AI SEO Statistics: SEO Content Strategy for Energy Industry (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same seo content strategy for energy industry questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 47.5% (ChatGPT) down to 32.5% (Gemini), a 15-point gap on an identical question set.

Across the 40 seo content strategy for energy industry answers it produced, ChatGPT recommended hiring a professional in 47.5% of them and suggested a DIY approach first 42.5% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 12.5% of the time. ChatGPT asked a clarifying question before answering in 30% of cases, warned about red flags or scams in 2.5%, and told the buyer to verify credentials in 7.5%, averaging 792 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 25%, and framed the choice around local proximity in 7.5%; a selection-criteria checklist appeared in 17.5% of its answers and a recommendation to gather multiple quotes in 2.5%.

Across the 40 seo content strategy for energy industry answers it produced, Claude recommended hiring a professional in 35% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 2.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 7.5% of the time. Claude asked a clarifying question before answering in 52.5% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 5%, averaging 333 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 25%, and framed the choice around local proximity in 17.5%; a selection-criteria checklist appeared in 37.5% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 40 seo content strategy for energy industry answers it produced, Gemini recommended hiring a professional in 32.5% of them and suggested a DIY approach first 12.5% of the time. It named a specific provider in 2.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 15% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 12.5%, and told the buyer to verify credentials in 2.5%, averaging 224 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 7.5%, and framed the choice around local proximity in 15%; a selection-criteria checklist appeared in 32.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a seo content strategy for energy industry buyer to a professional (47.5%) and Gemini the least (32.5%). ChatGPT produced the longest answers, at 792 words on average. Specific providers were named most often by Claude (2.5%) — even there, roughly one answer in 40 carried a name.

On other behaviors the three models move almost in lockstep — the points of near-consensus for seo content strategy for energy industry, where all three landed within a few points of each other:

• Tells the buyer to check reviews: 0% across all three models.
• Names a specific provider: 0%–2.5% across all three (a 3-point spread).
• Recommends multiple quotes: 0%–2.5% across all three (a 3-point spread).
• Tells the buyer to verify credentials: 2.5%–7.5% across all three (a 5-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "tells the buyer to check reviews" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (37.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the seo content strategy for energy industry buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 0% of answers on average. Verifying credentials or certifications appeared in 5%. Warning about red flags or scams appeared in 11.7%.

On structuring the decision, a selection-criteria checklist showed up in 29.2% of answers on average and a recommendation to gather multiple quotes in 0.8%. The single least-reproduced protective signal for seo content strategy for energy industry is "tells the buyer to check reviews" at 0% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 40 questions behind every percentage on this page were drawn from real seo content strategy for energy industry (professional services; buyer hiring decisions for this specific service) buyer journeys. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact seo content strategy for energy industry 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.