Inside the tool
A real BuzzView analysis in this category
Pricefx’s AI visibility across ChatGPT, Google AI Overviews & Perplexity — one of the brands tracked in this category, straight from the live tool.
We sent 12 real buying questions to ChatGPT and Google AI Overviews – the questions businesses in this category 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 (9.9%) and Pricefx (8.1%) dominate the answers – the remaining 43 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 12 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 this space.
Across 12 real buying prompts, AI models collectively named 43 distinct providers in the Pricing & Planning Software space. That is an exceptionally high number for a B2B software niche and points to something important: AI does not treat this as a settled, winner-takes-all market. With 111 total brand mentions spread across four dozen names, the average provider appears in fewer than three prompts. The long tail is real, and it is large — 31 providers share 46 mentions collectively, which represents 41.4% of all AI attention.
The top six providers — SAP (11 mentions, 9.9% SoV), Pricefx (9 mentions, 8.1%), Oracle (8 mentions, 7.2%), Jedox (7 mentions, 6.3%), Anaplan (5 mentions, 4.5%), and PROS (4 mentions, 3.6%) — together account for 44 out of 111 mentions, or 39.6% of total voice. In more mature software categories, the top three alone often command 50-60% of AI mentions. Here, even SAP, the category's most-mentioned brand, sits at less than 10%. This tells us that AI models have absorbed a genuinely diverse set of vendor signals and refuse to collapse the category into a shortlist of two or three names.
The reason for this fragmentation is structural. Pricing & Planning Software is not a single market — it is a cluster of adjacent but distinct use cases: enterprise FP&A, dynamic retail pricing, B2B price optimization for manufacturers and distributors, and AI-driven demand planning. SAP and Oracle dominate the ERP-adjacent planning space. Pricefx and Vendavo serve B2B price management for industrial companies. Competera, 7Learnings, and Omnia Retail live in e-commerce dynamic pricing. Jedox and Anaplan sit at the intersection of financial planning and driver-based modeling. AI faithfully reflects this market structure rather than flattening it.
For a brand in this space, this fragmentation is simultaneously an opportunity and a threat. It means there is no entrenched AI monopoly to unseat — no single vendor has locked in the AI recommendation engine the way Salesforce has in CRM or HubSpot has in inbound marketing. But it also means that earning share of voice requires a sustained, multi-signal presence across the distinct sub-niches of the category. A vendor that is well-known in FP&A circles may be completely invisible in AI responses about dynamic retail pricing, even if they technically serve both markets.
No single brand dominates AI-recommended Pricing & Planning Software — the 43-provider field means new entrants can realistically earn top-10 AI visibility with a focused, consistent content strategy targeting their specific sub-niche.
Among the three tracked providers in this study, the visibility scores reveal a striking divide. Pricefx and Jedox both achieve 87.5% AI visibility — meaning AI models surface them in response to nearly nine out of ten relevant prompts. 7Learnings, by contrast, achieves 25.0% visibility, appearing in only one out of four relevant conversations. This 3.5x gap is not a reflection of product quality or market presence; it is a reflection of AI training signal density and the way those signals are distributed across the broader web.
What drives high visibility in Pricing & Planning Software specifically? Analyst report coverage is a primary factor. SAP, Oracle, Pricefx, and Jedox all appear in Gartner Magic Quadrants, Forrester Waves, and G2 category reports that AI models treat as authoritative signals. These structured, third-party validations create a rich base of indexed content that consistently links brand name to category keyword. Jedox's 87.5% visibility despite a lower absolute mention count than SAP or Oracle suggests that analyst coverage can outpace raw brand size when it comes to AI visibility in niche enterprise software.
For 7Learnings, the 25% visibility score reflects its narrower positioning. The company is a dynamic pricing specialist for e-commerce and retail — a genuine use case, but one that AI models encounter primarily in the subset of prompts that explicitly mention dynamic pricing or AI-driven price optimization. When a buyer asks a broader question about "pricing software for manufacturers," 7Learnings simply does not appear in the AI's training signal for that use case. This is not a brand awareness problem in the traditional sense; it is an AI coverage problem rooted in which content categories and prompt contexts the brand has established a presence in.
