From Services to AI-Powered Insights: Zibble AI's Value-Market Fit Journey

Apr 16, 2026 · Predictable Revenue Podcast
🎧 PodShort 19 min squeezed to 2 AI SprinklerAS Sales Tech
Episode artwork
Olga Voit
Co-founder at Zibble AI
Predictable Revenue Podcast
19 min squeezed to 2
Full episode from Predictable Revenue Podcast
Quotable Moments

It's not really a product market fit that owners and founders need to worry about. They need to worry about value market fit. Do you really understand what value are you delivering?

Olga VoitCo-founder at Zibble AI
08:00

Showing the product was not selling the product. After I talked to like 30, 40, 50 people, trying to understand for this kind of company, for this kind of decision maker, what value this product can bring, then I started selling.

Olga VoitCo-founder at Zibble AI
10:30

I think that product, because the nature of the product is so future-oriented, it's business, this business is way more labor-intensive. They require a lot more passion and energy in general than services.

Olga VoitCo-founder at Zibble AI
15:50
Key Insights
  • Zibble AI originated from the idea that research insights and their delivery to Fortune 500 companies were outdated, leading to the creation of an AI-powered market research company.
  • The name 'Zibble' was chosen to represent the action of quickly getting insights, encouraging users to 'Zibble it' instead of spending time and money on lengthy research.
  • Instead of product-market fit, founders should focus on 'value-market fit,' understanding what value they are delivering to their customers, as the product itself will constantly evolve.
  • A common mistake in using AI for market research is treating AI as a generic expert instead of creating a group of experts representing specific market segments or niches to pressure-test ideas.
  • The initial customer acquisition for Zibble AI came from converting existing service clients into product clients, leveraging established trust and relationships.
  • When demonstrating the product, it's more effective to focus on the value it delivers to the client's business and how it can help them make decisions, rather than just showcasing features.
  • Going from a service-based business to a product-based business requires a significant shift in focus, as it's not possible to maintain the same level of effort for both simultaneously.
  • The next phase for Zibble AI is to evolve its platform into a comprehensive knowledge base that empowers clients to feel more intelligent, creative, and confident in their decision-making.
Metrics Mentioned
  • 3-4 digit monthly fee (Zibble AI's pricing for its product, indicating it's not a cheap solution but aims for accessibility without being perceived as low-value.)
  • 6 recurring clients (The number of recurring clients Zibble AI has acquired since launching its main product in October.)

RevBots.ai View:

  • AI Sprinkler stage: Zibble AI integrates AI into market research without full transformation.
  • Value-market fit aligns with ARM's focus on delivering tangible customer value.
  • Leveraging existing relationships for client acquisition mirrors SaaS Hoarder tactics.
  • Future platform evolution hints at ARM's AI orchestration potential.
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