AI Visibility in SaaS & Technology: Which Sources Shape Software Recommendations?

When a potential buyer asks ChatGPT “What’s the best CRM for a growing business?” or “Which BI platform should I use?”, the brands appearing in the answer can enter their consideration set. Which sources sit behind those answers? 

Peak Ace’s LLM Industry Benchmark analysed a fixed set of 1,000 commercially relevant prompts across 10 industries in Germany during August 2026. Across Gemini, ChatGPT and Google AI Overviews, we measured which brands show up, which source types are retrieved and how brands are spoken about. Here’s what this standardised snapshot reveals for SaaS & Technology, with a focus on the source mix and its implications for GEO and Digital PR.  

Contents 

• How we conducted our LLM Industry Benchmark 
• AI Visibility for SaaS & Technology: How does it compare to other industries? 
• Which SaaS & Technology brands are most visible in AI? 
• Which Sources Do LLMs Use for SaaS & Technology Questions? 
• How do SaaS & Technology brands become visible in AI? 
• The Full Picture Is in the LLM Industry Benchmark 
• FAQ: AI Visibility in the SaaS & Technology Industry 

How we conducted our LLM Industry Benchmark 

The benchmark is built on a defined methodology: 

• 1,000 standardised bottom-of-funnel prompts across 10 industries, each with 100 commercially relevant prompts. 
• Prompts were split across 10 topic clusters per industry. 
• Four intent types were tested: best/top/test winner, comparisons, pricing/where to buy, and criteria/guidance, with 25 prompts per intent in each industry. 
• The analysis focused on the German market and German-language prompts during August 2026. 
• Gemini, ChatGPT and Google AI Overviews were monitored. Each prompt ran 15 times, five per system. 
• Data was sourced from Peec AI exports; 50 brands per industry were monitored, with reporting focused on the Top 20 by visibility. 
• The three core brand KPIs are visibility, Share of Voice/SOV and sentiment. Visibility measures how often an entity appears in answers for the prompt set; SOV records its share of voice in the monitored dataset; sentiment measures the tone of answers mentioning an entity on a 0–100 scale. For concentration analysis, SOV shares are separately normalised to 100% within the Top 20.  

The source analysis describes retrieval counts and URL types by industry and intent. All results apply to the selected prompts, monitored entities, systems and study period. 

For the full methodology, definitions and cross-industry breakdowns, the complete benchmark is available for download. 

AI Visibility for SaaS & Technology: How does it compare to other industries? 

In our benchmark, comparison pages lead the SaaS & Technology source-type lists for recommendations, comparisons and purchasing questions. How-to guides lead for criteria/guidance. These are also the leading formats across all 10 industries. 

Here’s how the leading source types compare: 

The percentages describe the cross-industry retrieval mix, not SaaS shares. 

The useful distinction is between intents: software-selection questions draw on comparisons, while criteria and guidance bring practical explanations to the front. That gives content teams two different jobs: explain which solution fits, and help buyers work out what they need. 

For additional context, SaaS & Technology records average visibility of 7.7%, compared with 6.94% across all 10 industries. Its reported average SOV is 3.6%, versus 3.72%, and sentiment is 55.4, versus 54.58. Sentiment indicates answer tone within the dataset, not software quality. 

Its HHI is 548, and its Top-3 Share is 24%. HHI measures concentration: higher values mean SOV is distributed less evenly. The three largest SOV contributors account for 24% of the Top-20 total, leaving 76% across the remaining entities. These concentration figures use normalised SOV shares, separate from the reported average SOV above, and are not market shares.  

Which SaaS & Technology brands are most visible in AI? 

According to Peak Ace’s benchmark for Germany in August 2026, the top three entities by visibility in the SaaS & Technology prompt set are: 

• Salesforce: 14% visibility
• HubSpot: 13% visibility
• Power BI: 9% visibility  

Their shared advantage is being an established option for the decision being tested. The white paper explains their prominence through their relevance to commercial questions about CRM and BI selection. Salesforce and HubSpot address the CRM choice; Power BI addresses the business-intelligence choice. Each is a software product that directly fits the kind of recommendation the prompts request.  

The source mix reinforces this focus on evaluation. Comparison pages lead three intent lists. The white paper links this pattern to the nature of standard-software selection: buyers compare products offering similar functions. For competing brands, the practical task is to explain why their product fits a particular need, rather than simply presenting another list of features.  

CRM and BI are different buying decisions, pooled into one industry category here. Assess them separately in your own monitoring so a broad SaaS figure does not obscure the questions relevant to your product. 