The lesson from this visibility range is that the path from 25% to 87% visibility does not require becoming a larger company — it requires expanding the surface area of AI-indexed content. This means publishing detailed use-case pages, getting listed in software comparison directories that AI models consistently cite, earning coverage in category-spanning analyst reports, and generating third-party reviews that connect the brand name to a wider variety of pricing and planning contexts. For 7Learnings, even appearing in two or three additional comparison articles that mention it alongside Pricefx and Competera in the same breath could meaningfully shift its AI visibility score.
The 62.5-percentage-point visibility gap between the leaders and 7Learnings is driven almost entirely by analyst coverage and cross-context content — not company size. Closing that gap is a content investment problem, not a product problem.
Not all AI prompts are equal, and the Pricing & Planning Software data reveals how dramatically winner sets shift depending on how a buyer frames their question. Best-of prompts — "What is the best pricing software in 2026?" or "What are the top FP&A tools?" — consistently surface the largest, most broadly known brands. SAP and Oracle dominate these responses because AI models equate broad brand recognition with category authority. These two companies have produced such a large volume of indexed documentation, customer case studies, and analyst citations that AI treats them as default answers to any general planning-software question.
Comparison prompts — "SAP vs Pricefx," "Jedox vs Anaplan," "Pricefx vs PROS" — produce a very different winner set. Specialist vendors like Pricefx, Jedox, and Anaplan gain substantial ground here because they have invested heavily in versus-page content, feature comparison tables, and positioning documents that AI models treat as relevant when a buyer is already in evaluation mode. Jedox in particular benefits from a strong comparison content strategy, appearing frequently in head-to-head contexts even against vendors with far greater brand recognition globally. The sample prompts in this study — including "Vergleiche Jedox, SAP Analytics Cloud und Oracle Planning Cloud" — confirm that three-way comparisons are a real buyer behavior in this category, and brands that have indexed content for those specific matchups earn disproportionate visibility.
Alternative-seeking prompts — "What are alternatives to Competitive Pricing Solutions?" or "What can I use instead of SAP for price optimization?" — open the door for mid-tier and emerging vendors. PROS, Vendavo, Zilliant, and Competera appear most frequently in these responses, because buyers asking for alternatives are signaling dissatisfaction with the incumbent and a willingness to consider lesser-known names. AI models have absorbed enough comparison and review content about these vendors to serve them as credible alternatives in this context. Use-case and vertical prompts — "Best dynamic pricing tool for e-commerce," "AI pricing for manufacturers and distributors in Germany" — are where 7Learnings, Omnia Retail, and Competera earn their mentions.
The strategic implication is clear: a single-format content strategy will only win a single prompt type. A brand that publishes only product pages and case studies will appear in best-of questions but disappear in comparison and alternative-seeking contexts. A brand that wants to appear across all four prompt types needs distinct content assets for each: authoritative overview pages for best-of queries, detailed versus pages for comparison queries, "alternatives to X" positioning content for alternative-seeking queries, and deep vertical use-case documentation for industry-specific prompts. In Pricing & Planning Software, where the buyer journey is long and multi-touchpoint, this multi-format presence is the difference between appearing in 25% of relevant prompts and appearing in 87%.
Each prompt type surfaces a different winner set — brands that build content assets for all four prompt types (best-of, comparison, alternative, vertical use-case) systematically outperform single-format competitors across the full buyer journey.
One of the most striking patterns in this dataset is the complete absence of negative sentiment. Every single provider in the leaderboard records zero negative mentions across all 111 brand appearances. This is unusual but explainable: Pricing & Planning Software is a technically complex, high-consideration B2B category where AI models default to describing capabilities rather than expressing opinions. AI is not a review aggregator — it distills the general tone of its training data, and in enterprise software, that data skews toward vendor documentation, analyst frameworks, and professional case studies rather than frustrated Reddit threads or one-star reviews.
Within the neutral-to-positive spectrum, however, meaningful differences emerge. Jedox earns 3 positive and 4 neutral mentions from its 7 total appearances — a 43% positive sentiment ratio. Anaplan achieves 3 positive and 2 neutral mentions from just 5 appearances — a 60% positive sentiment ratio, the highest in the entire leaderboard. Omnia Retail, despite having only 3 total mentions, records 2 positive mentions — a 67% positive rate among a small sample. These high ratios suggest that certain vendors benefit from a disproportionate volume of outcomes-focused testimonial content and third-party validation that AI reads as recommendation-worthy rather than merely informational.
