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Predictive Analytics for Tobacco Companies
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Inspired by a conversation on:
The Business Brew
Spencer Cibelli - Haypp Group: Nicotine's 'Win-Win-Win' Business
Host: Bill Brewster
Timestamp: 08:00 - 10:00
Found an idea? We can build it for you.
We design and develop SaaS, AI, and mobile products — from concept to launch in weeks.
Direct Quote
"Hape can go to British American and say, Hey, this Velo flavor is really popping off in like this jurisdiction."
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Sign InHow should I validate this saas idea before building it?
2:34 PM
Great question! For a saas idea like this, I'd recommend starting with these validation steps:
- Customer interviews: Talk to Technical to understand their pain points
- MVP approach: Build a simple landing page to test demand
- Competitor analysis: Research existing solutions and identify gaps
Would you like me to help you create a specific validation plan for your high difficulty idea?
2:35 PM
Yes, and what about the technical implementation? Should I build this myself or hire a team?
2:36 PM
Based on your idea's complexity and 6-12 months, here's my recommendation:
Technical Strategy:
- Start with no-code tools for rapid prototyping
- Consider your technical background and available $1,000-$10,000
- Plan for scalability from day one
I can help you create a detailed technical roadmap and resource allocation plan...
2:37 PM
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Sign InSimilar Ideas
Sensory Data Analytics Platform for Cannabis
The idea revolves around creating a sensory data analytics platform tailored for the cannabis industry. This platform would aggregate and analyze sensory data from various cannabis products to provide insights on consumer preferences and trends. By leveraging the existing $8 billion market, the platform could help cannabis producers understand which flavor profiles, aromas, and effects resonate most with their customers. This data-driven approach would not only aid in product development but also improve marketing strategies by aligning them more closely with consumer desires. The platform could utilize machine learning algorithms to continuously refine its recommendations based on new data inputs, ensuring it remains relevant and useful for producers. The target audience would include cannabis producers, dispensaries, and brands looking to enhance their product offerings through sensory insights.