Each observed question shape has its own leaderboard page.
Machine Relations Index
Observed shapes6 Published6 Collecting0 ReleaseNovember 5, 2026
Physical Consumer Products · Machine Relations Index category
Which sources AI engines cite for Physical Consumer Products questions
Editorial publications earn 77.0% of classified citations in Physical Consumer Products answers (621 of 806), as of November 5, 2026.
In the November 2026 release of the Machine Relations Index, these are the sources AI answer engines cited most often for each of the 6 Physical Consumer Products question shapes, each ranked on that shape's own observed runs. This category has 6 observed question-shape segments in the current public release. Each segment keeps its own observed-run denominator and dates; this page does not average rates across shapes. Observed runs are answer runs, not questions: every segment repeats a small set of distinct questions across engines and dates, so a run count is not a count of independent questions.
Top sources by question shape
The sources engines cite most, shape by shape
A rate is the share of the shape's observed answer runs that cited the source; rank is the source's place on that shape's full leaderboard.Best tools
Example pattern: best physical consumer products tools. 122 observed runs across 8 dates.
| Rank | Source | Source role | Citation rate | Cited runs |
|---|---|---|---|---|
| #1 of 229 | Tom's Guide | Editorial publication | 23.77% | 29 of 122 |
| #2 of 229 | rtings.com | Other observed source | 18.03% | 22 of 122 |
| #3 of 229 | Forbes | Editorial publication | 15.57% | 19 of 122 |
| #4 of 229 | TechRadar | Editorial publication | 14.75% | 18 of 122 |
| #5 of 229 | Yahoo News | Editorial publication | 13.93% | 17 of 122 |
How buyers choose
Example pattern: how to choose physical consumer products tools. 129 observed runs across 8 dates.
| Rank | Source | Source role | Citation rate | Cited runs |
|---|---|---|---|---|
| #1 of 188 | rtings.com | Other observed source | 13.18% | 17 of 129 |
| #2 of 188 | blueair.com | Other observed source | 10.85% | 14 of 129 |
| #3 of 188 | sylvane.com | Other observed source | 10.08% | 13 of 129 |
| #4 of 188 | daikin.co.uk | Other observed source | 8.53% | 11 of 129 |
| #5 of 188 | homeairqualitylab.com | Other observed source | 8.53% | 11 of 129 |
Is it worth it
Example pattern: is physical consumer products software worth it. 128 observed runs across 8 dates.
| Rank | Source | Source role | Citation rate | Cited runs |
|---|---|---|---|---|
| #1 of 168 | Tom's Guide | Editorial publication | 19.53% | 25 of 128 |
| #2 of 168 | Good Housekeeping | Editorial publication | 14.84% | 19 of 128 |
| #3 of 168 | YouTube (only pages not mapped to a channel or publication) | Search or media platform | 12.50% | 16 of 128 |
| #4 of 168 | ecovacs.com | Other observed source | 11.72% | 15 of 128 |
| #5 of 168 | choice.com.au | Other observed source | 10.16% | 13 of 128 |
Problem-first research
Example pattern: how to solve physical consumer products problems. 94 observed runs across 7 dates.
| Rank | Source | Source role | Citation rate | Cited runs |
|---|---|---|---|---|
| #1 of 138 | YouTube (only pages not mapped to a channel or publication) | Search or media platform | 19.15% | 18 of 94 |
| #2 of 138 | clivecoffee.com | Other observed source | 12.77% | 12 of 94 |
| #3 of 138 | kitchenaid.com | Other observed source | 10.64% | 10 of 94 |
| #4 of 138 | merakitech.com | Other observed source | 10.64% | 10 of 94 |
| #5 of 138 | myhomebarista.com | Other observed source | 8.51% | 8 of 94 |
Top lists
Example pattern: top physical consumer products platforms. 96 observed runs across 7 dates.
| Rank | Source | Source role | Citation rate | Cited runs |
|---|---|---|---|---|
| #1 of 222 | Consumer Reports | Editorial publication | 18.75% | 18 of 96 |
| #2 of 222 | The New York Times | Editorial publication | 18.75% | 18 of 96 |
| #3 of 222 | thisoldhouse.com | Other observed source | 13.54% | 13 of 96 |
| #4 of 222 | Garage Tested | Editorial publication | 12.50% | 12 of 96 |
| #5 of 222 | hgtv.com | Other observed source | 12.50% | 12 of 96 |
Comparisons
Example pattern: physical consumer products platform A vs B. 96 observed runs across 7 dates.
