Kiteworks Quadrupled Non-Brand Traffic with Quattr.
Kiteworks Quadrupled Non-Brand Traffic with Quattr.
CloudEagle is a leading SaaS spend management platform that helps enterprises track, optimize, and manage software subscriptions. The platform serves finance and IT teams who need visibility into software costs, vendor usage, and renewal decisions across their organization.
Organic acquisition plays a critical role in CloudEagle’s growth, especially for reaching buyers during high-intent evaluation stages such as pricing comparisons, alternatives research, and vendor shortlisting.
CloudEagle’s SEO lead partnered with Quattr to solve a problem common across B2B content teams: SEO expertise had become the bottleneck.
While the team had strong writers and valuable existing content, every optimization decision required hands-on involvement from the SEO lead. This slowed execution, limited experimentation, and pulled focus away from higher-leverage initiatives like paid acquisition alignment and landing page optimization.
CloudEagle needed a way to scale execution without scaling dependency.
THE CHALLENGE
CloudEagle needed to grow qualified, non-brand organic traffic, but the rules of discovery were shifting.
Buyers were no longer researching exclusively through traditional Google SERPs. AI-mediated discovery via Google AI Overviews, ChatGPT, Perplexity, and other LLMs was increasingly shaping how prospects evaluated software.
To continue growing, CloudEagle needed to:
1. Optimize existing high-authority pages instead of relying on net-new content production.
2. Remove the SEO expertise bottleneck slowing execution across the content team.
3. Build semantic internal connections at scale so search engines and LLMs could interpret CloudEagle’s content as an authoritative knowledge base.
The pages with the most compounding potential, already indexed, already ranking, already earning signals, are also the hardest to optimize.
Refreshing content requires competitive analysis, intent alignment, and internal linking decisions. Without embedded guidance, writers can’t execute these steps independently. As a result, most teams default to publishing new content while their highest-signal pages stagnate.
Beyond Google, CloudEagle’s content needed to perform across AI discovery surfaces.
Without strong semantic connections between pages, LLMs treat content as disconnected assets rather than a unified source of expertise, limiting citations and visibility in AI-native buyer journeys.
THE SOLUTION
CloudEagle deployed Quattr’s GIGA AI SEO Agent to transform optimization from a manual process where writers relied on guidance from the SEO Lead at each step instead of the writers subject matter expertise. They needed a repeatable execution system to maximize throughput.
The GIGA guided workflows took the writers through a step-by-step process after onboarding with Quattr and their SEO Lead. It was clear there was a vast keyword universe hidden that Quattr unlocked.
GIGA provided a structured, step-by-step workflow that removed guesswork for writers:
1. ICP Intent Targeting: Writers identified keywords with the highest relevance and buying intent for CloudEagle’s ICP
2. Multi-Model Competitor Research: Teams analyzed competitors across Google, ChatGPT, and other LLMs using the same buyer queries prospects use
3. Semantic Content Analysis: GIGA surfaced exactly where pages lacked relevance, highlighting topic gaps and optimization opportunities writers could confidently address
Instead of one-off training sessions, CloudEagle embedded SEO expertise directly into the workflow, allowing writers to execute independently.
More importantly, GIGA also automatically identified new internal linking opportunities directly within the natural text of the content.
To solve the discoverability problem, CloudEagle deployed Quattr’s autonomous internal linking API.
The system programmatically connected 33 priority pages into a semantic, demand-weighted link graph based on real user intent. Instead of generic anchors, links were built using actual Google Search Console queries, the same language buyers use when searching.
This created a compounding “halo effect,” where improvements on one page reinforced performance across the entire network.
With execution running autonomously, CloudEagle’s SEO lead was able to step out of day-to-day optimization work and refocus on higher-impact initiatives.
Time previously spent reviewing content updates was redirected toward aligning SEO with paid acquisition efforts, improving landing page conversion performance, and exploring new category opportunities and competitive gaps. SEO shifted from a manual bottleneck to a strategic growth function.
THE RESULT
The impact appeared quickly and compounded through the quarter, validating that execution-led optimization, rather than monitoring alone, drives measurable growth across both traditional search and AI-native discovery.
Within weeks of deploying GIGA, CloudEagle’s optimized pages began surfacing more consistently for high-intent buyer queries. Over the full pilot window, these early gains sustained and expanded.
Across the 12 complete weeks following intervention, organic clicks across the pilot cohort increased from 2.47K to 5.25K, representing a +113% sustained lift.
Importantly, this growth was not driven by publishing more content. It came from optimizing and structurally connecting existing high-authority pages, allowing them to perform better for the queries that matter most to CloudEagle’s ICP.
Beyond traditional search, CloudEagle achieved a significant expansion in AI-native visibility. Their AI Citation Share increased by 3× post optimizations.
This shift indicates a meaningful change in how AI systems surfaced CloudEagle during buyer research journeys. The brand moved from occasional mentions to a reliably cited source for pricing, comparisons, and vendor evaluation.
Crucially, these insights were captured from real consumer-facing AI responses, not simulated prompts or API outputs, aligning measurement with how actual buyers experience AI search.
Key Outcomes
1. Unlocked 328 net-new Page 1 queries that previously drove zero clicks.
2. Captured bottom-funnel demand at scale, with 77% of post-intervention clicks coming from high-intent, consideration-stage searches.
3. Strengthened commercial performance, as pricing, comparison, and buyer-stage content consistently outperformed baseline traffic levels.
Together, these results validated that execution-led optimization, guided by real buyer intent and reinforced by demand-weighted internal linking, can drive measurable growth in both traditional and AI-first search environments.
Previously, everything was flowing from me. I had to give all the keywords, what to do, what topics to use. Now, it's democratized. The writers have become experts with the help of the system.
Quattr's AI-first platform evaluates like search engines to find opportunities across content, experience, and discoverability. A team of growth concierge analyze your data and recommends the top improvements to make for faster organic traffic growth. Growth-driven brands trust Quattr and are seeing sustained traffic growth.
And we’re happy to share the wisdom. Here are some resources curated just for you:
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