AI SEO Statistics: SEO Political Campaigns (2026-07 edition)
40 questions · 120/120 expected AI responses · 3 models · measured 2026-07-06
The question bank
The questions we tested — a frozen buyer-intent benchmark for seo political campaigns.
The question set was curated from a predefined buyer-intent taxonomy and held constant for this edition. Each model received the same wording. These are the prompts behind every percentage on this page.
Show all 40 questions
Model by model
13.6% question-level model disagreement.
This rate is the average pairwise disagreement between binary behavior codes across questions and behaviors. It is not the gap between the highest and lowest aggregated model percentages.
Behavior prevalence across 40 seo political campaigns benchmark questions, 2026-07 edition. Last column: equal-model mean.
| Behavior | ChatGPT | Claude | Gemini | Equal-model mean |
|---|---|---|---|---|
| Recommends hiring a professional | 32.5% | 22.5% | 10% | 21.7% |
| Suggests DIY first | 30% | 10% | 15% | 18.3% |
| Names specific providers | 10% | 0% | 0% | 3.3% |
| Gives price or cost info | 7.5% | 5% | 5% | 5.8% |
| Tells to check reviews | 0% | 5% | 0% | 1.7% |
| Tells to verify credentials | 2.5% | 0% | 2.5% | 1.7% |
| Mentions case studies / portfolio | 10% | 12.5% | 2.5% | 8.3% |
| Mentions local proximity | 10% | 7.5% | 10% | 9.2% |
| Gives selection criteria | 15% | 20% | 15% | 16.7% |
| Warns about red flags | 10% | 15% | 2.5% | 9.2% |
| Asks a clarifying question | 37.5% | 55% | 0% | 30.8% |
| Recommends multiple quotes | 2.5% | 0% | 0% | 0.8% |
Question-level agreement
How often all measured models received the same binary code.
Agreement is calculated question by question for each behavior. A high value can coexist with a low behavior prevalence; it means the models usually agreed on whether the behavior appeared.
All-model binary agreement by behavior across 40 benchmark questions.
| Behavior | All-model agreement |
|---|---|
| Recommends hiring a professional | 65% |
| Suggests DIY first | 70% |
| Names specific providers | 90% |
| Gives price or cost info | 92.5% |
| Tells to check reviews | 95% |
| Tells to verify credentials | 95% |
| Mentions case studies / portfolio | 80% |
| Mentions local proximity | 82.5% |
| Gives selection criteria | 77.5% |
| Warns about red flags | 80% |
| Asks a clarifying question | 30% |
| Recommends multiple quotes | 97.5% |
By model
How each assistant handled SEO Political Campaigns questions.
Reading the 120 answers model by model shows how differently the three assistants treat the same seo political campaigns questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 32.5% (ChatGPT) down to 10% (Gemini), a 23-point gap on an identical question set.
Across the 40 seo political campaigns answers it produced, ChatGPT recommended hiring a professional in 32.5% of them and suggested a DIY approach first 30% of the time. It named a specific provider in 10% of answers (about 0.1 distinct providers per answer) and included price or cost information 7.5% of the time. ChatGPT asked a clarifying question before answering in 37.5% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 2.5%, averaging 690 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 10%, and framed the choice around local proximity in 10%; a selection-criteria checklist appeared in 15% of its answers and a recommendation to gather multiple quotes in 2.5%.
Across the 40 seo political campaigns answers it produced, Claude recommended hiring a professional in 22.5% of them and suggested a DIY approach first 10% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 5% of the time. Claude asked a clarifying question before answering in 55% of cases, warned about red flags or scams in 15%, and told the buyer to verify credentials in 0%, averaging 317 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 12.5%, and framed the choice around local proximity in 7.5%; a selection-criteria checklist appeared in 20% of its answers and a recommendation to gather multiple quotes in 0%.
Across the 40 seo political campaigns answers it produced, Gemini recommended hiring a professional in 10% of them and suggested a DIY approach first 15% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 2.5%, and told the buyer to verify credentials in 2.5%, averaging 232 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 10%; a selection-criteria checklist appeared in 15% of its answers and a recommendation to gather multiple quotes in 0%.
Taken together, ChatGPT is the assistant most likely to route a seo political campaigns buyer to a professional (32.5%) and Gemini the least (10%). ChatGPT produced the longest answers, at 690 words on average. Specific providers were named most often by ChatGPT (10%) — even there, roughly one answer in 10 carried a name.
Where they disagree
The behaviors where the choice of model changes the answer.
Question-level model disagreement is 13.6% — the average pairwise rate at which models received different binary codes across questions and behaviors. The observed rate spreads below are a separate measure showing where which assistant a seo political campaigns buyer happens to ask matters most:
- Asks a clarifying question: from 0% (Gemini) to 55% (Claude) — a 55-point spread.
- Recommends hiring a professional: from 10% (Gemini) to 32.5% (ChatGPT) — a 23-point spread.
- Suggests a DIY approach first: from 10% (Claude) to 30% (ChatGPT) — a 20-point spread.
- Warns about red flags or scams: from 2.5% (Gemini) to 15% (Claude) — a 13-point spread.
