Inside the tool
A real BuzzView analysis in this category
commercetools’s AI visibility across ChatGPT, Google AI Overviews & Perplexity — one of the brands tracked in this category, straight from the live tool.
We sent 44 real buying questions to ChatGPT and Google AI Overviews – the questions online retailers actually ask. Then we counted which providers get named, and how often. The result is a ranking built from real AI answers, not opinion.
Shopify (9.3%) and Shopware (7.9%) dominate the answers – the remaining 135 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 44 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 competing in e-commerce platforms.
Across 44 real buying prompts sent to ChatGPT and Google AI Overviews, AI systems named 135 distinct e-commerce platforms. That number alone should stop any marketer in their tracks: the AI-visible competitive landscape in this category is not a handful of names — it is a sprawling ecosystem of over a hundred brands all competing for the same recommendation slot. The sheer breadth of the category means that AI systems are drawing from a very wide training corpus, pulling references from developer communities, review aggregators, analyst reports, and vendor documentation all at once.
And yet, concentration still emerges at the top. The six most-mentioned platforms — Shopify, Shopware, Adobe Commerce, SAP, WooCommerce, and Xentral — together account for 202 of the 558 total brand mentions, which is roughly 36%. That leaves 64% of all AI mentions distributed across 129 remaining providers, including the 123-strong long tail that collectively draws 269 mentions. This is a classic power-law distribution: a steep drop-off from the leaders, then a very wide, flat tail of smaller players each earning only occasional references.
For brands in this space, the structural dynamic mirrors the broader e-commerce platform market itself: a small number of dominant, general-purpose platforms (Shopify and Shopware leading the pack) coexist with a large number of specialized tools serving specific verticals, order volumes, or technical architectures. AI systems have learned this market structure and replicate it faithfully in their recommendations. A brand like WooCommerce gets named because it is ubiquitous in the WordPress ecosystem; commercetools gets named because it is the default reference for headless commerce architecture discussions.
The implication is that winning the AI visibility game in e-commerce platforms does not require displacing the giants. It requires becoming the undisputed answer for a specific sub-question: best platform for multichannel retail, best ERP-integrated shop system for mid-market, best headless platform for enterprise. The long tail of 123 providers proves that AI will name very specific tools when the prompt is specific enough — and that specificity is exactly where challenger brands can carve out disproportionate share.
With 135 providers named and only 36% of mentions concentrated at the top, this category rewards vertical specialization — brands that own a specific use-case conversation earn consistent AI mentions even if they cannot challenge Shopify or Shopware on breadth.
Among the eleven tracked providers, the visibility scores reveal a dramatic spread. commercetools and plentymarkets both achieve a perfect 100% visibility score, meaning they are named by AI in response to every prompt type where they are a plausible answer. At the opposite end, ePages and Makaira score just 37.5% — present in fewer than half of the relevant prompt types. That 62.5-percentage-point gap between the top and bottom performers is not random noise: it reflects fundamentally different levels of AI-accessible content density surrounding each platform.
What drives visibility at 100%? For commercetools, the answer lies in its dominance of the headless and composable commerce narrative. The platform has invested heavily in developer documentation, published extensively in technical media, appeared in Gartner and Forrester analyses, and been a fixture in comparison articles on high-traffic review platforms like G2 and Capterra. plentymarkets achieves the same result through a different route: deep integration with the German-language e-commerce media landscape, strong presence in marketplace and multichannel commerce discussions, and a large, active user community generating organic content.
For ePages and Makaira, the lower scores reflect a content surface area problem. Both platforms have genuine product differentiation — ePages serves small- and medium-sized retailers through hosting partner networks, Makaira delivers powerful search and merchandising layers — but neither has built the volume or variety of publicly accessible content that AI systems index at training time. When AI cannot find multiple independent sources discussing a platform in a given context, it simply omits it, regardless of how good the product actually is.
The lesson from this range is that AI visibility in e-commerce platforms is driven by documented presence, not product quality alone. Technical documentation that developers actually use, comparison content that appears on trusted review sites, and analyst recognition all feed directly into how often a platform surfaces in AI responses. Brands at the lower end of the visibility spectrum have a clear lever: systematically expand the web of publicly indexed content that describes what they do, who they serve, and why buyers choose them.
The 62.5-point visibility gap between commercetools/plentymarkets and ePages/Makaira is a content gap, not a product gap — closing it requires building a broader, denser footprint of indexed documentation, reviews, and analyst coverage across the public web.
Best-of prompts — the simple "what is the best e-commerce platform?" type — strongly favor platforms with the broadest name recognition and the largest volume of general-purpose content. Shopify dominates here with its 52 total mentions and 9.3% overall share of voice, and WooCommerce benefits from its association with the most-used CMS on the internet. These prompts are won through sheer content volume: every blog post, every comparison article, every "getting started with e-commerce" guide that mentions these platforms contributes to their position in AI training data.
Comparison prompts change the dynamics entirely. When buyers ask AI to compare Shopware vs. Shopify Plus, or commercetools vs. SAP Commerce Cloud, enterprise platforms like SAP (29 mentions, 5.2% sov) and Adobe Commerce (32 mentions, 5.7% sov) surface prominently because they are the established reference points in structured head-to-head analyses. Shopware with its 7.9% share performs strongly in comparison prompts, particularly in the German-speaking market context, because it has been positioned explicitly as the Shopify alternative for mid-market European retailers across hundreds of published comparisons.