SAP, by contrast, earns only 2 positive mentions from 11 total appearances — an 18% positive sentiment rate. This is not a negative signal; it reflects that most SAP mentions are functional and encyclopedic rather than enthusiastic. When AI models respond to questions about SAP, they describe capabilities, integrations, and market position. When they respond to questions about Anaplan or Jedox, they are more likely to echo the outcomes-focused language from case studies — "accelerated planning cycles," "unified financial modeling," "reduced manual consolidation" — that reads as positive rather than neutral framing. The difference lies not in product quality but in how each vendor's content corpus is weighted toward functional description versus outcome narration.
For brands seeking to increase their positive sentiment ratio in AI responses, the path is clear: invest in third-party validation that uses outcome language. G2 reviews, Gartner Peer Insights submissions, customer success stories published on neutral platforms, and analyst quotes that lead with business outcomes rather than feature lists all contribute to a training signal that AI interprets as positive framing. Importantly, this applies even to categories where no negative sentiment currently exists — earning a higher positive ratio means your brand is described with genuine endorsement rather than merely factual presence, and that distinction influences whether a buyer sees your mention as a recommendation or simply a name on a list.
Anaplan's 60% positive sentiment ratio versus SAP's 18% shows that outcomes-focused customer evidence — not brand size — determines whether AI frames your mentions as a recommendation or a reference. Investing in G2 reviews and case studies pays directly into AI sentiment.
AI-search maturity describes how settled a software category is in terms of which brands AI models reliably recommend, and how confidently they do so. Mature categories — think CRM, email marketing, or project management — show a tight leaderboard where the top two or three players command 50-70% of AI share of voice and appear in virtually every relevant prompt. Emerging categories show extreme fragmentation, low total mention counts, and AI uncertainty about which brands even belong in the category. Pricing & Planning Software sits between these poles, which is precisely what makes it an interesting moment to compete.
The evidence for mid-stage maturity is threefold. First, the category generates 111 mentions across just 12 prompts — a reasonable signal density that indicates AI models have absorbed enough content to answer confidently. Second, there is a recognizable top tier: SAP, Pricefx, Oracle, and Jedox consistently appear, giving the category some shape and predictability. Third, however, no brand exceeds 10% SoV, and 31 providers share 41.4% of all mentions collectively. This pattern — recognizable leaders without a dominant monopoly — is characteristic of a category where AI training data is abundant but not yet consolidated around a clear consensus shortlist.
The bifurcated structure of the market further explains this mid-stage positioning. Pricing & Planning Software is genuinely two markets layered on top of each other: large enterprise planning tools (SAP, Oracle, Anaplan, Jedox, OneStream) serving CFO and FP&A buyers, and specialized pricing optimization tools (Pricefx, PROS, Vendavo, Zilliant, Competera, 7Learnings, Omnia Retail) serving commercial and revenue management buyers. These two buyer personas ask structurally different prompts, which is why AI surfaces such a wide range of providers. A category that serves two distinct buyer types will always appear more fragmented in AI data than a category with a single, unified buyer persona.
What does this mean for brands wanting to build AI visibility now? The mid-stage window is historically the best time to invest. AI training data consolidation typically follows actual market consolidation and content investment — the brands that build the richest, most consistently indexed content corpus over the next 18-24 months are the ones that will appear as the default shortlist when this category reaches maturity. For a specialized vendor like Pricefx or Jedox, the window to lock in a top-three AI position ahead of larger, better-resourced competitors is open today but will narrow as enterprise software giants increase their AI-specific content investment. For emerging players like 7Learnings, the priority is to build cross-context visibility before the category consolidates around names that buyers and AI models already recognize.
Pricing & Planning Software is in a mid-stage AI maturity window where consistent, multi-context content investment can still reshape the leaderboard — brands that act now have a realistic path to top-three AI share of voice before the category consolidates.
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
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.
Pricefx’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
