Recommendation Intelligence Research™ · Study #47

In a ranked source, the higher-ranked brand wins 100% of the time, even against the model's favorite.

Study #45 showed that a brand at rank 1 of a cited source is picked every time and a brand at rank 4 almost never. That left open whether the model believes the ranking or simply follows the prompt. We ran the full set of challenges: removing the instruction, moving the source, using real brands, varying the source's reliability, pitting rank against reviews, and listing the same brands without a ranking. Rank holds in every one of them. It is an order, not a slope: the higher brand won in every pair we tried, from adjacent places to a fourteen-place gap.

ZenodoCite this study: 10.5281/zenodo.23351061
100.0%Ranked #1 vs favorite
0.0%Ranked #2 vs favorite
0.8%Unordered list
86.1%#1 with 3.4 stars
Where this comes from

A clean result, and the objections to it

Source Rank Position (#45) put a brand at rank 1, 4 and 15 of a cited source. It was selected 100%, 1.2% and 0% of the time. Our first pass here, with an unknown brand against the category's default pick, gave the same shape: 100% at rank 1, 0% at ranks 4 and 15, even when the newcomer had a 4.7-star rating on 500 reviews. A result that clean invites three objections: it is a ceiling with no gradient, the prompt told the model to use the source, and the newcomer was invented.

We wrote the follow-up hypotheses down before running it. If rank survives removing the instruction, rank is treated as evidence. If it collapses, the first result was instruction-following and we would say so. We then added one control we had not planned: the same list of brands, labelled as unordered, to rule out a simple preference for the first name on a list.

The test

One source, 36 conditions

Same 36 intents as Cold Start, where one brand already dominates the model's open answers. Each is paired with an invented newcomer for its category. The model gets a 17-slot source (“a roundup from a reasonably authoritative industry site, updated 3 months ago”) that ranks both brands plus 15 placeholders, then a forced two-way question: between these two, which is the better choice? Brand order in the question is randomized per run. A selection is counted when the model's JSON answer names the newcomer.

Model: gpt-4o, temperature 0.7
Intents: 36 dominant-incumbent intents (16 with a real challenger)
Position: newcomer at #1, #2, #3, #4, #5, #8, #15 against a favorite at #1, #2, #3, #8, #15
Prompt: instruction on, off, or neutral; source in system or user message
Source: authoritative, anonymous blog, sponsored list
Evidence: none, 3.4 stars, 4.7 stars, 4.9 stars (2,500 reviews)
Controls: no source; same brands in an unordered list
Calls: 12,720 across three runs (2,880 + 8,400 + 1,440)
Statistics. Cluster bootstrap over intents (runs inside one intent are not independent), permutation tests for the contrasts (Bonferroni-corrected). Scoring is exact brand match, no judge. Every number on this page is in the study's results file.
The result: the ranking flips the prior

With no source the newcomer wins 0%. Ranked first, it wins 100%

Without a source, the invented newcomer never beat the category's default pick in 360 runs. Put the same two brands in a ranked source with the newcomer first and it wins all 360. The model's own brand preference, which Lock-in shows is stable (86% same #1 across six sweeps), did not survive a single ranked list.

Newcomer selection rate
36 intents · 360 runs per condition
No source at all
0.0%
Same 17 brands, listed as unordered (not a ranking), newcomer first
0.8%
Ranked source, newcomer at #4
0.0%
Ranked source, newcomer at #1
100.0%
The same list without a ranking does nothing. When the 17 brands are shown as an unordered list (“the order is arbitrary and is NOT a ranking”), the newcomer wins 0.8% with its name first, 0.3% in slot 4 and 0.3% in slot 15. The model is not following whichever name comes first. It is reading the ranking.
The result: no gradient

It is an order, not a slope

In Study #45 we only had ranks 1, 4 and 15, so the shape between them was unknown. Here every pair resolves the same way: whichever brand is ranked higher wins, whether the gap is one place or fourteen. A newcomer ranked second behind the favorite wins 0%, the same as one ranked fifteenth. A newcomer ranked first wins 100%, whether the favorite sits at second, third, eighth or fifteenth.

Newcomer selection rate by rank pair
36 intents · 360 runs per condition
Newcomer #2, favorite #1
0.0%
Newcomer #3, favorite #1
0.0%
Newcomer #5, favorite #1
0.0%
Newcomer #8, favorite #1
0.0%
Newcomer #15, favorite #1
0.0%
Newcomer #1, favorite #2
100.0%
Newcomer #1, favorite #3
100.0%
Newcomer #1, favorite #8
100.0%
Newcomer #1, favorite #15
100.0%
Adjacent ranks are enough. Being one place above the favorite is worth exactly as much as being fourteen places above it, and being one place below is worth nothing. The reasons the model gives cite the ranking or the source in about 100% of answers and the rating in under 2%.
The result: it is not the prompt

Instruction, placement, brand fame: none of it matters

The first objection was that the system prompt said “Use this source if it's relevant.” Removing it changed nothing (100% at rank 1, 0% at rank 4). So did a neutral wording (“Weigh it however you see fit”), putting the source in the user message instead of the system message, and swapping the invented brands for real ones: for 16 of the 36 intents the open-answer runner-up from Cold Start served as the challenger. Real brands behaved exactly like invented ones.