| Rank | Source | Source role | Citation rate | Cited runs |
|---|---|---|---|---|
| #1 of 107 | YouTube (only pages not mapped to a channel or publication) | Search or media platform | 22.92% | 22 of 96 |
| #2 of 107 | mattressnerd.com | Other observed source | 21.88% | 21 of 96 |
| #3 of 107 | madeincookware.com | Other observed source | 19.79% | 19 of 96 |
| #4 of 107 | Mattress Clarity | Editorial publication | 19.79% | 19 of 96 |
| #5 of 107 | casper.com | Other observed source | 18.75% | 18 of 96 |
Published segments met the release evidence floor.
Collecting segments expose sample progress, not mature leaderboards.
Methodology v2.1.
Question shapes
Separate denominators by segment
| Question shape | State | Observed runs | Distinct questions | Run dates | Distinct cited domains | Canonical segment |
|---|---|---|---|---|---|---|
| Best tools | Published | 122 | 7 (5 paraphrase groups) | 8 | 229 | Open leaderboard |
| How buyers choose | Published | 129 | 7 (5 paraphrase groups) | 8 | 188 | Open leaderboard |
| Is it worth it | Published | 128 | 7 (5 paraphrase groups) | 8 | 168 | Open leaderboard |
| Problem-first research | Published | 94 | 7 (5 paraphrase groups) | 7 | 138 | Open leaderboard |
| Top lists | Published | 96 | 7 (5 paraphrase groups) | 7 | 222 | Open leaderboard |
| Comparisons | Published | 96 | 7 (5 paraphrase groups) | 7 | 107 | Open leaderboard |
By answer engine
Whole-window rates on each engine
Each link ranks sources with a published Physical Consumer Products segment by that source's citation rate on one engine across the whole window. It is not a rate inside Physical Consumer Products alone. A collecting engine has no published ranking for this category.Cite this
Citation
Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. Physical Consumer Products, observed Machine Relations Index category, 2026-05-10 to 2026-11-05. Release mri_score_v2.1+2026-11-05+66c560c07279. https://machinerelations.ai/index/categories/physical-consumer. CC BY 4.0.APA
Parrott, J. (2026). Physical Consumer Products in the Machine Relations Index (Version mri_score_v2.1+2026-11-05+66c560c07279) [Data set]. Machine Relations Research. https://machinerelations.ai/index/categories/physical-consumer https://doi.org/10.5281/zenodo.23652423BibTeX
@misc{parrott2026mriphysicalconsumer,
author = {Parrott, Jaxon},
title = {Physical Consumer Products in the Machine Relations Index},
year = {2026},
version = {mri\_score\_v2.1+2026-11-05+66c560c07279},
publisher = {Machine Relations Research},
url = {https://machinerelations.ai/index/categories/physical-consumer},
doi = {10.5281/zenodo.23652423},
license = {CC-BY-4.0},
note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}Release and boundary
No pooled category score
Published November 5, 2026. The observation window runs May 10, 2026 to November 5, 2026. Methodology v2.1.
Use the data
curl -fsSL "https://machinerelations.ai/data/machine-relations-index.json" -o machine-relations-index.json
curl -fsSL "https://machinerelations.ai/data/mri-release-manifest.json" -o mri-release-manifest.json
curl -fsSL "https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv" -o domains.csv
curl -fsSL -L "https://doi.org/10.5281/zenodo.23652423" -o mri-zenodo.htmlimport json
from urllib.request import urlopen
index_url = "https://machinerelations.ai/data/machine-relations-index.json"
with urlopen(index_url) as response:
index = json.load(response)
print(index["generated"], index["total_domains"])This page is a directory of observed segments. A domain's overall citation rate is not a category rate, and MRI does not publish an averaged category score in this slice.
Physical Consumer Products buyers on AuthorityTech’s publication intelligence is a downstream practitioner projection of these segments. It is not source evidence, citation provenance, or an identity link for the neutral dataset.