LASVI | Logistics AI Search Visibility Index | 2026
2026 Edition
The LASVI
Logistics AI Search Visibility Index
We scored 127 logistics companies on how visible they are to AI systems like ChatGPT, Gemini, and Perplexity. Most scored a 2. The companies winning right now scored a 41.
2%
Bottom Quartile
Invisible to AI search
14%
Industry Median
Barely discoverable
41%
Top Quartile
AI-visible leaders
38%
Completely Invisible (Score <5%)
20x
Gap Between Top & Bottom
16%
Actively Targeting AI Search
127
Companies Scored
What is the LASVI Score?
A measure of how often AI systems (ChatGPT, Gemini, Perplexity, AI Overviews) cite, reference, or recommend a logistics company when users ask relevant questions.
How It's Measured
Across 500+ logistics-relevant AI prompts
We submitted 500+ prompts to major AI systems covering common logistics buying scenarios: "best 3PL for e-commerce," "freight visibility platforms," "cold chain monitoring solutions," and hundreds more. The LASVI score represents the percentage of relevant prompts where a company is cited, recommended, or meaningfully referenced in the AI-generated response.
Why It Matters Now
AI search is replacing the top of the funnel
Gartner predicts traditional search volume will drop 25% by 2026 as AI chatbots replace queries. Over half of B2B buyers now ask ChatGPT, Perplexity, or Gemini for vendor shortlists before visiting Google (G2, 2025). AI systems cite only 3-5 sources per query (Superlines, 2026). If your company isn't one of those 3-5 answers, you're invisible to the fastest-growing discovery channel in B2B. The companies scoring 41% in this index are already capturing that demand.
The Scorecard: A LASVI score below 5% means AI systems essentially don't know you exist. Between 5-15% means you appear in some niche queries. Above 20% means AI regularly recommends you. Above 35% means you're a default answer in your category. Only 21% of logistics companies scored above 20%.
LASVI Scores by Segment
AI search visibility varies dramatically by sub-vertical and company size
LASVI by Sub-Vertical
Median scores across 6 logistics segments
LASVI by Revenue Tier
Bottom quartile, median, and top quartile
Sub-Vertical
Bottom 25%
Median
Top 25%
% Scoring >20%
% Actively Targeting AI
YoY Trend
Freight Tech / SaaS
8%
22%
41%
54%
38%
+14pts
Freight Forwarding
4%
15%
32%
28%
14%
+8pts
3PL / Managed Trans.
3%
12%
28%
22%
18%
+6pts
Asset Carrier / Fleet
2%
9%
18%
14%
8%
+4pts
Warehousing / Fulfillment
2%
8%
16%
12%
6%
+3pts
Freight Brokerage
1%
6%
14%
8%
4%
+2pts
The Gap Is Widening: Freight Tech companies are pulling away at +14 points YoY while brokerages are gaining only +2 points. The companies investing in executive thought leadership, editorial coverage, pillar/cluster architecture, and SME-driven content are the ones AI systems learn from. The ones publishing brochureware and press releases are invisible.
What Drives a High LASVI Score?
The content and infrastructure signals that correlate with AI search visibility
Pillar/Cluster Architecture
3.1x
Structured topic authority. LLMs map interconnected content as expertise signals.
Executive Thought Leadership
2.8x
Named-author perspective pieces with operational depth get cited as expert sources.
Editorial News Coverage
2.4x
Covering your vertical like a beat reporter signals real-time industry authority.
Avg Content Depth >1,500 words
1.9x
Long-form with real scenarios and specifics. Thin content gets ignored by LLMs.
SME Interviews & Named Experts
1.7x
Content featuring named subject matter experts gets attributed as primary sources.
Content Velocity >4/mo
1.6x
Consistent publishing cadence signals active authority to AI crawlers.
Content Types That Build AI Visibility
Correlation between content approach and LASVI score
Content Types AI Systems Overlook
Formats that fail to register with LLMs
The Content Playbook: AI systems cite sources that demonstrate operational expertise, named-author authority, and industry-specific depth. Executive thought leadership with real scenarios, editorial news coverage of your vertical, SME interviews, and role-based content that speaks to specific buyer pain all contain the structural richness LLMs pull from. Companies that shifted their content mix toward these formats saw their LASVI score jump an average of 12 points in 6 months. Generic product pages, undifferentiated blogs, and press releases without substance remain invisible.
External validation: The Princeton GEO study found that content with embedded statistics increases AI citation rates by 37%. The 2025 Edelman-LinkedIn report found that 95% of "hidden buyers" say thought leadership makes them more open to outreach, and 79% are more likely to champion a vendor during RFP based on it. This isn't just about AI visibility. The content that AI systems cite is the same content that moves deals.
The Marketing Science Behind LASVI
AI visibility is not an SEO problem. It is a marketing infrastructure problem.
AI Availability: The Third Pillar
Byron Sharp's framework, extended
Byron Sharp (Ehrenberg-Bass Institute) built the foundational model: brands grow through mental availability (being remembered at the moment of need) and physical availability (being easy to buy). In 2025, Sharp introduced a third pillar: AI Availability. The likelihood your brand is recommended by an AI system when a buyer is ready to act. The LASVI score measures exactly this. You are no longer competing for blue links. You are competing for cognitive inclusion in AI's model of your category.
