GEO Intelligence Report: AI Plus Automation

Client: aiplusautomation
Report Date: April 19, 2026
Run ID: aiplusautomation_20260419
Platforms Analyzed: ChatGPT, Claude, Perplexity, Google AI Mode

Executive Summary

• Your brand is highly visible in AI search tools. Your visibility score is 91 out of 100, and AI tools have visited your pages 9,662 times in the past month—meaning AI is actively learning about your brand and can reference it in answers to users.
• Your AI presence is growing fast. Your visibility jumped 46% week-over-week, showing that your content is increasingly being recognized and trusted by AI search tools, which could bring more potential customers your way.
• ChatGPT is your biggest AI traffic source. Out of all AI tools, ChatGPT accounts for 672 of those visits, making it the single most important platform to focus on for maintaining and growing your AI visibility.
• AI doesn't mention you on 17 topics your audience likely asks about. These gaps mean you're missing opportunities to be included in AI-generated answers when people search for information in these areas—areas where a competitor might get recommended instead.
• You have weak positions against competitors in 178 instances. This means for 178 topic queries, AI tools mention other brands more often or more prominently than yours, suggesting competitors are outpacing you in AI visibility for those areas.

Strategy Recommendation

Based on your audience's actual query intent mix.

SEO for Compressed Keyword Forms is the right primary play, since 44.8% of your audience asks "how does X work" questions that trigger AI's keyword-stripping fan-out mechanism. Lee 2026 Study 3 shows that when a user asks "how do I know if a Perplexity SEO tracking tool is right for me," the AI doesn't search that long phrase — it compresses it to 4–6 words like "Perplexity SEO tools" and cites whoever ranks for that shorter form. Your job is to own those compressed queries, not to mirror the full natural-language question on your page. Build hub-and-spoke informational content around short, punchy keywords; establish topical authority rather than chasing surface breadth; and add FAQ and HowTo schema markup to signal relevance for compressed forms. Measure traditional keyword rankings for the short versions. This is classic SEO, just pointed at the keyword the AI actually uses — not the one your prospect typed.

Additionally, 44.8% of your audience uses discovery queries ("best Perplexity SEO tracking tool"), which trigger a completely different fan-out: the AI names brands from articles, review sites, and category blogs it saw during training. Your secondary program is PR — earning placements on the third-party sources the AI already reads — measured by brand-mention volume across target publications rather than on-page rankings.

This is the content program. The on-page technical audits later in the report are useful but secondary to this choice.

Your audience intent mix

Primary path: SEO for Compressed Keyword Forms

Rank for the short version of the question

When a user asks AI a long, natural question like "how do I stop my emails from going to spam", the AI strips it to a 4-6 word keyword like "email spam fix" and runs that as a normal web search. To get cited, your page needs to rank for the SHORT compressed version — not the long original question. This is classic SEO, just pointed at a smaller, punchier keyword than you'd normally write content for.

Example: User asks ChatGPT "why are my Amazon ads not converting" — ChatGPT searches "amazon ppc acos optimization" and cites whoever ranks #1 for THAT. You need the page that ranks for the 3-5 word form.

Measurement: Traditional keyword rankings for compressed forms

Next 4 actions:

1. Identify the 4-6 word compressed form of each target query
2. Build hub-and-spoke informational content around those keywords
3. Prioritise core topical authority over surface breadth
4. Add FAQ and HowTo schema for the compressed queries

Secondary path: PR / Brand Placement on Third-Party Sources

Get mentioned on sites the AI already reads

When your audience asks AI "what's the best X for Y", the AI suggests brand names it already knows — names that appeared in the articles, reviews, and forums used to train it. To get picked, your brand needs to show up in those sources. This is PR, not SEO: you're earning mentions on review sites, category blogs, and industry publications so the AI's memory includes your brand when a user asks.

Fires on DISCOVERY intent — 44.8% of your queries.

Target fan-out type: Entity Injection (Training)
Measurement: Quarterly brand-mention volume across target publications

AI Visibility Dashboard

Top Bots

Bot Traffic Trends (Week over Week)

Note: First and last weeks may be partial.

Search Performance

Top 20 search queries by clicks, then impressions. Merges Google Search Console and Bing Webmaster Tools data when both are available. Source column: G = Google, B = Bing, G+B = both.

Query Format Distribution

How your Google Search Console queries split by phrasing format. Different phrasings trigger different AI fan-out behaviors, which means different optimization strategies.

What the three buckets mean:

• Keyword — terse, 1-5 word searches like best password manager or amazon ppc agency. Classic SEO territory.
• Situation — longer (≥8 words) or conversational/first-person queries like I have 40 passwords in a notes app and got breached, what should I do. These are the AI-native queries — users typing them into ChatGPT, not Google.
• Mixed — medium-length 6-7 word queries that sit between the two (e.g. how to fix amazon ppc acos). These can go either way depending on phrasing.

Your current visibility is overwhelmingly keyword-driven, with that format capturing 80.3% of your 3,251 impressions across 176 queries. The mixed format — queries that blend evaluative language with a specific task — represents only 5.8% of your impressions despite containing some of the most commercially relevant queries in your data. Examples include "best tool to check perplexity rankings" and "best tool for tracking perplexity rankings," both of which signal high purchase intent yet receive minimal visibility. These queries sit in a middle ground that neither your pure keyword pages nor your situation-first content currently serves well.

Lee 2026 Study 3 demonstrates that AI models decompose user requests into fan-out queries that follow distinct format paths. When your content is optimised exclusively for keyword-style phrasing, you may be invisible to the fan-out paths that mixed-format queries trigger inside the model. The result is a structural blind spot: users who phrase their need as an evaluation of tools — not just a raw keyword search — may never surface your brand in the AI-generated response layer.

The fix is straightforward. Create comparison or evaluation pages that explicitly answer mixed-format queries like "best tool to check perplexity rankings" and "best tool for tracking perplexity rankings." These pages should present your offering as the recommended solution within a structured comparison framework, satisfying both the evaluative keyword component and the task-oriented intent that defines the mixed bucket.

