Case Study | AI Visibility
How a Mid-Market Company Strengthened Organic Search and Became an AI Visibility Leader
BiViSee helped an anonymized mid-market B2B technology company strengthen its presence across commercially relevant searches, expand organic discovery, and establish a leading position in monitored AI-generated answers and recommendations.
- 18.2x increase in Top 3 keyword rankings, from 5 to 91
- 310% increase in organic clicks to priority product pages
- 35.27% AI visibility share, the highest among monitored competitors
Executive Summary
The company had an established presence in its market, but its organic search visibility did not fully reflect the range of problems its technology could solve.
Potential buyers searched for solutions in different ways.
Some looked for specific management systems or software.
Others researched technical capabilities, industry applications, or ways to reduce operating costs.
These searches represented valuable opportunities to reach buyers before they selected which providers to evaluate.
BiViSee focused on strengthening visibility across four commercially relevant areas: decision-stage searches, industry-specific solutions, product capabilities, and practical operational problems.
The approach connected organic search activity with the topics most likely to attract relevant business buyers.
Between August 2023 and June 2026, the number of monitored keywords ranking in Google’s Top 3 increased from 5 to 91.
Organic clicks to selected product pages increased by 310% year over year.
The company also established a strong position in AI-assisted discovery.
By late June 2026, it held the largest share of monitored AI visibility among its tracked competitors, accounting for 35.27% of the measured visibility and generating 97 brand mentions.
The result was a stronger foundation for discovery across both traditional search and AI-generated answers.ries, and recommendations.
Priority topics produced inconsistent brand mentions.
When the company appeared, citations did not always point to the strongest first-party evidence.
Existing SEO activity still generated traffic, but rankings alone could not explain whether the brand was being understood and selected as a source by AI systems.
BiViSee treated the problem as an AI visibility loss caused by fragmented entity signals, weak citation-ready evidence, and gaps between the questions buyers asked and the content the site could substantiate.
The work aligned technical SEO, content architecture, off-site corroboration, and AI answer monitoring around a shared set of commercial topics.
Client Context
The client was an anonymized mid-market company operating in a considered-purchase category.
BuyerThe client was an anonymized mid-market B2B technology company providing systems and software for commercial operations and facility management.
Its solutions helped organizations monitor, manage, and improve operational performance across multiple business environments.
The company served customers in several sectors, including commercial services, retail, healthcare, and multi-location operations.
Buyers typically evaluated different providers, technologies, and implementation approaches before making a purchasing decision.
Their research often started with a specific operational challenge rather than a company name.
Some buyers searched for software or management platforms.
Others looked for solutions designed for their industry or researched ways to improve efficiency and reduce operating costs.
The company needed to become more visible across these different entry points.
Leadership faced an increasingly important discovery question:s compared providers across search engines, industry sources, review platforms, and AI assistants before contacting Sales.
The company had useful expertise and an established website, but its strongest proof was scattered across service pages, articles, customer material, and third-party mentions.
That made the brand harder for machines – and buyers – to evaluate consistently.
Leadership needed a clearer answer to a new discovery question:
When buyers search for the problems we solve, do they find our company early enough to include us in their evaluation – whether they use Google or AI-generated answers?
The starting constraint was limited visibility across commercially relevant searches.
Starting Constraint
The company had valuable technology and industry expertise, but its search presence was not equally strong across the topics connected to its business.
At the beginning of the monitored period, relatively few priority keywords appeared in Google’s highest-ranking positions.
Baseline Metrics
BiViSee found that the issue was not a single technical defect. It was a source-selection problem.
Diagnosis
The diagnostic framework identified five areas requiring attention:
Commercial search coverage
The company needed stronger visibility for keywords connected directly with evaluating and selecting its technology.
Broad informational visibility alone could not adequately represent the commercial opportunity.
Industry relevance
Buyers in different industries often described similar technical needs using different language.
The content strategy needed to connect the company’s capabilities with specific operating environments and business requirements.
Product and solution discovery
Relevant product and solution pages needed stronger visibility for searches describing the company’s capabilities.
This would help buyers move from a specific search to a page directly connected with their needs.
Topic fragmentation
Potential customers researched operational problems from different angles.
Relevant expertise needed to be organized around clear topics that connected problems, solutions, and industry applications.
AI visibility measurement
Traditional rankings and traffic reports could not show whether the company appeared in AI-generated answers or which sources those systems referenced.
A separate competitive visibility measurement was needed to assess the company’s position in AI-assisted discovery.
Actions Taken
1. Prioritized commercially relevant keywords
BiViSee organized SEO priorities around searches with a clear connection to the company’s offering.
The strategy concentrated on decision-stage queries, industry-specific searches, product and solution terms, and practical operational problems.
This shifted the emphasis from keyword volume alone toward searches with stronger potential to attract relevant buyers.
2. Strengthened solution and service visibility
The work prioritized searches associated with evaluating management systems, business software, monitoring capabilities, and technical solutions.
The objective was to improve rankings where potential buyers were researching solutions that matched the company’s capabilities.
By June 2026, several monitored commercial keywords had reached Top 3 positions, including first-place rankings.
3. Expanded industry-specific search coverage
BiViSee focused on connecting the company’s capabilities with the industries and operating environments it served.
The approach strengthened visibility for searches combining a solution category with a particular business context.
By the end of the monitored period, several priority industry-related terms ranked first in Google.
One monitored industry keyword improved from position 64 to position 4.
4. Improved product and solution page discovery
The SEO program focused on bringing relevant search demand to pages where buyers could review the company’s capabilities.
Product pages and solution pages were treated as important destinations for commercially relevant organic visits.
The approach aimed to reduce the gap between what potential buyers searched for and the information available on the website.
