Nexuscale.ai
The All-In-One Outbound OS: From Beta Audit to Organic Growth Engine
NexusScale is a complete prospecting tool that combines lead search and email sending. Our mission was threefold: defining article topics to rank on Google, tracking down critical logic bugs, and proposing missing features to align with the market.
Content writing
Production & SEO
We didn't just plan; we executed. We wrote dozens of expert articles to fill the auto-generated sitemap. This manual production was the only way to ensure high rankings on specific keywords.
Functional audit
System Integrity
We tested the tool in real-world conditions. Our mission was to find logical inconsistencies and critical bugs in contact management to allow developers to deliver a finished and stable product.
Interface finishes
Visual quality
We combed through the interface. We flagged display errors, translation bugs, and usability issues to ensure the tool looked professional from the very first login.
User analysis
Behavioral research
No more guessing: we installed tools to record user sessions. This allows the team to see exactly where people click, where they hesitate, and where they drop off during sign-up.
Feature proposals
Feature Optimization
We don't just fix what exists. We identify features that are missing compared to competitors (like optional tracking) to ensure the product meets market expectations.
Competitive analysis
Market Positioning
We analyzed market leaders like Apollo and Clay to find their weaknesses. This served as the basis for creating honest comparison pages, designed to convince dissatisfied users to switch tools.
How we work differently
We didn't just audit software, we made the business viable. from writing the content to fixing critical bugs, here is how we prepared the ground.
Defining the editorial strategy in a market saturated by generic content
Building authority with specific, problem-solving content. We refused the standard approach of churning out generic, AI-generated fluff. Since the technical SEO structure was automated, our value lay in defining what to write. We built a content plan rooted in the actual pain points of the modern B2B tech stack. We focused on a library of "Problem Awareness," tackling complex subjects like "Email Warmup Myths," "The Dark Funnel," and the nuances of "Buying Signals." When we did address competitors like Apollo or Clay, we created factual comparison pages. This approach ensures that the auto-generated pages are filled with high-value content that Google actually wants to index.
Catching the safety limit failure
blocking logic errors before they hit the first clients. A working code is not enough; the logic must be foolproof. During our audit of the Beta version, we identified critical flaws that would have been disastrous. For example, the "Safety Limit" feature, designed to restrict the number of contacts per company, was broken. This meant a user could inadvertently spam an entire organization despite their settings. We also flagged severe bugs in the emailing module where French and English text mixed up in the drafts. By reporting these issues early, we ensured the final product was not only functional but safe and professional.
Solving the tracking data dilemma
Re-introducing tracking without killing deliverability. During our audit, we identified several friction points, such as "Open Tracking" being completely disabled. While this protected reputation, it frustrated users who needed data visibility. We proposed a strategic compromise: implementing "Open Tracking" as an optional Beta feature. Similarly, to secure inbox placement, we suggested a Hybrid Drafting Model. We advised against fully AI-generated emails to avoid hallucinations. Instead, we recommended using AI strictly for the personalized hook, while keeping the core sales pitch static. These examples show how we aimed to combine user control with maximum deliverability.
How watching real users struggle transformed the development roadmap
Replacing internal debates with visual evidence. The biggest trap for SaaS founders is believing their interface is intuitive simply because they built it. We put an end to the guessing game by installing Hotjar-style session recordings. This allowed the team to stop guessing and start watching. By viewing the actual user journeys, we saw users getting lost in the "Search Criteria" setup flow, hesitating, and abandoning the process. This visual evidence allowed the team to fix the specific friction points that were blocking user adoption, rather than building new features blindly.