Inside the tool
A real BuzzView analysis in this category
ecosio’s AI visibility across ChatGPT, Google AI Overviews & Perplexity — one of the brands tracked in this category, straight from the live tool.
We sent 36 real buying questions to ChatGPT and Google AI Overviews – the questions logistics and supply chain teams actually ask. Then we counted which providers get named, and how often. The result is a ranking built from real AI answers, not opinion.
SAP (5.4%) and DHL (2.8%) dominate the answers – the remaining 188 named providers split what's left. If you're not here, you simply don't exist to AI users. That's exactly the gap BuzzView makes visible.
Share of all brand mentions across 36 prompts (Share of Voice). The longer the bar, the more often AI names the provider – across every question tested.
Behind the ranking — what the numbers actually mean for brands in logistics and supply chain.
Across 36 real buying prompts, AI models named 188 distinct logistics and supply chain providers — a remarkable breadth that reflects just how atomized this market truly is. Total mentions reached 390, yet no single provider came close to dominating the conversation. SAP leads with 21 mentions and a 5.4% share of voice, but that figure alone underscores the challenge: even the biggest name in enterprise software captures barely one in twenty AI recommendations in this space.
Adding up the top six — SAP, DHL, Sendcloud, Oracle, Shopify, and Coupa — delivers only 64 combined mentions, or 16.4% of the total 390. The remaining 83.6% is distributed across 182 other providers, many of which appear just once or twice across the entire prompt set. This is the classic long tail of a complex B2B market, and AI engines are faithfully mirroring it.
The logistics and supply chain sector spans an extraordinarily wide range of sub-verticals: freight brokerage, warehouse management, last-mile delivery, EDI and e-invoicing, food distribution technology, container logistics, procurement software, and 3PL coordination — to name only the most prominent. AI systems are trained on content that reflects this diversity, which means they surface highly specialized tools alongside global platforms depending on how a question is framed.
Unlike, say, CRM software — where a handful of names dominate virtually every recommendation — logistics AI visibility is genuinely fragmented. This means the opportunity for specialist brands is real: in a category where no player holds more than 5.4% SOV, a focused content and PR strategy can meaningfully shift your share of AI recommendations without needing to outspend giants like SAP or Oracle.
With 188 providers named and the top 6 holding only 16.4% of mentions, this category has no dominant AI voice — which means every specialist brand has a realistic path to the top tier with the right content foundation.
Among the nine tracked providers in this study, visibility scores range from a high of 75% (ecosio) down to 25% for Seven Senders, Container xChange, and Scoutbee. That 50-percentage-point gap is not an accident of brand size or marketing budget — it reflects a structural difference in how well each provider's digital presence maps to the way AI models learn about solutions in this space.
ecosio's strong showing at 75% visibility and an 11.8% share of voice is directly tied to its deep investment in technical documentation, EDI standards content, and integration guides. When an AI system is asked about B2B communication automation or e-invoicing for large enterprises in Germany, ecosio's content ecosystem provides clear, authoritative, and crawlable signals that are hard for competing providers to match without equivalent documentation depth.
Choco and Warehousing1, both sitting at 62.5% visibility, follow a similar pattern: they have built category-specific content that answers the exact types of questions buyers ask AI. Choco's focus on food service distribution ordering software, and Warehousing1's positioning around fulfillment and warehouse logistics management, give AI models clean, unambiguous signals about what problem each brand solves.
The brands stuck at 25% visibility — Seven Senders, Container xChange, and Scoutbee — are not obscure businesses. They operate at scale in last-mile delivery, container trading, and supplier discovery respectively. The visibility gap suggests their web presence is either too thin in AI-relevant content formats (comparison pages, structured FAQs, third-party reviews) or too narrow in keyword coverage to surface across the full range of prompt types used in this study.
The 50-point visibility gap between ecosio and the bottom-tier tracked brands is driven by content depth and technical documentation quality — not brand recognition alone. Brands at 25% can close this gap with targeted AI-content investment in their core sub-vertical.
Best-of prompts — "What are the best logistics platforms?" or "Top supply chain tools for enterprises?" — heavily favor established, broad-scope platforms. SAP and DHL surface consistently here because their brand equity and content volume give AI models high confidence when assembling a general-purpose shortlist. Oracle and Shopify also benefit from this prompt type, riding their cross-category software authority into logistics recommendations even when their logistics-specific feature depth is moderate.
Comparison prompts change the picture significantly. When buyers ask AI to compare specific tools — "ecosio vs Tradeshift vs Basware" or "Choco vs TraceLink vs Blue Yonder" — the AI is forced to engage with the differentiated capabilities of each product. Here, specialist brands like ecosio, Choco, and Warehousing1 compete on equal footing because the prompt's frame shifts from general authority to specific functional knowledge. Providers with detailed feature comparison content, integration lists, and use-case documentation consistently outperform in this prompt type.
Alternative-seeking prompts — "What are the alternatives to Tradeshift?" or "Which Sendcloud alternatives exist for e-commerce fulfillment?" — create the most fragmented output of any prompt type. Here, the AI draws from a much wider pool, surfacing niche providers like TIMOCOM (freight exchange), DPD (parcel services), and Coupa (procurement) alongside the usual suspects. Brands that explicitly position themselves as alternatives to category leaders in their web content gain disproportionate visibility in this prompt type.
Use-case and vertical prompts — "Best fulfillment tools for German e-commerce companies" or "EDI solutions for large enterprises" — are where sub-vertical specialists shine hardest. TIMOCOM's freight exchange positioning, Choco's food distribution focus, ecosio's B2B e-invoicing depth, and Warehousing1's fulfillment-center angle each resonate strongly when the prompt anchors to a specific operational context. Brands that have built vertically-specific content libraries are rewarded with higher visibility exactly where it matters most: buyer intent prompts with real purchase decisions behind them.
