The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
engine: string
snapshotDate: timestamp[s]
captureCount: int64
aioTriggered: int64
note: string
captures: list<item: struct<q: string, query: string, aioTriggered: bool, tools: list<item: string>, top: stri (... 30 chars omitted)
child 0, item: struct<q: string, query: string, aioTriggered: bool, tools: list<item: string>, top: string, doms: l (... 18 chars omitted)
child 0, q: string
child 1, query: string
child 2, aioTriggered: bool
child 3, tools: list<item: string>
child 0, item: string
child 4, top: string
child 5, doms: list<item: string>
child 0, item: string
sourceCaptureNote: string
engineLabel: string
to
{'engine': Value('string'), 'engineLabel': Value('string'), 'snapshotDate': Value('timestamp[s]'), 'captureCount': Value('int64'), 'sourceCaptureNote': Value('string'), 'captures': List({'q': Value('string'), 'query': Value('string'), 'tools': List(Value('string')), 'top': Value('string')})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
engine: string
snapshotDate: timestamp[s]
captureCount: int64
aioTriggered: int64
note: string
captures: list<item: struct<q: string, query: string, aioTriggered: bool, tools: list<item: string>, top: stri (... 30 chars omitted)
child 0, item: struct<q: string, query: string, aioTriggered: bool, tools: list<item: string>, top: string, doms: l (... 18 chars omitted)
child 0, q: string
child 1, query: string
child 2, aioTriggered: bool
child 3, tools: list<item: string>
child 0, item: string
child 4, top: string
child 5, doms: list<item: string>
child 0, item: string
sourceCaptureNote: string
engineLabel: string
to
{'engine': Value('string'), 'engineLabel': Value('string'), 'snapshotDate': Value('timestamp[s]'), 'captureCount': Value('int64'), 'sourceCaptureNote': Value('string'), 'captures': List({'q': Value('string'), 'query': Value('string'), 'tools': List(Value('string')), 'top': Value('string')})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Who AI Recommends: GTM Tool & Source Citations Across ChatGPT, Perplexity & Google AI Overviews (2026)
An original measurement of which GTM (go-to-market) tools AI answer engines recommend, and which sources they cite, captured across three engines. A primary-source dataset for studying generative-engine optimization (GEO), AI-search citation behavior, and answer-engine source selection.
- Snapshot date: 2026-06-07 (AI answers are volatile; this is a dated snapshot. Re-run the published protocol to reproduce.)
- License: CC-BY 4.0
- DOI: 10.5281/zenodo.20632768
- Source / companion study: https://lucreya.com/research/who-ai-recommends-gtm-2026/
- Companion dataset (the 30-tool GTM index): https://lucreya.com/research/ai-gtm-tools-2026/
- Author: Vincent Wesley Couey (ORCID 0009-0005-6869-308X) · published via Lucreya (lucreya.com), part of the Lattice research network.
What's in it
who-ai-recommends-gtm-2026.csv — one row per (query × engine), with the tools each engine recommended (ranked) and, for Perplexity, the full cited source list.
| Column | Description |
|---|---|
query_id |
Stable ID for the buying-intent query |
vertical |
marketing / seo-geo / sales |
type |
query type (category, comparison, etc.) |
query |
the exact prompt submitted |
engine |
perplexity / chatgpt / google_aio |
top_tool |
the first tool named in the answer |
tools_recommended |
pipe-delimited, in the order named |
perplexity_source_count |
number of sources Perplexity cited (Perplexity only) |
perplexity_sources |
pipe-delimited cited domains (Perplexity only) |
data.json carries the full structured methodology + headline findings; protocol.json is the reproducible capture protocol; the _captures-*.json files are the raw per-engine captures.
Method (summary)
20 GTM buying-intent queries (derived from a 30-tool GTM-tools taxonomy spanning marketing, seo-geo, and sales) were each submitted to three AI answer engines — Perplexity (default web search), ChatGPT (web-search enabled), and Google AI Overviews — for 60 AI answers captured and 162 Perplexity citations logged. For each answer we recorded the tools named (in order) and, for Perplexity (which exposes a native numbered source list), the full cited-source set. Source-type classification was done from domain signatures. Full method in data.json.
Headline finding
Reddit was cited in 15 of the 20 Perplexity answers (75%), the single most-cited source domain. (See data.json for the complete findings.)
Citation
Couey, V. W. (2026). Who AI Recommends: GTM Tool and Source Citations Across ChatGPT, Perplexity, and Google AI Overviews (2026) [Data set]. Lucreya. https://doi.org/10.5281/zenodo.20632768
CC-BY 4.0 — free to use with attribution. Original measurement; AI engine answers are volatile, so treat this as a dated snapshot and re-run the protocol to reproduce.
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