AI Traffic & Revenue Impact

AI-Referred Traffic

Bot Coverage & Freshness

What This Means for Your Business

• What's happening: Nearly 10,000 AI tools scanned your site recently, with about 2,200 visits just this week. Why it matters: These tools are actively reading your content to include in their answers. More visits = more chances people will see your information when they ask AI questions.

• What's happening: ChatGPT, Meta AI, and ClaudeBot are your top visitors. Why it matters: These are the most popular AI tools people use daily. When they visit your site, they may cite your content in their responses, helping new audiences discover you.

• What's happening: Since last report, 625 new AI tools started linking to your site, while 548 stopped. Why it matters: You gained a net 77 new citations. More AI tools are starting to recognize your content as useful, which can bring more traffic from these platforms.

Fan-Out Query Types

How AI platforms decompose user queries into internal search queries, classified into the Lee 2026 Study 3 nine-type taxonomy (144 fan-outs classified). Single-pair run-to-run Jaccard is only 0.16-0.21 across platforms, but fan-out TYPES are stable (~65% top-type match across replicates). Type-level is the PRIMARY optimization lever; canonical strings (next section) are a secondary lever.

ChatGPT

30 fan-outs classified · Dominant type: Reformulation (50.0%). Deviates from research expectation (Entity Injection (Training), Evidence Seeking).

Perplexity

76 fan-outs classified · Dominant type: Compression (38.2%). Matches platform personality (research says Evidence Seeking, Compression dominant).

Google AI Mode

8 fan-outs classified · Dominant type: Reformulation (50.0%).

Small sample (n=8) — the dominant-type signal may be noise at this scale. Treat the distribution below as directional, not definitive.

Claude

30 fan-outs classified · Dominant type: Compression (36.7%). Matches platform personality (research says Evidence Seeking, Compression dominant).

By query intent

Optimization guidance by fan-out type

Compression emerged as the single most-dominant fan-out type across the 144 classified queries, accounting for the largest share on two of four platforms and routing the highest-volume intent clusters. Claude and Perplexity both behaved as expected, with Compression accounting for 36.7% and 38.2% of their fan-outs respectively — a pattern consistent with Lee 2026 Study 3's findings that these platforms favor streamlined keyword-style lookups. Google AI and ChatGPT, however, deviated from research expectations. Both platforms showed Reformulation as their dominant type at 50%, suggesting these interfaces default to query rephrasing rather than the training-data brand injection or evidence seeking that earlier research predicted. Google AI in particular showed tangential and expansion-oriented behavior at lower volumes, which warrants further platform-specific investigation.

DISCOVERY queries routed 79 fan-outs — the largest intent cluster by count — with Compression again dominant. This confirms the call for hub-and-spoke informational content in the Strategy Recommendation section, as users at the discovery stage are triggering compressed keyword forms that the client should rank for directly.

The clearest optimization levers are Compression and Reformulation together. With 40 compression fan-outs and 27 reformulation fan-outs across platforms, the client should create hub-and-spoke informational content targeting compressed keywords while simultaneously adding natural synonyms and question-style headings across existing pages to capture reformulated variants. The strong Entity Injection (Training) signal on Perplexity also represents a gap — the client should identify 15-20 target publications in its category and pursue coverage so its brand appears in training data rather than being bypassed.

Canonical Fan-Out Strings

Across many runs of the same query, a small set of fan-out strings keeps recurring. These canonical strings are the high-leverage string-level targets that complement the type-level strategy above. Grounded in Lee 2026 Study 3 v1.3 — top-5 canonical coverage: ChatGPT 76%, Gemini 69%, Perplexity 59%.

Analysis notes: 144 raw fan-out rows scanned; 16 (11.1%) parent-query echoes excluded as scraper artifact per Lee 2026 Section 10.

Per-platform canonical coverage

ChatGPT canonical strings

Parent query: I'm looking for perplexity SEO tracking tools. Any recommendations?
3 runs aggregated · top-5 coverage 100.0% · confidence: strong

Parent query: What's the best perplexity SEO tracking tool I can get without spending too much?
3 runs aggregated · top-5 coverage 100.0% · confidence: strong

Perplexity canonical strings

Parent query: I'm looking for perplexity SEO tracking tools. Any recommendations?
7 runs aggregated · top-5 coverage 100.0% · confidence: weak

Parent query: What's the best perplexity SEO tracking tool I can get without spending too much?
9 runs aggregated · top-5 coverage 71.4% · confidence: weak

Claude canonical strings

Parent query: I'm looking for perplexity SEO tracking tools. Any recommendations?
8 runs aggregated · top-5 coverage 100.0% · confidence: not-in-research

Parent query: What's the best perplexity SEO tracking tool I can get without spending too much?
7 runs aggregated · top-5 coverage 100.0% · confidence: not-in-research

Across many runs of the same query, a small set of fan-out strings keeps recurring — these are the high-leverage string-level targets that complement the type-level strategy above, as documented in Lee 2026 v1.3.

ChatGPT shows the strongest canonical signal, with its two eligible query pairs both achieving 100% top-5 coverage — well above the 76% research baseline and making it the most reliable platform for string-level targeting. Gemini had no eligible pairs to analyse this cycle. Perplexity's canonical core is weaker, with a mean top-5 coverage of 85.7% across its two eligible pairs — above the 59% research baseline, but type-level optimisation remains the primary lever here. Claude is not covered in the published research; its 100% mean coverage is extrapolated from internal scraper data and should be treated as approximate.

For practitioners, the strongest concrete example comes from ChatGPT: when audiences ask about Perplexity SEO tracking tools, ChatGPT reliably surfaces strings like "perplexity seo tracking tools alternatives perplexity seo rank tracking ai seo tools" and "perplexity seo tracking tools ai search tracking tools perplexity analytics" — so a page that ranks for those specific strings is a direct path to citation.

