How Fenmo AI's Website Increased Enterprise Demo Requests by 189%

The Problem: Selling AI to People Who Don’t Trust AI

Fenmo AI had built something genuinely transformative—autonomous AI “co-workers” that handle repetitive finance tasks like cash application, AR reconciliation, and month-end close. The technology worked. CFOs and controllers didn’t believe it.

The original website’s performance told the story:

• 91% bounce rate from enterprise traffic
• Average of 0.8 demo requests per week despite significant paid media spend
• Sales cycle averaging 6+ months—most of it spent overcoming initial skepticism
• Lost deals to “safer” legacy solutions that finance teams understood

The fundamental problem: Fenmo was trying to sell autonomous AI to the most risk-averse buyers in any organization.

“Finance people have seen too many ‘AI solutions’ that turn out to be glorified spreadsheets,” Fenmo’s CEO explained. “They’re skeptical before they even land on our site. And our website was doing nothing to address that skepticism.”

Understanding the Finance Buyer’s Mind

We spent two weeks interviewing Fenmo’s sales team, reviewing call recordings, and analyzing competitor positioning. The insights reshaped our entire approach:

What Finance Leaders Fear:

1. Errors they’ll be blamed for—AI mistakes become their mistakes
2. Loss of control—Autonomous systems feel like giving up oversight
3. Audit complications—“The AI did it” won’t satisfy auditors
4. Integration nightmares—Their ERP is sacred, don’t break it
5. Job security questions—Will this replace my team?

What Finance Leaders Want:

1. Time back—40+ hours/week spent on tasks that should be automated
2. Accuracy—Fewer manual errors in high-volume transactions
3. Visibility—Better understanding of cash position and AR status
4. Scalability—Handle growth without proportional headcount
5. Control—Final say on everything that posts

The gap was clear: Fenmo’s old website talked about AI capabilities. Finance buyers wanted to hear about control, accuracy, and risk mitigation.

Our Strategy: Trust Before Technology

We rebuilt Fenmo’s website around one core principle: address the objection before making the claim.

Information Architecture for Skeptics

Traditional SaaS sites lead with features. We led with trust:

Section 1: The Problem Validated the pain points finance teams experience daily. When visitors see their exact frustrations described accurately, they know you understand their world.

Section 2: The Solution Framework Introduced “AI co-workers” as teammates, not replacements. Key messaging:

• “Works alongside your team”
• “You approve before anything posts”
• “Full audit trail on every action”

Section 3: How It Actually Works Transparent explanation of the process—no black boxes. Showed exactly how the AI makes decisions and where humans stay in control.

Section 4: Proof It Works Results from real customers, with specific metrics finance teams care about:

• Hours saved per week
• Match rates achieved
• Error reduction percentages

Section 5: Security & Compliance Prominent placement of SOC 2 certification, data handling practices, and ERP integration safeguards. This section would normally be buried—we made it impossible to miss.

Design System for Enterprise Finance

Finance software looks a certain way. Fenmo needed to fit the category while standing out:

Visual Approach:

• Clean, data-forward aesthetic—Charts, metrics, and dashboards prominently featured
• Dark professional palette—Serious enough for finance, modern enough for AI
• Real product interfaces—Actual screenshots showing the control panels and approval workflows
• Process diagrams—Visual explanations of how AI + human collaboration works

Trust Signals Throughout:

• Security badges positioned near every CTA
• “Human-in-the-loop” messaging reinforced at key decision points
• Client logos from recognized companies
• Integration partner logos (ERP systems they already use)

Content Strategy: Show, Don’t Claim

We rewrote all copy to demonstrate rather than assert:

Before:

“Fenmo AI uses advanced machine learning to automate your cash application process with industry-leading accuracy.”

After:

“See exactly how each payment gets matched. Review the AI’s reasoning. Approve with one click—or override with your own allocation. You’re always in control.”

The difference: the first makes a claim. The second shows how control is maintained.