Why Traditional SEO Fails Here
Different game, different rules
Only 12% of URLs cited by ChatGPT, Perplexity, and Copilot rank in Google's top 10. 80% don't rank in Google's top 100 at all. The #1 predictor of LLM citations is not backlinks or keyword rankings. It's brand search volume (0.334 correlation), followed by domain authority and content depth. AI systems understand the web through language and brand signals, not links. This is a marketing problem, not an SEO problem.
Earned Media Share of LLM Citations
25%
Journalistic and editorial sources account for 1 in 4 AI citations (Muck Rack, March 2026)
Non-Paid Sources in AI Answers
94%
Non-paid media sources represent 94% of all AI-cited links. You can't buy your way in.
Third-Party Distribution Lift
239%
Median AI visibility lift from distributing content through news outlets vs. owned channels alone
What This Means for Logistics Companies
The LMA methodology, validated by data
The companies showing up in AI answers are the ones that invested in credible, consistent marketing infrastructure. Not keyword tricks. Not ad spend. They built pillar/cluster content architectures that establish entity authority across their topic domain. They published executive thought leadership with named authors and operational depth. They covered their vertical like a beat reporter through editorial news curation. They created the kind of content AI systems train on and cite: expert commentary, original data, problem-to-solution arcs, and role-based content that speaks to specific buyer pain.
Recall-Bound Growth in the AI Age
Demand Point Constellations meet LLM citation
When a VP of Logistics asks ChatGPT "who's the best 3PL for e-commerce fulfillment," being cited IS being recalled at the demand point. The recall mechanism shifted from human memory alone to human memory + AI memory. Companies with high LASVI scores aren't just visible. They are building retrieval dominance across an expanding set of demand situations. Every piece of thought leadership that connects the brand to a demand point does double duty: strengthening that brand's recall while actively suppressing competitor recall in the same space.
The operating model is the differentiator. AI doesn't reward more content. It rewards better marketing infrastructure. 67% of top ChatGPT citations go to first-hand data and original research. Content with expert quotes and proprietary data shows 30-40% higher visibility. Comprehensive pages that answer the main question plus sub-questions get 40-60% more citations than traditional keyword pages. The question isn't "can AI help us produce more content?" The question is "do we have a marketing system worth accelerating?"
Supporting Benchmarks
The traditional marketing metrics that correlate with (and feed) AI search visibility
Organic Sessions/mo
8,420
Median across all segments
Domain Authority
38
Median. Tech: 46, Brokers: 29
Median CPL (All Channels)
$142
Content-first: $45. Direct: $142.
LinkedIn Engage (Exec)
5.4%
vs. 2.8% company page avg
Mktg Budget (% Rev)
3.2%
Tech: 8.4%. Carriers: 1.4%.
LASVI Score vs. Organic Traffic
Higher AI visibility correlates with higher organic sessions
LASVI Score vs. Inbound Leads
Companies with LASVI >20% generate 4.2x more inbound leads
Supporting Metric
3PL
Broker
Carrier
Tech
W/H
Fwd
All
Organic Sessions/mo
9,800
4,200
6,100
14,600
5,300
7,900
8,420
Domain Authority
39
29
35
46
33
41
38
Content Velocity/mo
3.8
1.6
2.2
6.4
2.0
3.0
3.2
CPL (Google Ads)
$128
$94
$82
$168
$96
$138
$118
LI Engagement (Exec)
5.8%
4.6%
4.2%
6.4%
5.0%
5.6%
5.4%
Newsletter Open Rate
27%
25%
26%
31%
29%
30%
29%
CRM Adoption
58%
38%
48%
82%
44%
62%
58%
Mktg Budget (% Rev)
3.4%
2.2%
1.8%
8.4%
2.6%
3.8%
3.2%
The Maturity Gap
Marketing infrastructure is the single biggest predictor of AI search visibility
LASVI by Marketing Maturity
The jump from Scrappy to Growth Mode = biggest ROI inflection point
Where the Industry Sits
38% of logistics companies have no marketing infrastructure
Maturity Level
% of Companies
Avg LASVI Score
Avg Team Size
Has Content Strategy
CRM Adoption
Inbound Leads/mo
Startup / Scrappy
38%
2%
0.8
12%
28%
4
Growth Mode
41%
14%
3.2
68%
72%
38
Established / Scaling
21%
28%
9.4
92%
94%
142
The Inflection Point: Moving from Scrappy to Growth Mode produced a median 4x increase in inbound leads and a 7x jump in LASVI score within 12 months. The companies that made this leap didn't do it by spending more on ads. They built marketing infrastructure: a CRM, a content strategy, a pillar/cluster architecture, and a system for creating the kind of content AI systems learn from.
What's Your LASVI Score?
We'll run your company through the same 500+ prompt analysis and show you exactly where you stand, what your competitors score, and what content shifts would move the needle fastest.
Takes 48 hours. No strings. Just your score and the data behind it.
