I founded Kukuyeva Consulting to meet you where you are (no company/data too small) and improve your product market fit by leveraging data to understand how your customers are using your product(s), to help you identify the most valuable and loyal customer base, improve your product and scale the business -- and avoid very costly mistakes I’ve seen companies make time and time again.
Here's my roadmap for systematizing product market fit.
It’s impossible to get insights from data you didn’t collect. Having mentored, advised and consulted for 50+ companies that are trying/are data-driven, I recommend that you have a (loose) data strategy ASAP -- ideally, with your alpha users, but it's not too late to start now -- because it becomes exponentially harder and more expensive to catch up. I'm here to help you get started!
When I was at a top consulting firm, my colleagues and I executed multi-year -- multi-million dollar -- digital transformations to help Fortune 500 companies begin making near-real time decisions based on data for the very first time. Let's get started earlier, and avoid these costly mistakes.
You've spent time and money to develop your product and market it, to get prospects to your door. Do you know who's going inside and what your customers are doing once they get there? Do you need an expert to guide you?
For the past 10 years, I've helped companies of all shapes and sizes (from solopreneurs to international corporations) start from the very beginning, and refine their product market fit in virtually every industry: IoT, fashion, hospitality, internet and social networks, healthcare, finance, market research and online advertising, including:
Reduced product risk and increased revenue streams for therapeutic device start-up by advising founders to scope down offering from smart apparel to HaaS
Developed and implemented novel performance metrics to evaluate quality of network connectivity for online gaming start-up with terabytes of data
Identified areas of missed revenue opportunities, by understanding nuances of how customers choose what to buy, for fashion subscription box from 10K+ customer reviews
Do you need someone who's vendor-agnostic? Because I've seen it all... Happy to talk through pros/cons of different tech stacks/implementations.
I have a PhD in Statistics from UCLA, where I developed a novel image compression algorithm and uncovered similarities between two storms on Jupiter -- a finding confirmed by NASA’s Juno mission 6 years later.
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