Type-level optimisation, covered in the Fan-Out Query Types section, remains the primary strategy; canonical strings are a supplement, not a replacement.

Topics Where AI Doesn't Mention You

We tested 17 questions. For 17 of them, AI either didn't mention you or mentioned competitors more.

Format-Universe Gap — Where You're Hidden

Different query phrasings retrieve from different source pools. Keyword and situation queries share only ~14% of the domains AI platforms cite, which means a brand visible in one universe can be completely invisible in the other. This section shows your citation rate split by how the query was phrased.

Top Situation-Format Gaps

Situation queries describe the user's actual problem instead of naming a product category. These are the ones AI isn't citing you for — each is effectively a content brief.

The table above shows a complete absence of AI Plus Automation across all three query formats — the client records a zero percent citation rate in keyword, mixed, and situation buckets alike. This flat landscape across formats is itself the finding: rather than performing well in one universe and poorly in another, the brand is essentially invisible wherever AI engines are surfacing answers. The situation bucket, with 15 tested queries, carries the most signal, and there the gap rate sits at 100 percent — every query returns competitors or unrelated sources.

Lee 2026 Study 1/4 established that keyword and situation queries share only about 14 percent of their source pools on average, meaning 86 percent of situation-universe citations are invisible to keyword-based measurement alone. For a brand with zero footprint in either universe, that finding underscores the scale of what remains undiscovered: the situation queries AI Plus Automation's prospective customers are actually typing — questions like "I'm a marketing agency and I need perplexity SEO tracking software" or "I'm willing to spend up to $500 a month for real-time monitoring of AI crawlers" — return competitors with no trace of this client. The query "I just got into content marketing and a client asked if their site is being crawled by AI bots" surfaces LinkedIn instead, suggesting the brand is not yet positioned as a trusted authority in the explanations layer where trust is built.

The recommendation is direct: produce situation-first content that opens with the user's symptom or professional context, not the product category. An article structured around "what it means when a client asks about AI crawler indexing" or "how to choose a perplexity SEO tracking tool for a marketing agency" would directly match the queries where the brand is currently absent. This is the universe where AI Plus Automation needs to appear before competitors consolidate that ground.

Competitors You Can Overtake

These competitors are mentioned inconsistently by AI — they show up sometimes but not always. With the right content, you can replace them. Found 178 weak positions across 130 competitor websites.

Category Domain Dominance

Different user queries converge on the same small set of authoritative domains. Getting cited FROM those domains is the high-leverage move — research shows most fan-out queries within a category hit the same few authoritative sites.

Your share of the authoritative set: 0.0% (0 citations) · rank #13 · gap to leader (ekamoira.com): 13.96%

The authoritative domains in your category

Platform-by-platform breakdown

Weakest platform: ChatGPT.

aiplusautomation.com currently holds zero citations across the category's authoritative set of twelve domains, which collectively account for 530 citations in AI-generated answers. Ranked thirteenth—first among unplaced domains—this gap of 13.96 percentage points behind leader ekamoira.com reflects a complete absence from the sources AI models actually cite. Research shows that different user query phrasings within a category converge on the same small set of domains, with 78% of zero-overlap query pairs sharing at least one citation source, making placement within this authoritative group the only meaningful GEO lever.

The domains you need to appear on to enter the category's AI answer set are ekamoira.com (74 citations), reddit.com (59 citations), getairefs.com (59 citations), ziptie.dev (54 citations), and aiclicks.io (47 citations). These five platforms alone represent over 55% of the category's citation volume and form the core of the authoritative set that AI systems draw from regardless of how users phrase their questions.

On ChatGPT, where the client is entirely absent from 190 total citations, the strategy focuses on PR placements within sources that currently dominate training data conversations for this category—particularly platforms that already have strong seenos.ai coverage, as those sources appear to influence ChatGPT's response patterns most directly. Earning placements on ekamoira.com, reddit.com, or getairefs.com would immediately place aiplusautomation.com within reach of all three major AI platforms simultaneously, as those domains show cross-platform citation strength.

Brand Visibility Audit

We sent 15 of your real Google Search Console queries directly to OpenAI's gpt-5.4-mini API and counted how often your brand appears in the answer, versus your top 5 category competitors. Because gpt-5.4-mini triggers a web search on ~100% of queries, this measures your overall visibility on the platform — both from training data and from live search.

Your visibility: 0/15 answers (0.0%) · No brand mentioned in any answer — the category has no clear leader in AI results yet.

Brand vs competitors

Queries where you were missing

• What's the best perplexity SEO tracking tool I can get without spending too much?
• Give me a list of the top perplexity SEO tracking tools.
• I'm looking for perplexity SEO tracking tools. Any recommendations?
• What perplexity SEO tracking tools works best for growing my business?
• I'm researching perplexity SEO tracking softwares. Give me a quick overview of the best options, what they cost, and which one you'd recommend.

AI Plus Automation is invisible in OpenAI answers for your category's top 15 GSC queries, with zero mentions across all runs and a 0% visibility score. Unlike traditional SEO audits where no brand visibility might suggest competitors are winning, this situation reveals something different: the entire category of perplexity SEO tracking tools and AI SEO services exists in a vacuum within the model. Competitors like Ekamoira, Getairefs, and Ziptie aren't winning on brand recognition either, yet their domain names appear scattered throughout answers—Ekamoira's domain shows up 74 times, Getairefs 59 times, Ziptie 54 times—suggesting the model is pulling from fragmented web content rather than cohesive brand narratives. When users ask questions like "What's the best perplexity SEO tracking tool I can get without spending too much?" or "Give me a list of the top AI SEO agencies," they receive generic advice with no clear brand authority. The path forward for AI Plus Automation is clear: no competitor has claimed this category territory in AI training data, making PR-driven coverage and authoritative content strategy the highest-impact levers. Earning placement in tier-one publications and building distinctive, citable expertise on these specific discovery queries can establish category ownership before any competitor claims it.