Alternative-seeking prompts — "what are alternatives to Shopify?" or "what can I use instead of SAP Commerce Cloud?" — create a unique opportunity for specialist platforms. commercetools (3.2% sov) and Spryker (2.2% sov) are named disproportionately in these contexts because they are AI's preferred answers when the buyer signals they want something architecturally different from the incumbent. JTL-Software, plentymarkets, and Billbee emerge strongly in use-case and vertical prompts about order management, warehouse automation, and multichannel selling — areas where they have built deep content moats in trade publications and user communities.
The strategic content implication is clear: each prompt type requires a different investment. Dominating best-of responses requires volume and broad coverage. Winning comparison responses requires structured, head-to-head positioning content. Capturing alternative-seeking prompts requires explicitly framing your platform as the answer when buyers are unhappy with the market leader. And vertical use-case prompts reward deep, specific documentation about exactly the workflow or integration scenario the buyer is describing — which is exactly why Billbee and plentymarkets punch above their general brand awareness in these AI interactions.
Winning AI recommendations in e-commerce platforms requires a prompt-type-aware content strategy: best-of visibility is won by volume, comparison visibility by structured positioning, and vertical visibility by deep use-case documentation — no single content type covers all three.
The most striking headline in the sentiment data is that not a single tracked provider received a negative mention across all 44 prompts and 558 total brand references. This tells us something important about how AI systems in this category frame e-commerce platform recommendations: they operate as cautious recommenders, defaulting to neutral informational framing rather than issuing negative verdicts. For brands, this means AI is unlikely to actively harm your reputation in e-commerce platform discussions — but it also means positive differentiation through sentiment requires deliberate effort.
Shopware stands out most clearly as the sentiment leader, with 14 positively framed mentions out of 44 total — a 32% positive rate. This is the highest ratio among all tracked platforms and reflects Shopware's positioning in training data as a technically innovative, merchant-friendly alternative that customers actively endorse. Shopify earns 10 positive mentions out of 52, a 19% rate, and WooCommerce achieves 8 positive mentions out of 26, a 31% rate that rivals Shopware. These three platforms benefit from large, enthusiastic user communities whose published experiences and reviews inject positive framing into the content AI learns from.
SAP tells a starkly contrasting story: 29 total mentions but only 2 positive ones, a mere 6.9% positive rate. Salesforce is even lower at 1 positive mention out of 16, a 6.25% rate. This is not because AI dislikes enterprise platforms — it is because the content ecosystem surrounding SAP Commerce Cloud and Salesforce Commerce Cloud skews heavily toward technical evaluation, implementation complexity, and cost discussions, all of which generate neutral or analytical rather than enthusiastic framing. Enterprise platforms are described, not celebrated, in the training corpus that AI learns from.
What drives positive sentiment in this category? Primarily customer success stories, third-party validation from trusted review platforms, and the presence of enthusiastic communities that publish use-case-specific endorsements. Platforms like Xentral and commercetools earn positive mentions in the 21-22% range by cultivating exactly this type of content: case studies from specific industries, partner ecosystem testimonials, and community-generated how-to content that AI reads as evidence of genuine user satisfaction rather than vendor-produced marketing material.
With no negative mentions in the dataset, sentiment competition is entirely about positive vs. neutral framing — and the brands earning the highest positive rates (Shopware, WooCommerce, Shopify) do so through community-generated content and third-party success stories, not through their own marketing materials.
A mature AI search category looks like cybersecurity or cloud infrastructure: a very small number of names (three to five) dominate across virtually all prompt types, and the long tail is thin. An emerging category looks like the opposite: chaotic fragmentation, with no clear consensus leaders and AI systems essentially listing any tool they can find. The e-commerce platforms category sits in neither extreme — it is in what we call active development, where two or three names have achieved clear dominance, a meaningful mid-tier of seven to ten platforms is establishing stable positions, but over a hundred other providers still compete for the scraps of a highly fragmented long tail.
The evidence for active development is visible in the data structure itself. Shopify leads with 9.3% share of voice, but that is a modest lead over Shopware at 7.9% — far less dominant than what you see in truly mature AI-search categories, where the leader might hold 25-30% share. The visibility scores of the tracked firms range from 37.5% to 100%, indicating that positions are not yet locked in. A platform like Gambio at 50% visibility or Frontnow at 50% visibility has genuine room to grow its AI presence with the right content investments — it has not been permanently eclipsed the way a late entrant to a mature category would be.
The composition of the named provider set also reflects the market transition this category is undergoing. Traditional monolithic platforms (SAP Commerce Cloud, Adobe Commerce) coexist with modern API-first and headless architectures (commercetools, Spryker, Frontnow), ERP-integrated solutions (Xentral, JTL, plentymarkets), and open-source and developer-first options (WooCommerce). AI systems are faithfully replicating this market transition in their recommendations, which means the category's AI visibility landscape will continue to shift as the market shifts, with headless and composable architectures likely gaining ground over the next two to three years of AI training data cycles.
For brands that want to build AI visibility now, the active development phase is actually the best possible moment to act. Positions are not fixed. The 135 providers competing for attention means the content landscape is still forming, consensus recommendations are still being written, and authoritative comparison content that does not yet exist can still be created and indexed. Brands that publish deeply informed, independently credible content in the next twelve to eighteen months — content that AI can draw on when a buyer asks exactly the right question — are building assets that will compound in value as AI search matures and becomes an even larger share of the discovery journey for e-commerce technology buyers.
The e-commerce platforms category is in active AI-search development — positions are not fixed, the mid-tier is still contestable, and brands that invest in authoritative, indexed content now will compound their AI visibility advantage as the category matures over the next 12 to 18 months.
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.
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commercetools’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.
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