AI Citations series · No. 5 · the drift report

The Reddit collapse.

Fifteen days ago, Reddit appeared in 87% of Perplexity's answers to our 39 buyer questions — the most inevitable source we had ever measured. We re-ran the identical questions through the identical pipeline. It's 18%.

87%18% answers citing Reddit · byte-identical 39 questions · July 1 → July 16, 2026 · Perplexity

39 identical questions · 15 days apart · same engines, prompts, gateway, extraction · source-level figures are Perplexity only

79%
of questions changed their single top-cited source
31 of 39 · Perplexity
25%
Perplexity's brand-list overlap with its own answers from 15 days ago
ChatGPT 37% · Gemini 38%
59%
all-3-engine agreement — structurally unchanged
was 56% · all 3 engines
2.0%
Reddit's share of all citations now
was 10.4%
How controlled is this comparison? The 39 questions are byte-identical (mechanically enforced), same three engines and model ids, same system prompt and locale, same gateway, same counting method as report No. 2. One honest caveat: both runs pass through the same API gateway, so we measure the identical pipeline's behavior — we can't fully apportion the change between the engine and its citation passthrough. Either way, nothing on our side changed.
Finding 01

The collapse — with its controls

Only seven questions cited Reddit both times. And the two controls say this is Reddit-specific, not a citation drought: answers actually got richer (8.4 → 9.1 cited domains per answer), and YouTube barely moved.

Set A — identical 39 questionsJuly 1July 16
Answers citing Reddit34 / 39 = 87%7 / 39 = 18%
Reddit's share of all citations10.4%2.0%
Answers citing YouTube (control)15 / 39 = 38%14 / 39 = 36%
Cited domains per answer (control)8.49.1
Finding 02

Where the citations went

The hole Reddit left was filled — largely by editorial and listicle publishers. Community corroboration was swapped for edited, publisher-shaped pages.

Most-cited domains on the identical 39 questions
citation counts, Set A · Perplexity only
reddit.com — July 1
34
reddit.com — July 16
7
youtube.com — July 16
14
forbes.com — July 16
7
designrush.com — July 16
6
goodhousekeeping.com — July 16
6
0bars scaled to 39 questions39

If that direction holds, the pool got more winnable by published pages — which is most of what a brand can actually control — and less dependent on being talked about in threads.

Finding 03

It isn't just Reddit. Everything churns.

The single top-cited source changed on 31 of 39 questions (79%) in fifteen days. And at the brand level, each engine barely agrees with itself across the fortnight:

EngineOverlap with its own July 1 brand list
Perplexity25%
ChatGPT37%
Gemini38%
For scale: two different engines, same day7.5%

"Your brand ranks on ChatGPT" is a statement with a half-life measured in days.

Finding 04 · the counterweight

The rules are stable. The winners are not.

While the contents shuffled wholesale, the shape of the system did not move:

Structural metric — Set AJuly 1July 16
All 3 engines shared ≥1 pick56%59%
At least 2 engines shared ≥1 pick90%87%
Full-list overlap (mean Jaccard)7.2%7.5%

Every structural claim this series has published survived the fortnight. Every source-specific fact was perishable. That asymmetry is the strategy: optimize for the structure — be citable, be structured, be in the pool — not for any single incumbent source.

What remains

Reddit today, across all 250 questions

In the full July 16 scan (250 questions), Reddit appears in 13% of answers and holds 1.8% of all citations — 36 thread URLs spread across 30 different subreddits, none appearing more than three times. The subreddit taxonomy we had planned is therefore moot: there is no concentration left to map.

Disclosure. We attempted to fetch the 35 threads' public metadata for age analysis; reddit.com returned HTTP errors for every unauthenticated request. We don't scrape around blocks, so thread ages are not reported — degraded scope over fabricated scope. And a limit worth repeating: two snapshots make a line, not a law. This is the first interval of a monthly series; Reddit could be back at 87% next month, and that would be just as publishable.
What to do about it

Four things this data actually supports

01

Date every source-specific stat

"Reddit is 87% of AI answers" was true, measured — and lasted under fifteen days. Ask anyone quoting a citation stat when it was measured, and how often they re-measure.

02

Optimize for the structure, not the incumbent

The durable facts are structural: engines disagree, agreement is shallow, the pool is a long tail. Structured, citable pages on your own domain competed in both versions of this landscape; a Reddit-thread strategy competed in exactly one.

03

Measure continuously or not at all

Monthly is now the minimum honest cadence. This series re-runs the same 39 questions every month and publishes whatever they say.

04

Re-read report No. 2 with today's numbers

Its structural findings held; its Reddit reach figure did not — which is why it carries a dated update banner instead of a quiet edit.

The data

Every number, in one place

MetricScopeValue
Reddit presence — July 1Perplexity, Set A n=3934 / 39 = 87%
Reddit presence — July 16Perplexity, Set A n=397 / 39 = 18%
Questions citing Reddit both runsPerplexity, Set A7
Reddit share of citations — July 1Perplexity, Set A10.4%
Reddit share of citations — July 16Perplexity, Set A2.0%
YouTube presence, July 1 → 16Perplexity, Set A38% → 36%
Cited domains per answerPerplexity, Set A8.4 → 9.1
Top-cited domain changedPerplexity, Set A31 / 39 = 79%
Self-overlap over 15 days — Perplexitybrand lists, n=3925%
Self-overlap — ChatGPT / Geminibrand lists, n=3937% / 38%
Cross-engine overlap, same dayall 3, July 167.5%
All-3 agreement, July 1 → 16all 3, Set A56% → 59%
≥2 agreement, July 1 → 16all 3, Set A90% → 87%
Reddit presence, all 250 questionsPerplexity, July 1633 / 250 = 13%
Reddit share of all citationsPerplexity, July 16 n=2501.8%
Distinct subreddits / thread URLsPerplexity, July 1630 / 36
Thread metadata fetches blockedreddit.com, unauthenticated35 / 35
Recompute us. Both datasets ship with this report — multi39.csv (July 1) and multi250.csv (July 16; Set A is the identical re-run) — and verify-numbers.py asserts every figure above straight from them. We don't know why the collapse happened — licensing, crawl access, retrieval re-ranking are all consistent with the data and none is verifiable from outside — so we report the measurement and decline to speculate.
Questions this report answers

Quick answers, straight from the data

How fast do AI answers actually change?

In 15 days, on byte-identical questions and an identical pipeline, Reddit fell from 87% of Perplexity’s answers to 18%, and the top-cited source changed on 31 of 39 questions (79%).

Did the structure of AI answers change too?

No. All-three-engine agreement went 56% → 59%, at-least-two went 90% → 87%, and full-list overlap went 7.2% → 7.5%. The rules held; the winners churned.

Is the churn just a Perplexity problem?

No engine agrees with its own two-week-old answers: brand-list overlap with July 1 was 25% for Perplexity, 37% for ChatGPT, 38% for Gemini.

Which sources cite you — this week?

Same method, pointed at your domain, re-measurable monthly. We'll ask the engines your buyers' questions and show you what they cite instead of you — with a date on it.

Run the free audit →
Take this report with you