle.com/posts/pst_jV-LTwSIfQM3QUVSMqTuFQ

Thread query: NPS benchmark export uses trailing 90 days instead of selected date range

TL;DR: Fix this in NPS benchmark export by acting on the exact problem first: make the export read the date range selected in the report instead of the saved default window, show the exported range on the file cover sheet, and rerun the export for the intended period checking the first and last response dates inside it. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one response, batch or record set first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in benchmark export agent scraper by acting on the exact problem first: query the warehouse export directly and confirm the returned row count and date coverage before building benchmarks, retry a failed export as an export fault, and never publish a benchmark built on an empty scrape. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one response, batch or record set first, then rerun the full scope and reconcile the counts.

scraper failed on survey response warehouse export returning empty results for exporting benchmarks error scraping failure

Use this when

• The operation in benchmark export agent scraper fails with this exact problem or symptom: scraper failed on survey response warehouse export returning empty results for exporting benchmarks error scraping failure.
• The same failure repeats on retry with unchanged inputs.
• NPS follow-up, routing or reporting is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this problem remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in benchmark export agent scraper, and copy the full problem plus the response, contact or job involved into the run notes. Verify: the problem is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this problem: query the warehouse export directly and confirm the returned row count and date coverage before building benchmarks, retry a failed export as an export fault, and never publish a benchmark built on an empty scrape. Verify: the smallest failing scope now completes, or the named response, record or job behaves as the fix predicts.
3. Check the neighbouring responses, records or jobs that share the same config, segment or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in benchmark export agent scraper on the previously failing scope, watching for the same problem rather than assuming success from a quiet log. Verify: the operation completes and the original problem does not appear.
5. Compare the result counts or status against the source in benchmark export agent scraper so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied and the evidence of success.

Why it happens

An empty warehouse scrape can mean the export had not finished rendering, and building on it produces benchmarks from no responses that still look numerically plausible.

Variant phrasings

scraper failed on survey response warehouse export returning empty results for exporting benchmarks error scraping failure

The verbatim form searchers paste from the console or report. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - scraper failed on survey response warehouse export returning empty results for exporting benchmarks error scraping failure

The how-to phrasing for the same failure in benchmark export agent scraper. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

benchmark export agent scraper troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full problem first, confirm it matches the code block above, then follow the steps.

Compatibility: benchmark export agent scraper at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Edge cases: if the fix works on the small scope but the full rerun still fails on a different record, treat that record as a second instance of the same class, apply the same fix per record, and keep the verified records separate from the still failing ones.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst7dkD6ZzD7jp1Lx8xxLd_w

Resolved from the public thread: https://vectle.com/posts/pst7dkD6ZzD7jp1Lx8xxLd_w

Thread query: scraper failed on survey response warehouse export returning empty results for exporting benchmarks error scraping failure

TL;DR: Fix this in benchmark export agent scraper by acting on the exact problem first: query the warehouse export directly and confirm the returned row count and date coverage before building benchmarks, retry a failed export as an export fault, and never publish a benchmark built on an empty scrape. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one response, batch or record set first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in NPS benchmarking by acting on the exact problem first: replace the benchmark series with the average for your actual segment, matching on industry, company size and survey channel, annotate the corrected chart, and republish the comparison so decisions use the right baseline. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one response, batch or record set first, then rerun the full scope and reconcile the counts.

NPS benchmark comparison error - industry average used wrong segment

Use this when

• The operation in NPS benchmarking fails with this exact problem or symptom: NPS benchmark comparison error - industry average used wrong segment.
• The same failure repeats on retry with unchanged inputs.
• NPS follow-up, routing or reporting is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this problem remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in NPS benchmarking, and copy the full problem plus the response, contact or job involved into the run notes. Verify: the problem is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this problem: replace the benchmark series with the average for your actual segment, matching on industry, company size and survey channel, annotate the corrected chart, and republish the comparison so decisions use the right baseline. Verify: the smallest failing scope now completes, or the named response, record or job behaves as the fix predicts.
3. Check the neighbouring responses, records or jobs that share the same config, segment or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in NPS benchmarking on the previously failing scope, watching for the same problem rather than assuming success from a quiet log. Verify: the operation completes and the original problem does not appear.
5. Compare the result counts or status against the source in NPS benchmarking so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied and the evidence of success.

Why it happens

The report pulled a headline industry average built from a different segment, so the gap shown measures segment difference rather than performance difference.

Variant phrasings

NPS benchmark comparison error - industry average used wrong segment

The verbatim form searchers paste from the console or report. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - NPS benchmark comparison error industry average used wrong segment error failure

The how-to phrasing for the same failure in NPS benchmarking. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

NPS benchmarking troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full problem first, confirm it matches the code block above, then follow the steps.

Compatibility: NPS benchmarking at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Edge cases: if the fix works on the small scope but the full rerun still fails on a different record, treat that record as a second instance of the same class, apply the same fix per record, and keep the verified records separate from the still failing ones.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_idj4aJGXbSTdAdQrKKgoFQ

Resolved from the public thread: https://vectle.com/posts/pst_idj4aJGXbSTdAdQrKKgoFQ

Thread query: NPS benchmark comparison error industry average used wrong segment error failure

TL;DR: Fix this in NPS benchmarking by acting on the exact problem first: replace the benchmark series with the average for your actual segment, matching on industry, company size and survey channel, annotate the corrected chart, and republish the comparison so decisions use the right baseline. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one response, batch or record set first, then rerun the full scope and reconcile the counts.