Methodology
The LASVI score is calculated by submitting 500+ logistics-relevant prompts to major AI systems (ChatGPT/GPT-4, Google Gemini, Perplexity, and monitoring Google AI Overviews) and measuring the percentage of relevant prompts where a company is cited, recommended, or meaningfully referenced. Prompts cover common buying scenarios, category definitions, comparison queries, and operational questions across all logistics sub-verticals.
Supporting benchmarks are compiled from anonymized marketing performance data observed across 127 logistics, supply chain, and transportation companies between 2021 and Q1 2026. Data sources include Semrush, Google Search Console, Looker Studio, Google Ads, LinkedIn Campaign Manager, HubSpot, Salesforce, and direct operational observation. All company-level data is anonymized.
Companies are segmented by sub-vertical (3PL, Freight Brokerage, Asset Carrier, Freight Tech/SaaS, Warehousing/Fulfillment, Freight Forwarding) and revenue tier (Under $50M, $50M-$250M, $250M-$1B, $1B+). Marketing maturity is assessed on a three-tier scale based on team size, budget, technology adoption, and content strategy.
Produced by The Logistics Marketing Agency | the only marketing firm operating exclusively in logistics, supply chain, and transportation. Our embedded operating model gives us direct access to the marketing infrastructure of the companies we serve. This is real operational data, not survey results.
Supporting Research & External Validation
The LASVI findings align with and are corroborated by the following independent studies and industry research.
The Shift to AI Search
Gartner (Feb 2024): Traditional search engine volume will drop 25% by 2026 due to AI chatbots and virtual agents replacing queries previously executed in traditional search.
Gartner Newsroom →
Orbit Media Studios (2026 Survey):55% of respondents now use AI chat as their primary or frequent research tool. 44% say AI tools have fundamentally changed how they look for information online.
Orbit Media: AI vs. Google Survey →
G2 B2B Buyer Survey (2025): Half of 1,000+ B2B software buyers now start their buying journey in an AI chatbot instead of Google Search. Over half ask ChatGPT, Perplexity, or Gemini for vendor shortlists before visiting search results.
AI Citation Patterns & Content Visibility
Princeton / Georgia Tech GEO Study (2024): Content with embedded statistics saw a 37% increase in AI citation rates. Quotation addition, source citations, and authoritative framing all significantly improve visibility in generative engine responses.
arXiv: GEO Paper →
Superlines / AI Search Statistics (2026): AI systems cite only 3-5 sources per query on average, meaning top-cited brands capture disproportionate traffic. Only 30% of brands stay visible from one AI answer to the next.
Superlines: AI Search Statistics 2026 →
Yext AI Citations Study (2025):86% of citations in AI-generated responses come from sources brands can directly control, including websites, help content, and structured data.
Yext: What Brands Need to Know →
ConvertMate GEO Benchmark (2026): Pages above 20,000 characters get 4.3x more citations. Structured heading hierarchies present in 68.7% of cited pages. Content freshness within 30 days carries a 3.2x citation multiplier.
ConvertMate: GEO Benchmark 2026 →
Thought Leadership & B2B Buying Behavior
Edelman-LinkedIn B2B Thought Leadership Impact Report (2025):95% of hidden buyers say compelling thought leadership makes them more open to sales outreach. 79% are more likely to champion a vendor during RFP if that vendor publishes quality thought leadership. 71% say thought leadership is more effective than conventional marketing at demonstrating vendor value.
Edelman: 2025 B2B Thought Leadership Report →
10Fold Communications (2025): AI-based platforms like ChatGPT and Perplexity are now the second-most common source of qualified B2B leads, behind social media and ahead of organic search, email, and paid media. ChatGPT delivers a 56.3% higher close rate than leads from Google or Bing.
Earned Media, Entity Authority & AI Citations
Muck Rack Generative Pulse (March 2026): Earned media accounts for 25% of all LLM citations. Non-paid sources represent 94% of AI-cited links. Analysis of 1M+ links across ChatGPT, Claude, Gemini, and Perplexity.
Muck Rack: Earned Media & LLM Citations →
Stacker / Scrunch Citation Lift Study (2026): Distributing content through third-party news outlets produced a 239% median lift in AI search visibility vs. owned channels alone. Some cases reached 325%. The key variable was distribution context, not content quality.
Stacker: Citation Lift Study →
Search Engine Land / Byron Sharp (2025): AI Availability is the third type of brand availability, extending Sharp's mental and physical availability framework. Brands now compete for cognitive inclusion in AI's model of their category. Category entry points become prompt patterns, not keyword queries.
Search Engine Land: AI Availability →
Digital Bloom AI Visibility Report (2025): Brand search volume is the #1 predictor of LLM citations (0.334 correlation), outweighing backlinks. Only 12% of AI-cited URLs rank in Google's top 10. 67% of top citations go to first-hand data and original research.
Digital Bloom: AI Visibility Report →
Platform Market Share
Similarweb / Industry Data (2026): ChatGPT holds 68-78% of AI chatbot traffic. Perplexity at 13%. Google AI Overviews appearing in 60%+ of searches. Combined, AI-assisted search now influences a majority of B2B discovery journeys.
AI Search Market Share Data →