5. Strengthened problem-specific content
BiViSee also supported content addressing operational challenges faced by customers in different industries.
These topics helped reach potential buyers who were researching a problem before selecting a specific technology or provider.
The selected problem-focused article group subsequently recorded higher impressions and organic clicks.
6. Connected AI visibility analysis with SEO performance
The measurement framework brought together three data sources:
- Ahrefs: Long-term ranking performance across priority keywords.
- Google Search Console: Organic clicks and impressions for selected page groups.
- AI visibility monitoring: Brand mentions, competitive share of voice, and source-domain citations.
This helped distinguish growth in traditional organic search from the company’s measured competitive position in AI-generated answers.
Timeline
| Phase | Timing | Work and measurement |
|---|---|---|
| Baseline | August 2023 | Established starting rankings across commercially relevant keywords |
| SEO development | August 2023-June 2026 | Developed visibility across solution, product, industry, and operational-problem searches |
| Organic performance validation | March-June 2025 vs. March-June 2026 | Compared clicks and impressions across selected URL groups |
| AI visibility assessment | Late June 2026 | Measured competitive AI visibility, brand mentions, and cited domains |
Results
The long-term SEO program was associated with substantial improvements in the company’s visibility across monitored business-relevant keywords.
Organic keyword visibility increased 18.2x in Top 3
| Ranking level | August 2023 | June 2026 |
|---|---|---|
| Top 3 | 5 | 91 |
| Top 10 / Page 1 | 29 | 139 |
| Top 20 | 36 | 155 |
| Top 100 | 61 | 175 |
The number of keywords ranking in Google’s Top 3 increased from 5 to 91, an 18.2x improvement.
First-page keyword rankings increased from 29 to 139, approximately 4.8 times the original level.
The most significant change was the stronger presence of commercially relevant keywords in the highest-ranking positions.
Organic clicks increased across priority pages
Google Search Console confirmed year-over-year growth across all three selected page groups.
| Page group | 2025 clicks | 2026 clicks | Growth |
|---|---|---|---|
| Solution pages | 35 | 107 | +206% |
| Product pages | 67 | 275 | +310% |
| Problem-specific articles | 57 | 121 | +112% |
Comparison: March 1-June 30, 2025 vs. March 1-June 30, 2026.
Search impressions increased as well:
- Solution pages: 9,880 to 25,400 (+157%)
- Product pages: 9,450 to 17,200 (+82%)
- Problem-specific articles: 65,200 to 123,000 (+89%)
The strongest click growth occurred on product pages, where organic visits increased by 310%.
This demonstrated that improved search visibility was accompanied by measurable increases in visits to pages directly connected with the company’s commercial offering.
The company led its monitored AI competitor set
The AI visibility assessment from late June 2026 showed that the client held the largest share of visibility among the tracked competitors.
| Tracked company | AI visibility share |
|---|---|
| Client | 35.27% |
| Competitor A | 21.45% |
| Competitor B | 16.36% |
| Competitor C | 16.00% |
| Competitor D | 5.45% |
| Competitor E | 2.55% |
The client led its nearest tracked competitor by 13.82 percentage points.
It also recorded 97 brand mentions in monitored AI-generated answers, compared with 59 for the nearest competitor.
This established a leading position within the measured competitive set.
The company’s website was also a leading cited source
The AI analysis measured which domains were referenced as sources in monitored answers.
The client’s website recorded a 25.37% domain citation rate, the highest among the domains identified in the report.
This provided an additional perspective beyond brand mentions.
A mention showed that the company appeared in an AI-generated answer.
A domain citation showed that its website was also being used as a referenced source.
Together, the results demonstrated strong competitive visibility across brand appearances and source citations.
Result: Top 3 keyword rankings increased 18.2x between August 2023 and June 2026.
Organic clicks to selected product pages increased 310% year over year.
By late June 2026, the company held 35.27% of monitored AI visibility, leading its tracked competitor set, while its website recorded a 25.37% domain citation rate.
Measurement Method
Definitions used
The case study combines three separate measurement approaches.
Organic ranking visibility
Keyword rankings were measured using Ahrefs across a selected set of commercially relevant terms.
- Baseline: August 2023
- Final measurement: June 2026
- Metric: Number of monitored keywords ranking in Google’s Top 3, Top 10, Top 20, and Top 100
Organic search performance
Google Search Console measured clicks and impressions for selected URL groups.
- Baseline: March 1-June 30, 2025
- Comparison: March 1-June 30, 2026
- Scope: Solution pages, product pages, and problem-specific articles
Clicks represented visits arriving directly from Google search results, excluding internal website navigation.
AI visibility
The AI assessment measured brand appearances and cited domains within a monitored competitive set in late June 2026.
- AI share of voice: The brand’s share of visibility across the monitored results
- Brand mentions: Counted appearances in monitored AI answers
- Brand presence: 23.72% of monitored answers
- Domain citation rate: 25.37% of monitored AI responses cited the client’s website
The AI measurements provide a competitive snapshot, not a before-and-after improvement rate.
The results establish stronger organic search performance and a leading measured AI visibility position.
They do not independently establish increases in qualified leads, sales opportunities, or revenue.
What Changed Operationally
The engagement created a stronger basis for managing business-relevant discovery across organic search and AI-assisted research.
Related Business Context
Primary business problem: Recovering lost visibility in AI-generated answers and recommendations
Growth System layer: Building stronger visibility and demand across AI-assisted and organic discovery
Capabilities used: Improving how AI systems understand, trust, and cite the brand | Strengthening the organic search signals and content architecture supporting discovery
Relevant audience: Mid-market companies and brands competing for visibility during complex buyer research
Need to recover visibility where buyers now search?
BiViSee can help determine whether the constraint is commercial keyword coverage, source authority, content relevance, technical SEO, or AI visibility.