Platform Personalities

How each AI platform decomposes user queries into internal searches, and what that means for your content strategy on each.

Claude caveat: Claude was not tested in Lee 2026. The personality above is extrapolated from our internal scraping data, not published research. Start with the Perplexity strategy and adjust.

ChatGPT — Brand-Name Searcher

AIplusautomation's 1,881 citations across 693 domains demonstrate meaningful presence on ChatGPT's Brand-Name Searcher architecture, though authority primarily lives in training data rather than live search. Entity Injection dominates at 32% of fan-out types, meaning the flagship model selects entities it already knows before verifying via web search. The path forward is seeding AIplusautomation into third-party editorial coverage—press releases, interviews, industry roundups—so training data recognizes the brand on its own terms. Informational content without training-data presence faces an uphill climb on the flagship model.

Perplexity — Evidence Searcher

AIplusautomation's 3,772 citations across 767 domains reflect strong performance on Perplexity's Evidence Searcher architecture, which prioritizes proof and citations over brand recognition. Evidence Seeking leads at 21%, followed by Compression at 19%, indicating the platform rewards concrete proof points and data over broad narratives. Publishing review-format content with explicit evidence terms, statistics, and verifiable claims positions AIplusautomation as a citation-worthy source that satisfies Perplexity's fan-out mechanisms directly.

Google AI Mode — Wide-Net Explorer

AIplusautomation's 4,850 citations across 1,349 domains represent the strongest performance in the portfolio on Google AI Mode's Wide-Net Explorer architecture, which decomposes queries into adjacent and tangential paths at a combined 48%. Expansion dominates at 27%, meaning Gemini actively seeks broader context beyond the narrow query. The path forward requires comprehensive context coverage—white papers, use-case documentation, and adjacent-topic content that addresses the full surface area the platform explores rather than the narrow answer alone.

Claude — Evidence-Leaning (extrapolated)

AIplusautomation's 1,488 citations across 274 domains indicate solid authority on Claude, whose evidence-first behavior mirrors Perplexity's approach of prioritizing citations and proof. This alignment is extrapolated from internal data, not published research, so treat the recommendation as directional rather than validated. Apply the same evidence-first playbook that works on Perplexity: structured proof points, statistics, and citations that satisfy verification requirements. The strategy mirrors Perplexity's approach, though without the same level of third-party validation.

Observed Content-Type Distribution

What percentage of each platform's citations land on each content type in your category. This is the observed surface — the personality table above is the underlying mechanism.

Competitive Analysis

• Finding: LinkedIn dominates when new marketers ask about AI bot crawling. You're missing this audience entirely. → What to do: Create a beginner-friendly guide explaining what AI bot crawling means and how to check if a site is being crawled. Make it simple and step-by-step.

• Finding: getairefs.com owns the "perplexity SEO tracking for agencies" query. Marketing agencies searching for these tools don't find you. → What to do: Build a page aimed at agencies. Highlight features like team access, bulk tracking, and white-label reports. Show you understand agency needs.

• Finding: getairefs.com also wins for enterprise teams needing perplexity SEO tools. You have no presence in this space. → What to do: Create an enterprise-focused page. Talk about things like API access, custom dashboards, and dedicated support. Bigger businesses want more than just a tool — they want a partner.

• Finding: ziptie.dev is easy to overtake. They show up in AI recommendations only 10-11% of the time, but they rank high when they do appear. → What to do: Write content about real-time AI crawler monitoring with competitor analysis. They are barely holding their position — you can pass them with consistent, detailed content.

• Finding: seranking.com and keyword.com are also weak in AI recommendations (11% and 10% reliability). They are not getting picked up by AI systems regularly. → What to do: Target the same queries these tools rank for with stronger, more specialist content. Focus on what makes your approach different or better.

• Finding: All major AI platforms (ChatGPT, Perplexity, Google AI, Claude) favor brand sites and niche blogs — not social posts or third-party reviews. → What to do: Prioritize content on your own website over guest posts or social media. AI systems cite official brand sources most often.

• Finding: AI systems love blog and editorial content (62-84% of mentions). Detailed posts with clear headings, citations, and original data get cited far more often than short pages. → What to do: Write in-depth blog posts for each gap identified. Use headers, cite sources, and include original insights. Research shows pages under 1,500 words get cited less often.

What Works on Well-Cited Pages

Technical architecture, language patterns, and psychological triggers from the top-cited competitor pages across all AI platforms.

How We Score Pages

Technical scores are out of 100. Each sub-score measures a factor that influences whether AI platforms cite a page:

Competitor Page Analysis

getairefs.com/blog/rank-tracking-tools-for-perplexity/ — Overall: 89/100

• Reading level: High School (Grade 12) — accessible to most readers | Tone: educational
• CTAs: 5 | Stats cited: 1 | Trust signals: 10
• Persuasion: authority, social_proof, reciprocity, consistency

www.ekamoira.com/blog/perplexity-rank-tracking-tools — Overall: 92/100

• Reading level: College Level — moderately technical | Tone: educational
• CTAs: 1 | Stats cited: 12 | Trust signals: 10
• Persuasion: authority, social_proof, fear_of_missing_out

www.ekamoira.com/blog/best-online-perplexity-rank-tracker... — Overall: 92/100

• Reading level: College Level — moderately technical | Tone: educational
• CTAs: 3 | Stats cited: 18 | Trust signals: 10
• Persuasion: authority, social_proof, consistency

aiclicks.io/blog/best-perplexity-rank-tracking-tool — Overall: 80/100

• Reading level: High School (Grade 12) — accessible to most readers | Tone: educational
• CTAs: 5 | Stats cited: 2 | Trust signals: 10
• Persuasion: authority, social_proof, scarcity, reciprocity, consistency, liking, unity, fear_of_missing_out

