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FuseDemand Study Reveals SaaS Companies Lose Average $1.39M Annually from Fixable Marketing Friction

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New research from FuseDemand reveals that SaaS companies are losing an average of $1.39 million annually from three fixable marketing friction points: competitors stealing branded search traffic, unreadable website copy, and forms with excessive fields. The study analyzed late-stage US SaaS companies using publicly observable data and found that companies addressing these issues typically see 40% lower bounce rates and 50% higher conversion rates.

FuseDemand released the first-ever study of revenue leaks inside late-stage SaaS companies, revealing that every company analyzed is losing revenue, with average losses of $1.39M annually from three common, fixable marketing breakdowns.

The study analyzed late-stage US SaaS companies using publicly observable data including website analysis, Google search results, and form design.

The study found friction in three areas that quietly drain growth:

  • Competitors stealing branded search traffic – 60% affected
  • Unreadable website copy – 70% affected
  • Forms with too many fields – 35% affected

Also Read: AiThority Interview with Tim Morrs, CEO at SpeakUp

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“We’re seeing companies spend millions on AI while hemorrhaging revenue through basic friction points,” said Larry Jacobs, Owner of FuseDemand. “It’s like installing a turbocharger on a car with flat tires. Teams should first understand where they need to improve, then deploy AI to drive scale. Otherwise, they’re just scaling inefficiency.”

Why It Matters

These friction points are not theoretical, they have measurable impact. Companies that address them typically see:

  • 40% lower bounce rates
  • 50% higher conversion rates
  • Millions in protected search traffic

What the Report Delivers

  • Revenue loss breakdown by industry
  • Proven fixes with measurable results
  • Warning signs checklist
  • A 4-week action plan to stop the leaks

Also Read: Cognitive Product Design: Empowering Non-Technical Users Through Natural Language Interaction With AI-Native PLM

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

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