Use Case Deep Dives

Instead of generic capability pages, we created detailed breakdowns for each AI co-worker:

Cash Application Co-Worker:

• Problem: Manual matching takes 15+ hours/week
• Solution: AI matches 94% automatically, flags exceptions
• Control: Every match reviewable, approval required for edge cases
• Result: 40+ hours saved, 99.2% accuracy

AR Reconciliation Co-Worker:

• Problem: Month-end reconciliation is a scramble
• Solution: Continuous reconciliation throughout the month
• Control: Exception reports, approval workflows, audit trails
• Result: 3-day close reduced to same-day

Financial Close Co-Worker:

• Problem: Close process requires manual coordination
• Solution: Automated task management and status tracking
• Control: Human approval at every checkpoint
• Result: 50% faster close with fewer errors

Technical Execution

Performance for Enterprise Standards

Finance teams evaluate vendors on professionalism. Site speed is part of that evaluation:

• Sub-2-second load times on enterprise networks
• Accessibility compliance for large organization requirements
• Cross-browser testing (finance teams often use older browsers)
• Print-friendly layouts for internal distribution

SEO for High-Intent Keywords

We targeted searches from finance professionals actively seeking solutions:

Primary Keywords:

• “Cash application automation software” (890 monthly searches)
• “AI accounts receivable automation” (720 monthly searches)
• “Automated financial close software” (480 monthly searches)
• “AR reconciliation automation” (390 monthly searches)

Content Structure:

• Semantic HTML with proper heading hierarchy
• Schema markup for software products
• Long-form content addressing specific finance challenges
• Internal linking between related use cases

Conversion Path Optimization

Enterprise finance deals require careful lead capture:

• Gated resources—ROI calculators and implementation guides for top-of-funnel
• Demo requests—Streamlined form for bottom-of-funnel
• Contextual CTAs—Different offers based on which AI co-worker page they’re viewing
• Progressive profiling—Capture company size and ERP system for sales qualification

The Results: Trust Converted to Pipeline

Within 90 days of launch, the metrics transformed:

Metric	Before	After	Change
Demo Requests/Week	0.8	2.3	+189%
Enterprise Bounce Rate	91%	52%	-43%
Avg. Time on Site	34 sec	3:12	+465%
Pages Per Session	1.2	4.1	+242%
Organic Traffic	Baseline	+134%	—

Beyond Traffic: Pipeline Impact

The qualitative changes mattered even more:

Sales Cycle Compression: “Prospects now come to demos with half their questions already answered,” Fenmo’s sales lead reported. “The objections we used to spend months overcoming? The website handles them upfront.”

Lead Quality Improvement:

• Higher percentage of decision-makers (CFOs, Controllers) requesting demos
• Better-qualified companies (right size, right ERP systems)
• Faster progression from demo to proof-of-concept

Competitive Positioning:

• Began winning deals against legacy vendors on “ease of implementation” messaging
• Website cited in RFP responses as evidence of modern approach
• Increased inbound from companies who had evaluated competitors first

What This Means for Enterprise AI Companies

Selling AI to risk-averse enterprise buyers requires a fundamentally different approach:

Lead with control, not capability. Your AI might be brilliant. Enterprise buyers need to know they won’t lose oversight.

Address fears before making claims. Security, audit trails, human oversight—put these front and center, not in the footer.

Show the human-AI collaboration. “AI-powered” is a red flag for many buyers. “AI-assisted with human approval” is reassuring.

Design for the skeptic. Your website’s first job isn’t to impress—it’s to reassure. Earn trust before asking for demos.

Specificity builds credibility. “Industry-leading accuracy” means nothing. “94% automatic match rate with full audit trail” means everything.

Fenmo now has a website that does the hardest part of their sales process: turning skeptical finance professionals into believers. That’s the difference between a website that costs you deals and one that closes them.

---

Selling AI to risk-averse enterprise buyers? Let’s build trust together →