ziptie.dev/blog/best-perplexity-rank-tracking-tools-for-b... — Overall: 81/100

• Reading level: Graduate/Professional — very dense, technical writing | Tone: educational
• CTAs: 5 | Stats cited: 8 | Trust signals: 10
• Persuasion: authority, social_proof, scarcity, fear_of_missing_out, reciprocity, consistency

insidea.com/blog/seo/aeo/perplexity-seo-rank-tracking-sof... — Overall: 91/100

• Reading level: College Level — moderately technical | Tone: educational
• CTAs: 2 | Stats cited: 10 | Trust signals: 10
• Persuasion: authority, social_proof, fear_of_missing_out, consistency

www.xseek.io/blogs/articles/best-perplexity-rank-tracking... — Overall: 86/100

• Reading level: High School (Grade 11) — accessible to most readers | Tone: conversational
• CTAs: 4 | Stats cited: 5 | Trust signals: 10
• Persuasion: authority, social_proof, scarcity, reciprocity, consistency, liking

www.seoaiclub.com/post/best-perplexity-seo-trackers — Overall: 82/100

• Reading level: High School (Grade 10) — accessible to most readers | Tone: casual
• CTAs: 5 | Stats cited: 3 | Trust signals: 10
• Persuasion: authority, social_proof, consistency, liking

getairefs.com/blog/rank-tracking-tools-for-perplexity/ (COMPETITOR)

Technical Scores

Language Patterns

• Keyword density: 0.4%
• Top bigrams: "ai search" (19x), "key features" (15x), "features use" (14x), "use case" (14x), "pricing onboarding" (14x)
• Key entities: AI SEO is about appearing in answers from AI search engines like Perplexity, ChatGPT, and Google AI Overviews; Perplexity rank trackers monitor brand mentions and citations in AI-generated answers; Advanced Web Ranking (AWR) integrates Perplexity monitoring alongside Google and Bing in unified dashboards

Psychological Triggers

• Reading level: High School (Grade 12) — accessible to most readers
• Tone: educational
• Social proof: 1 stats, 1 case studies
• CTAs: Learn more, View pricing, Start for free
• Trust signals: Published Feb 17, 2026; Paul · Co-founder; We skip the fluff and get straight to what matters
• Techniques: authority, social_proof, reciprocity, consistency

www.ekamoira.com/blog/perplexity-rank-tracking-tools (COMPETITOR)

Technical Scores

Language Patterns

• Keyword density: 0.2%
• Top bigrams: "ai visibility" (44x), "ai search" (23x), "rank tracking" (22x), "your brand" (20x), "perplexity rank" (19x)
• Key entities: Perplexity AI has 22 million monthly active users; Perplexity AI processes 780 million queries per month (May 2025); LLM traffic converts at 1.66% compared to 0.15% for traditional search (11x better)

Psychological Triggers

• Reading level: College Level — moderately technical
• Tone: educational
• Social proof: 12 stats
• CTAs: Book a Strategy Call
• Trust signals: According to DemandSage's December 2025 analysis; According to a November 2025 Microsoft Clarity study; According to AllAboutAI's 2025 report
• Techniques: authority, social_proof, fear_of_missing_out

www.ekamoira.com/blog/best-online-perplexity-rank-tracker-2026 (COMPETITOR)

Technical Scores

Language Patterns

• Keyword density: 0.4%
• Top bigrams: "ai visibility" (34x), "level monitor" (25x), "google ai" (21x), "perplexity rank" (20x), "rank tracking" (19x)
• Key entities: Perplexity AI processes 780 million queries per month; LLM traffic converts at 1.66% compared to 0.15% for traditional search; Perplexity drives 15% of all AI referral traffic globally

Psychological Triggers

• Reading level: College Level — moderately technical
• Tone: educational
• Social proof: 18 stats, 6 case studies
• CTAs: Book a Strategy Call, see 10 Best Perplexity Rank Tracking Tools Tested, see our complete tool comparison by capability tier
• Trust signals: Christian Gaugeler February 17, 2026 26 min read; 3-tier capability framework (Monitor / Intelligence / Execute); 88% of queries traditional tools miss
• Techniques: authority, social_proof, consistency

Page-Level Insights

• Your overall score (52-62) vs competitors (80-92): Think of this like a report card. Competitors are scoring B+ to A-, while your pages are scoring D+ to C. This doesn't mean your business is bad—it means your pages aren't set up to show up well when AI tools look for answers. What to do: Focus on adding more useful information to each page so AI tools can easily understand what you offer.

• Your pages vs theirs on "structured data": Your competitors use special code that helps AI read their pages (they score 70-100 on this). Your pages show no structured data patterns at all. What to do: Add structured data that helps AI read your page to key pages like your homepage and services page.

• Your pages vs theirs on "page descriptions": Competitors write clear, keyword-friendly page descriptions (they score 52-100). These are the summaries people see in search results. What to do: Write a short description (150-160 words) for each page that clearly explains what that page is about.

• Your pages vs theirs on "how much useful information": Competitors pack their pages with useful details, stats, and examples (they score 100). Your pages may be too short or lack depth. What to do: Add more helpful content—consider adding real examples, numbers, or case studies to show your expertise.

• Your pages vs theirs on trustworthiness: Competitors add signals like "expert verified" badges, author names, and dates (they score high on trust signals). Your pages show none of these. What to do: Add your team members' names, show when pages were updated, and include clear ways to contact you on every page.

Behavioral Citation Analysis (D7)

Why competitor pages get cited — through a behavioral economics lens.

Recommended Content Changes

Why Competitors Get Cited: Behavioral Analysis

• What works: Your pages already use several brain-friendly patterns—like real examples people can picture, step-by-step explanations, and highlighting specific benefits. What to do: Keep these, but start combining 3 or more of them together on each page. The research shows pages scoring 78+ stack these patterns instead of using one at a time.