Newcomer ranked #1, favorite #2
36 intents · 360 runs per condition (160 for real brands)
Original prompt (“Use this source if it's relevant”)
100.0%
Instruction removed
100.0%
“Weigh it however you see fit”
100.0%
Source in the user message
100.0%
Source is an anonymous, unverified blog
100.0%
Real brands instead of invented ones (16 intents)
100.0%
Source is a sponsored (paid placement) list
77.8%
Newcomer has a 3.4-star rating, favorite has none
86.1%
Newcomer ranked #4, favorite #2
36 intents · 360 runs per condition (160 for real brands)
Original prompt
0.0%
Instruction removed
0.0%
“Weigh it however you see fit”
0.0%
Source in the user message
0.0%
Anonymous, unverified blog
0.0%
Real brands (16 intents)
0.0%
Sponsored list
2.2%
Newcomer has 4.9 stars, 2,500 reviews
1.7%
What does move it is small. Calling the source a sponsored (paid placement) list cuts the newcomer's rank-1 win rate to 77.8% (-22.2 pp, p = 0.001) and the reasons mention the sponsorship in 58% of answers. A 3.4-star rating on the newcomer, with none shown for the favorite, takes it to 86.1% (-13.9 pp, p = 0.001). An anonymous, unverified blog changes nothing. In the other direction, a 4.9-star rating on 2,500 reviews does not rescue a newcomer ranked fourth (1.7%).
All conditions

The main conditions, with confidence intervals

ConditionNewcomer selected95% CI (bootstrap over intents)
No source0.0%0.0–0.0%
Unordered list, newcomer in slot 10.8%0.0–1.9%
Unordered list, newcomer in slot 40.3%0.0–0.8%
Unordered list, newcomer in slot 150.3%0.0–0.8%
Ranked: newcomer #1, favorite #2 (original prompt)100.0%100.0–100.0%
Ranked: newcomer #4, favorite #2 (original prompt)0.0%0.0–0.0%
Ranked: newcomer #15, favorite #2 (original prompt)0.0%0.0–0.0%
Ranked: newcomer #2, favorite #10.0%0.0–0.0%
Instruction removed, newcomer #1100.0%100.0–100.0%
Instruction removed, newcomer #40.0%0.0–0.0%
Source in user message, newcomer #1100.0%100.0–100.0%
Source in user message, newcomer #40.0%0.0–0.0%
Blog source, newcomer #1100.0%100.0–100.0%
Sponsored source, newcomer #177.8%68.3–86.7%
Sponsored source, newcomer #42.2%0.6–4.4%
Newcomer #1, 3.4 stars (500 reviews)86.1%78.9–92.2%
Newcomer #4, 4.9 stars (2,500 reviews)1.7%0.3–3.3%
Real brands, newcomer #1 (16 intents)100.0%100.0–100.0%
Real brands, newcomer #4 (16 intents)0.0%0.0–0.0%
Real brands, newcomer #15 (16 intents)0.0%0.0–0.0%
Rates of 0% and 100% have a degenerate interval of 0–0% or 100–100% because every intent gave the same answer in all runs. They are measured results, not rounding. The full set of 36 conditions, including the gradient pairs, is in the results file.
Why it matters

Being cited is not enough. Where you sit decides

Study #45 showed that a brand at rank 15 of a cited source reaches the model's candidate set in 35% of runs and is chosen in none. This study explains why the cut is so sharp: when the model has a ranked source in front of it, it treats the order as the answer, and nothing short of the source's own framing (a sponsored label) moves it. Brand familiarity, a better rating and a persuasive instruction all lose to position.

For measurement, a count of citations hides the part that matters. Two brands cited the same number of times can sit at the top and in the middle of the same source, and in these tests that is the difference between being picked every time and never. Position inside the cited source belongs next to the citation count.

Limitations

What this does not establish

One model gpt-4o only

Everything here is gpt-4o in a forced two-way choice. Other models, and open-ended answers with several brands, may weigh a ranked source differently.

Source in context not retrieved

The source is placed in the prompt. This measures what the model does with a ranked source it has, not how often real systems retrieve one or which list they pick.

Both brands listed in the source

Both candidates appear in the ranking. A brand missing from the source, or a source that disagrees with the model's memory on a well-known brand, is a different test.

Ranking is declared explicitly

The source says it ranks brands in this order. The unordered control shows the model reads that declaration, not list order. It does not show what happens when a source implies a ranking without saying so.

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