Winning across all four prompt types requires distinct content strategies: brand authority for best-of lists, feature depth for comparisons, explicit alternative positioning for alternative prompts, and vertical-specific case content for use-case prompts. Most logistics brands optimize for only one of these.
Across the top 12 brands in the leaderboard, not a single provider earned a negative AI mention — but the split between positive and neutral mentions tells a revealing story. Oracle received 8 mentions and Odoo received 5, both with zero positive sentiment and zero negative: every single AI reference to these brands was purely neutral. This pattern is typical of platforms that are mentioned for their market presence and feature breadth, but rarely praised for user experience, outcomes, or customer satisfaction in the source content that AI models learn from.
Sendcloud leads in terms of positive sentiment rate: 4 of its 9 mentions (44%) were positively framed. This aligns with Sendcloud's strong review ecosystem on platforms like G2, Capterra, and Trustpilot, where e-commerce merchants frequently write enthusiastic accounts of shipping time savings and carrier integrations. AI models learn from this review content and carry the positive framing into their recommendations, effectively amplifying the social proof that Sendcloud has built through community-driven feedback.
ecosio also performs well on sentiment: 3 of its 6 mentions were positive, giving it a 50% positive rate — the highest among all tracked providers. The driver here is different from Sendcloud's consumer-review approach. ecosio's positive framing comes primarily from case studies, partnership announcements, and industry analyst content around EDI automation outcomes for large enterprises. When AI reads "ecosio helped a manufacturer reduce invoice processing time by 60%", that outcome framing is reflected in how the brand is characterized in AI responses.
SAP, despite its 21 mentions and clear market leadership in volume, earns positive framing in only 3 of those mentions (14%). The remaining 18 are neutral — informational mentions without qualitative endorsement. This is a known phenomenon for large enterprise platforms: their complexity and implementation cost generate as much cautionary commentary as praise, which smooths out the sentiment signal. For a specialist looking to challenge SAP on AI sentiment, the gap between 14% and 44% positive rates represents a genuine strategic opening.
Volume of AI mentions and quality of AI sentiment are driven by different content types. User reviews and case study outcomes build positive framing; market-presence references build only neutral mentions. Brands that want to be recommended — not just named — need to invest in outcome-driven content and third-party validation.
In mature AI-search categories — think cloud CRM or marketing automation — you typically see two or three brands holding 25-40% of all AI mentions between them, with a steep drop to everyone else. The logistics and supply chain data looks nothing like that. SAP leads with 5.4% SOV, and the concentration drops quickly: by the time you reach rank six (Coupa, 1.8%), you're in statistical noise. This is the signature pattern of an emerging AI-search landscape: broad awareness of many options, but no clear AI-endorsed champions yet.
The 188-provider figure is particularly telling. It means that across just 36 prompts — a relatively small set — AI models collectively surfaced a near-encyclopedic list of logistics tools. This happens when the underlying training data is equally fragmented: trade publications, vendor blogs, G2 category pages, analyst reports, and procurement forum threads all point to different tools for different problems. The AI is accurately reflecting a market that has not yet consolidated around universally recognized leaders in the way that, say, project management or video conferencing software has.
The sub-vertical fragmentation is the key structural driver. Freight brokerage (sennder, Cargonexx, TIMOCOM), food supply chain (Choco), EDI and e-invoicing (ecosio), parcel delivery (DHL, DPD, UPS, Sendcloud), warehouse management (Warehousing1), container logistics (Container xChange), and procurement (Coupa, Oracle, SAP) are all treated by AI as distinct problem spaces. A brand that is dominant in one sub-vertical will rarely surface in prompts from another, which artificially suppresses individual SOV scores and inflates the total provider count.
This immaturity is an opportunity, not a limitation. Categories in this phase of AI-search development are still highly responsive to content investment. A brand that systematically builds authoritative, AI-readable content across comparison pages, use-case documentation, integration guides, and third-party review platforms can move from 25% to 75% visibility — as the gap between ecosio and the bottom-tier tracked brands demonstrates — within a realistic planning horizon. The window to establish category leadership in AI search for logistics and supply chain is open now; it will narrow as the market matures and the early content movers compound their advantage.
Logistics and supply chain is in the early-growth phase of AI-search maturity: highly fragmented, no dominant voice, and maximum sensitivity to content investment. Brands that act now to build structured, AI-optimized content in their specific sub-vertical can realistically establish top-tier AI visibility before the category consolidates.
No wishful thinking: the ranking comes from exactly these prompt types – best-of questions, comparisons, alternatives and use cases.
Visibility score = share of prompts where the provider appears in the AI answer at all. 100% means: present for every relevant question.
See it in action
Track your brand across every AI — automatically. Here's how it works.
1. What is BuzzView?
2. Your Brand vs. Competition
3. From Data to Action
ecosio’s AI visibility across ChatGPT, Google AI Overviews & Perplexity — one of the brands tracked in this category, straight from the live tool.
We set the real search and buying questions of your industry – exactly how your customers actually ask AI.
Every prompt runs against all major AI models. We count mentions, position, sentiment and the cited sources.
You see your ranking, your share of voice and exactly the prompts where competitors win – and you don't.
Run your own industry comparison and see in minutes whether ChatGPT & co. recommend you – or your competitors.
Start Free Trial No credit card · Results in minutes · GDPR-compliant, hosted in Germany