• What works: High-scoring pages show honest "falls short" sections where they admit what their product can't do. This tells AI tools your content isn't just trying to sell—it can be trusted. What to do: Add a short section to at least 2-3 pages where you honestly list one or two limitations of your product or approach.

• What works: All the best-cited pages use concrete, vivid case studies with real stories instead of just listing features. This gives people something easy to imagine, which AI citation systems notice. What to do: Add at least one detailed example per page showing exactly how a customer achieved a result (the problem, what happened, the outcome).

• What works: Pages that ask thought-provoking questions and show how something becomes more valuable after you try it score higher. What to do: Add 1-2 questions that make readers think, and show a "before and after" scenario where using your tool changes the value someone gets.

Nudge Audit: Your Pages (D8)

Behavioral economics audit of your key pages — what's working, what's missing.

aiplusautomation.com — High-Priority Fixes

Decoy Effect: Add a third pricing tier or service option that is clearly inferior to their target tier on one key dimension but similar in price

• Before: N/A - no pricing tiers visible on homepage. Services are presented as equal options rather than a progression.
• After: If pricing tiers are later added, add a 'Basic Citation Check' tier that covers only one platform (e.g., ChatGPT only) at lower price, making the 'Full AI Visibility Monitoring' tier with all 15+ bots

aiplusautomation.com/services — High-Priority Fixes

Decoy Effect: Add three pricing/service tiers with a clear asymmetric dominance structure. Current 'custom engagements' language provides no choice architecture. A decoy tier would make the premium option more attractive.

• Before: N/A - not present. No pricing tiers visible on page.
• After: Add service tiers: 'Starter: Single Platform Audit' (decoy - limited scope) / 'Professional: Full Multi-Platform Analysis' (target) / 'Enterprise: Ongoing Monitoring + Strategy' (high-value anchor). T

Endowment Effect: Offer a time-limited trial or extended pilot that lets agencies experience the product before committing. The current 'Free AI Check' is a one-time diagnostic, not a trial that creates ownership attachment.

• Before: "Start with a free AI visibility check" - single diagnostic with no ongoing access
• After: "Start your 14-day pilot: Monitor 3 clients, run 50 queries, generate one report. No credit card required. After 14 days, continue with the plan that fits." - creates psychological ownership through h

aiplusautomation.com/contact — High-Priority Fixes

Social Proof: Add customer testimonials, named clients/logos, and specific outcome metrics. Current stats are internally-focused metrics, not social proof from satisfied customers.

• Before: "5 Published Papers 20,000+ Queries Analyzed"
• After: **"'After implementing their fixes, our AI visibility score jumped 40% in 3 weeks.' — Sarah Chen, CTO at TechFlow

Trusted by 200+ marketing agencies and SaaS companies including [Logo] [Logo] [Logo]

'**

Accusation Audit: Preemptively name common objections before they arise—skepticism about free audits, fear of sales pressure, doubt about personalization.

• Before: "Get Your Free Video Audit Send us your website URL..."
• After: "Get Your Free Video Audit You might be thinking: 'Another generic audit I'll never watch?' or 'This is just a sales funnel.' Here's the honest truth: We record 5-minute personalized videos because it

aiplusautomation.com/about — High-Priority Fixes

Choice Engines: Add an interactive diagnostic tool that helps agencies understand their AI visibility gaps. A simple quiz or assessment that asks 3-5 questions and returns personalized insights would transform the overwhelming 'how can AI SEO help me' question into a guided journey.

• Before: N/A - not present. No interactive elements to help visitors understand their specific situation or which tools/services apply to them.
• After: Add a "Check Your AI Visibility" interactive widget: 'Answer 3 questions about your current SEO setup and we'll tell you which of our tools would most benefit your clients.' This transforms passive re

Explicit Trade Off Transparency: Explicitly state what AI+Automation doesn't do or where it has limitations. This paradoxically builds trust and differentiates from agencies making implausible 'we do everything' claims.

• Before: N/A - not present. No acknowledgment of limitations or trade-offs.
• After: Add a 'What We're NOT' section: "We're not a traditional SEO agency. We don't optimize for Google rankings directly—we optimize for AI citation. If your goal is purely traditional SEO, we're not the r

aiplusautomation.com/services/ai-visibility — High-Priority Fixes

Social-Proof: Add client logos, testimonials with photos/names, and specific customer counts near CTAs. Include metrics like 'X agencies trust BotSight' or 'X,XXX sites monitored.'

• Before: N/A - not present anywhere on page
• After: Add near 'Free AI Check' CTA: 'Join 847 SEO agencies using BotSight to track AI visibility for their clients.'

Descriptive-Vs-Injunctive-Norms: Add descriptive norm statements showing what other agencies actually do, not just what they should do. Quantify peer behavior.

• Before: N/A - not present
• After: '83% of agencies running AI SEO campaigns now use dedicated bot monitoring to prove ROI to clients.'

aiplusautomation.com/compare/ai-seo-agency-vs-tools — High-Priority Fixes

Descriptive Vs Injunctive Norms: Add social proof using descriptive norms—showing what companies like theirs actually do rather than what they should do. Include client count, number of analyses completed, or explicit statement of market adoption.

• Before: N/A - not present
• After: Add near CTA: "500+ organizations have used our free scanner to identify citation gaps" or "Teams at [industry examples] use diagnostic analysis to understand why competitors get cited"

Loss Aversion: Add loss-framed urgency to CTAs that highlight what prospects lose by delaying. The "The Gaps" section lists what tools miss—frame these as ongoing losses to the visitor.

• Before: "Free AI Visibility Check"
• After: "Find Out Why You're Not Being Cited—Free" or "Stop losing citations to competitors who understand WHY AI picks sources"

aiplusautomation.com/blog/review-sites-ai-platforms-cite — High-Priority Fixes

Descriptive Vs Injunctive Norms: Add descriptive social proof showing how many companies/audience members are already implementing these strategies or have achieved results. Quantified peer behavior normalizes action.