- Names a specific provider: from 0% (Claude) to 10% (ChatGPT) — a 10-point spread.
The widest single gap — asks a clarifying question, 55 points — means a seo political campaigns buyer can receive materially different guidance on the same question depending only on which assistant they happen to open, so any visibility strategy built on a single model's behavior describes only part of the seo political campaigns market.
Where they agree
The points of near-consensus in SEO Political Campaigns.
On other behaviors the three models move almost in lockstep — the points of near-consensus for seo political campaigns, where all three landed within a few points of each other:
- Gives price or cost information: 5%–7.5% across all three (a 3-point spread).
- Tells the buyer to verify credentials: 0%–2.5% across all three (a 3-point spread).
- Mentions local proximity: 7.5%–10% across all three (a 3-point spread).
- Recommends multiple quotes: 0%–2.5% across all three (a 3-point spread).
Measured question by question, the three assistants coded a response the same way most consistently on "recommends multiple quotes" (identical coding in 97.5% of questions) and least consistently on "asks a clarifying question" (30%).
Every behavior, measured
All twelve coded behaviors for SEO Political Campaigns, averaged across the three models.
The behaviors AI models reproduce most often for seo political campaigns are asks a clarifying question (30.8% on average), recommends hiring a professional (21.7%) and suggests a DIY approach first (18.3%); the rarest are recommends multiple quotes (0.8%), tells the buyer to verify credentials (1.7%) and tells the buyer to check reviews (1.7%). Each figure below is the share of a model's 40 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:
- Asks a clarifying question: 30.8% on average (ChatGPT 37.5%, Claude 55%, Gemini 0%) — a 55-point spread.
- Recommends hiring a professional: 21.7% on average (ChatGPT 32.5%, Claude 22.5%, Gemini 10%) — a 23-point spread.
- Suggests a DIY approach first: 18.3% on average (ChatGPT 30%, Claude 10%, Gemini 15%) — a 20-point spread.
- Gives selection criteria: 16.7% on average (ChatGPT 15%, Claude 20%, Gemini 15%) — a 5-point spread.
- Mentions local proximity: 9.2% on average (ChatGPT 10%, Claude 7.5%, Gemini 10%) — a 3-point spread.
- Warns about red flags or scams: 9.2% on average (ChatGPT 10%, Claude 15%, Gemini 2.5%) — a 13-point spread.
- Mentions case studies or portfolio: 8.3% on average (ChatGPT 10%, Claude 12.5%, Gemini 2.5%) — a 10-point spread.
- Gives price or cost information: 5.8% on average (ChatGPT 7.5%, Claude 5%, Gemini 5%) — a 3-point spread.
- Names a specific provider: 3.3% on average (ChatGPT 10%, Claude 0%, Gemini 0%) — a 10-point spread.
- Tells the buyer to check reviews: 1.7% on average (ChatGPT 0%, Claude 5%, Gemini 0%) — a 5-point spread.
- Tells the buyer to verify credentials: 1.7% on average (ChatGPT 2.5%, Claude 0%, Gemini 2.5%) — a 3-point spread.
- Recommends multiple quotes: 0.8% on average (ChatGPT 2.5%, Claude 0%, Gemini 0%) — a 3-point spread.
Trust signals
How well the models protect the seo political campaigns buyer.
Beyond whether to hire, the rubric codes how carefully each assistant protects the seo political campaigns buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 1.7% of answers on average. Verifying credentials or certifications appeared in 1.7%. Warning about red flags or scams appeared in 9.2%.
On structuring the decision, a selection-criteria checklist showed up in 16.7% of answers on average and a recommendation to gather multiple quotes in 0.8%. The single least-reproduced protective signal for seo political campaigns is "recommends multiple quotes" at 0.8% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.
Referral behavior
Do AI models name SEO Political Campaigns providers?
For service providers the decisive question is whether these systems name anyone at all. Across 120 seo political campaigns answers, a specific provider was named in 3.3% of responses on average — roughly 0 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for seo political campaigns: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.
The question set
What these 40 SEO Political Campaigns questions cover.
The 40 questions behind every percentage on this page form a frozen seo political campaigns (professional services; buyer hiring decisions for this specific service) buyer-intent benchmark. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact seo political campaigns question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.
How to read this
A note on the numbers.
A percentage here is the share of a model's 40 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-06, the figures describe this specific seo political campaigns question set and snapshot rather than a general prior. The full protocol and coding rubric are documented in the study methodology.
Methodology
A controlled snapshot, documented end to end.
40 frozen benchmark questions, one expected response per model per question (ChatGPT API (gpt-5-mini), Claude API (claude-sonnet-5), Gemini API (gemini-3-flash-preview)), collected 2026-07-06 and coded against a fixed 12-behavior rubric. The pipeline validates the schema, recomputes aggregates and reports consistency issues. AI outputs vary with model version, location and time, so the figures describe this edition's exact sample and measurement window. Read the full methodology →
Citation
Cite this edition.
Authority Specialist. “AI SEO Statistics: SEO Political Campaigns (2026-07 edition).” AuthoritySpecialist.com. https://authorityspecialist.com/research/ai-seo-statistics/services/professional/seo-political-campaigns