Which Sources Do LLMs Use for SaaS & Technology Questions? 

The benchmark analysed which types of content the selected AI systems retrieved when processing SaaS & Technology prompts. 

Note: retrieval records source access, not necessarily a citation or brand mention in the final answer. 

The source mix varies by intent: 

A few things stand out. 

• Comparison pages lead three lists, including pricing/where to buy. Evaluation content features beyond direct “A versus B” questions. 
• Product pages appear in every list and rank second for comparisons and purchasing questions. Product facts remain part of the selection process. 
• How-to guides also appear throughout, leading criteria/guidance ahead of articles. Practical explanations sit alongside product evaluation. 
• Listicles rank second for recommendations, while articles rank second for guidance. Shortlisting and understanding requirements call for different formats. 

What does the source mix suggest? 

• Explain suitability, not just features. Use comparisons to show which solution fits a buyer’s workflow, integrations and requirements. Make the differences between alternatives explicit. 
• Treat pricing as part of evaluation. Comparisons and product pages lead purchasing questions. Review whether buyers can understand plan differences, user limits and billing conditions across both formats. 
• Give buyers a way to assess the software. How-to guides lead guidance questions. A useful next step is content explaining how to test a relevant workflow or assess a reporting requirement, rather than another feature summary. 

How do SaaS & Technology brands become visible in AI? 

The data raises several questions that SaaS and technology marketers should consider: 

• Are you visible on the comparison pages and product sources retrieved for relevant questions? Review the actual pages and domains in your own monitoring. Check whether they describe your product accurately and explain when it is a suitable option. 
• Does your content strategy cover all four intent types? Keep the original decision journey in view: recommendations, comparisons, criteria/guidance and pricing. Pair selection content with practical evaluation guidance. 
• Is your brand represented consistently across relevant sources? Check product names, capabilities, integrations and plan details across your website, comparisons and third-party coverage. Prioritise outdated or conflicting information. 
• Are you thinking beyond your own software website? Coordinate GEO and Digital PR around the sources relevant to your product category. Monitor brand mentions and retrieved sources separately, using a consistent prompt set and reviewing results by intent and system. 

Expert tip: Build authority beyond your own SaaS website

The Full Picture Is in the LLM Visibility Benchmark 

This blog post covers the SaaS & Technology highlights. The full LLM Visibility Benchmark goes considerably deeper: 

• How SaaS & Technology compares with all 10 industries across visibility, SOV, sentiment and dominance 
• The broader visibility patterns – which industries are dominated by a few brands and which offer a more open visibility landscape 
• Differences between intent types – how the source mix shifts depending on whether users ask for recommendations, comparisons, pricing or guidance 
• The complete brand and source-type analysis for every industry 
• Cross-industry insights on what drives LLM visibility and where the biggest opportunities lie 

Download the full LLM Industry Benchmark here. 

Had a look at our benchmark and looking to improve your LLM visibility? Get in touch with our LLMO and GEO team. 

FAQ: AI Visibility in the SaaS & Technology Industry 

How visible are SaaS & Technology brands in ChatGPT and other AI assistants?

SaaS & Technology achieves an average visibility of 7.7% in LLM-generated answers. This is above the cross-industry average of 6.94% within the prompt set and study period used in Peak Ace’s 2026 LLM Visibility Benchmark. 

Which SaaS & Technology brands are most visible in AI search?

According to Peak Ace’s 2026 LLM Visibility Benchmark, Salesforce has 14% visibility, followed by HubSpot at 13% and Power BI at 9%. 

What types of content do LLMs use to answer SaaS questions?

The source mix varies by intent. The benchmark identifies How-To Guides, Product Pages, Listicles, Comparison Pages, Articles and other sources across the four intent types. Comparison and product-oriented content are particularly relevant to software selection and evaluation. 

Does AI visibility matter for SaaS brands?

AI visibility provides another way of measuring how often software brands appear when users ask commercially relevant questions. It should be considered alongside traditional SaaS KPIs such as organic traffic, demos, trials, conversions, customer acquisition and revenue rather than treated as a direct replacement for them. 

How can SaaS & Technology brands improve their AI visibility?

SaaS & Technology brands can improve their AI visibility by mapping the questions their audience asks across recommendations, comparisons, criteria, guidance and pricing. Then assess which sources LLMs retrieve for those questions, develop useful content in the relevant formats, and strengthen your presence on independent third-party sources through Digital PR and broader GEO for SaaS tactics.