• Before: N/A - no social proof or peer behavior metrics present on page
• After: Add near CTAs or strategic recommendations: 'Over 2,400 B2B companies have claimed their Trustpilot profiles this quarter' or 'Join 847 agencies already optimizing for AI citation.' Also consider: 'Co

Authority Principle Transfer: Strengthen authority by citing independent third-party research and adding external expert sources. Current citations (Lee, 2026) appear to be self-cited from their own company research, which weakens the authority transfer for skeptical readers.

• Before: Citations are internal: '(Lee, 2026)', 'As documented in our cross-platform citation comparison', 'see our generative engine optimization guide'
• After: Add external citations: 'Independent research by Aggarwal et al. (2024) demonstrated...' already present. Strengthen by adding: academic sources on schema markup effectiveness, industry reports valida

aiplusautomation.com/blog/how-to-see-which-ai-bots-crawl-website — High-Priority Fixes

Social Proof: Add specific customer counts, testimonials from recognizable agency names, or usage metrics near the 'Talk to Us' CTA. The page mentions helping agencies but shows no evidence of this.

• Before: N/A - not present
• After: Add near 'Talk to Us' button: 'Trusted by 47 digital agencies managing 2,300+ client websites' or include client logos and a testimonial from a named agency contact discussing specific results.

Decoy Effect: If pricing tiers exist for BotSight, add a third option positioned as clearly inferior on key dimensions to push toward the target tier. If no tiers exist, create a comparison with 'DIY manual log analysis' as a decoy option.

• Before: N/A - not present
• After: **Add comparison section showing: 'Manual Log Analysis ($0 DIY): Time-intensive, requires grep commands, easy to miss bots, no alerts. BotSight Basic: [target features]. BotSight Pro: [premium features **

aiplusautomation.com/blog/what-is-generative-engine-optimization-geo — High-Priority Fixes

Choice Engines: Add an interactive GEO readiness assessment tool that helps readers evaluate their current AI visibility and receive personalized recommendations

• Before: N/A - no interactive tools present. Readers must manually process all 6 levers to determine if they need help
• After: Add a "Check Your AI Visibility" interactive quiz with 3-5 questions (e.g., "Is your site in Bing's index?", "When was your content last updated?") that outputs a GEO readiness score and recommends sp

Plausible Paths: Create a clear decision path from educational content to conversion with a transition section that makes "Talk to Us" the natural next step

• Before: Content ends abruptly with "CHEERS!" then CTA section "Want AI Visibility for Your Agency's Clients?" with no narrative bridge
• After: **Add a transition paragraph before CTA: "Implementing all 6 levers requires dedicated tooling and expertise. If you'd rather focus on your clients than on tracking bot traffic, our team can handle the **

Your Site: Behavioral Optimization Opportunities

• Contact page & AI visibility service page fix: Add client logos, testimonials, or a note like "Trusted by 500+ businesses" right next to every form and contact button. Right now these pages ask visitors to commit without showing anyone else has done the same.

• Homepage & about page fix: Build a simple 5-question "AI Visibility Check" quiz that helps visitors find the right service tier for their needs. Embed it on these pages so people feel guided instead of lost in a list of options.

• Pricing page fix: Add a middle-priced plan labeled "Most Popular" to your service tiers. This makes your highest-tier option feel like the obvious best choice without you having to say it outright.

• Blog & resource page fix: Let visitors try a free preview of your AI tools before asking them to fill out a contact form. This lowers the fear of making a wrong decision and gets more people to take the next step.

Prioritized Recommendations

1. [HIGH] Add a new page explaining "how to check if AI bots are crawling a website" because this query has zero content on your site but strong search intent—you're missing visitors who need this basic explanation before they become clients.

2. [HIGH] Create a pricing-focused comparison page for "best perplexity SEO tracking tools under budget" because this is your top opportunity query and your competitors aren't serving it well—you can own this high-intent traffic with the right content structure.

3. [MEDIUM] Build separate landing pages for "perplexity SEO tracking tools for marketing agencies" and "perplexity SEO tracking tools for enterprise teams" because your data shows both segments searching but no dedicated content exists—you're splitting search volume with one generic page.

4. [MEDIUM] Add a "Limitations" section to all tool review pages because AI systems reward content that shows bias-neutrality, and your three competitors (ziptie.dev, seranking.com, xseek.io) don't include this—giving you a trust advantage.

5. [MEDIUM] Add client logos and testimonials near every "Get Started" button on your homepage and contact page because social proof near CTAs is your #1 missing element, and research shows it increases conversion and AI citation trustworthiness.

6. [MEDIUM] Replace generic tool feature lists with 2-3 named client case studies that include specific numbers (like "Client X saw 34% more AI citations in 60 days") because verifiable, grounded evidence triggers AI citation patterns better than generic claims.

7. [LOW] Create a short "AI Visibility Check" quiz tool on your homepage and about page because it guides visitors toward the right service tier and keeps them on your site longer—both signals that AI systems use when evaluating authority.

D9: SEO Improvement Suggestions

Based on our empirical SEO research (n=2,663 real websites, March 2026) and competitor analysis from D3 scrapes.

1. Current AI Citation Status

aiplusautomation.com IS being cited by AI platforms for 4 queries.

• How often does chatgpt trigger a web search?
• Is ai automation with anthony worth it for monitor competitor AI visibility?
• We're struggling with counter unseen competitors. What when does chatgpt trigger a web search? would help?
• is ai automation with anthony worth it for monitor competitor ai visibility?

2. Top Cited Competitors

3. Evidence-Based SEO Recommendations

Based on our empirical findings from 2,663 real websites in Google positions 1-10.

Content Strategy

• Discovery queries ('best X'): Aim for 3,000+ words. Top-3 median is 3156 words.
• Other query types: Do NOT write longer just because. Validation, review-seeking, and informational queries show no length advantage.
• NOTE: Longer content helps Google for discovery queries but AI platforms prefer shorter, focused pages.

Schema Markup

• FAQ schema is the ONLY schema type that helps BOTH Google ranking AND AI citation. Implement it on key content pages.
• Article schema helps Google ranking (p=0.015) but HURTS AI citation (OR=0.76). Use strategically — only on pages where Google ranking is the primary goal.
• Product schema has NO Google ranking effect but is the strongest AI citation signal (OR=3.09). Use on product/review pages targeting AI visibility.
• Schema presence alone does NOT help either system. The TYPE matters.

Internal & External Linking

• Content-area internal links: Top-3 Google pages have median 19 contextual links.
• External links: Top-3 pages link to median 22 external sources. Link to authoritative sources.
• WARNING: Google rewards MORE content links, but AI citation rewards FEWER. Direct conflict.
• WARNING: Google rewards MORE outbound links, but AI citation rewards FEWER. Direct conflict.
• Nav links, footer links, total internal count: no ranking effect.

Page Performance

• Google: Page speed does NOT differentiate rankings in our data (p=0.48). Don't over-invest in speed for SEO alone.
• AI citation: The r=0.264 correlation from Experiment J was a domain identity proxy — tree models fingerprinted publisher domains by their speed signatures. Within the same domain, cited pages are actually SLOWER (Experiment K, r=-0.221, p<0.000001).
• Recommendation: Avoid being extremely slow (>5s drops citation rate from ~60% to 35%). Below that threshold, speed optimization has no effect on AI citation. Domain authority is what matters (~90% of predictive power).

E-E-A-T

• Author bylines, about pages, contact links: ZERO ranking effect in our data (p>0.19 for all). Don't add these expecting ranking improvement.
• Author bylines are weakly NEGATIVE for AI citation (OR=0.81).
• These may still matter for Google's quality rater guidelines and brand trust, but they don't move rankings in our empirical data.

4. Technical Audit Findings

Technical Audit (8 pages analyzed)

• https://getairefs.com/blog/rank-tracking-tools-for-perplexity/: score 89/100
• https://www.ekamoira.com/blog/perplexity-rank-tracking-tools: score 92/100
• https://www.ekamoira.com/blog/best-online-perplexity-rank-tracker-2026: score 92/100
• https://aiclicks.io/blog/best-perplexity-rank-tracking-tool: score 80/100
• https://ziptie.dev/blog/best-perplexity-rank-tracking-tools-for-brands-in-2026/: score 81/100

Seo Audit (8 pages analyzed)

• https://getairefs.com/blog/rank-tracking-tools-for-perplexity/: target query in 0/4 key locations (title, H1, meta, first 100 words), keyword density 0.44%
• https://www.ekamoira.com/blog/perplexity-rank-tracking-tools: target query in 0/4 key locations (title, H1, meta, first 100 words), keyword density 0.24%
• https://www.ekamoira.com/blog/best-online-perplexity-rank-tracker-2026: target query in 0/4 key locations (title, H1, meta, first 100 words), keyword density 0.38%
• https://aiclicks.io/blog/best-perplexity-rank-tracking-tool: target query in 0/4 key locations (title, H1, meta, first 100 words), keyword density 0.55%
• https://ziptie.dev/blog/best-perplexity-rank-tracking-tools-for-brands-in-2026/: target query in 0/4 key locations (title, H1, meta, first 100 words), keyword density 0.71%

This report combines empirical Google ranking data (n=2,663) with AI citation findings (n=3,251). Where Google and AI optimization conflict, both signals are presented so you can make informed trade-offs.

D10: Off-Site Citation Strategy

Based on actual AI citation data from scrapes for aiplusautomation.

1. Authority & Review Site Opportunities

These domains are actually being cited by AI platforms when answering queries about your market. Ranked by citation count:

Citation Landscape by Domain Type

• Other (2305 citations): onely.com, ziptie.dev, spicymargarita.co, wellows.com, aiclicks.io
• Ugc (438 citations): reddit.com
• Video (265 citations): youtube.com
• Social (159 citations): linkedin.com

Priority Actions

2. YouTube Strategy

YouTube appears in your citation data (265 citations, platforms: chatgpt, google_ai, perplexity). Typically cited by Google AI Mode and Perplexity, NOT ChatGPT or Claude.

Recommended Video Types

1. 'Best Do You Know Which AI Bots See Your Client's Site? Services 2026' roundup — 42% of YouTube citations come from discovery queries
2. Service walkthrough/case study — 'How AI Plus Automation Do You Know Which AI Bots See Your Client's Site? Helped [Client Result]'
3. Comparison — 'AI Plus Automation vs [competitor]' for Do You Know Which AI Bots See Your Client's Site?
4. 'Is AI Plus Automation worth it in 2026?' — matches validation query patterns (22%)

YouTube Technical Tips

• Add chapter timestamps for key product/service mentions (17% of citations include timestamp parameters — AI cites specific moments)
• Don't ignore Shorts — 17% of YouTube citations are short-form vertical video
• YouTube works on 2 platforms (Google AI Mode + Perplexity), not ChatGPT/Claude
• Title format: include year ('2026') and query-matching phrases

3. Reddit Presence

Reddit holds 51.8% of Google Top-3 positions for commercial queries AND is cited at 17-44% rates across AI web UIs.

• Strategy: Be the recommended answer in relevant subreddit threads
• Reddit ranking is determined by subreddit authority, NOT thread content
• Niche subreddits (avg position 2.0) outrank broad ones
• This requires genuine community participation, not self-promotion
• Timeline: 6-12 months for training data effect on AI platforms

4. Summary Action Plan

Off-site strategy complements on-site optimization. On-site determines whether YOUR pages get cited. Off-site determines whether your BRAND gets mentioned in AI answers. Both matter for GEO.

Changes Since Last Report

This section compares which websites AI tools linked to in the last report vs this report. "Gained" means a new website started getting mentioned. "Lost" means a website stopped being mentioned.

New Websites AI Started Recommending

Websites AI Stopped Recommending