30 Questions to Validate Your Business Idea & Market

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We all have ideas, that’s the easy part.  Validating, iterating, and executing is the hard part.  Often, we can fall in love with our ideas and lose sight of the customer and market we must ultimately serve.  For your idea to succeed, you need a market and an ideal customer that you can focus your product development on.  As such, in my experience working with thousands of aspiring and experienced entrepreneurs around the world, I have learned that one of the most difficult challenges in taking ideas from concept to creation is taking a few steps back to research and validate the market (problem).

The following 30 questions will help you explore the market, validate your problem/idea, and help you decide whether this is worth pursuing.

  1. What is your idea? State it in 300 characters or less.
  2. Who is the ideal customer for your idea? Be specific.
  3. Be more specific about your ideal customer. What does your ideal customer feel, think, want, and do?
  4. What problem does your idea solve for your ideal customer?
  5. What obstacle are you removing for your ideal customer?
  6. In what way do you make your customer’s life easier?
  7. If you successfully resolve this problem/obstacle, what is the ultimate objective your ideal customer able to accomplish? In other words, what did your ideal customer really want to achieve in the first place?  (hint:  they do not wake up wanting to solve their problem.  They want achieve the goal that the problem is interfering with!)

When I refer to ultimate objective, I am referring to the job that your customer really wants to get done when they run into a problem.  Often, we think our customers only want to solve their problems.  While that is true to an extent, it is important for us to consider that they only want to solve their problems in order to achieve their ultimate objective.  Let’s take AirBnB as an example.  Continue reading

What if IBM’s Watson Was Your Co-Founder?

What if artificial intelligence partnered with entrepreneurs, to validate ideas, hypotheses, and assumptions by conducting a study of all of the information in the world on those topics? That is, crawl the Internet and all relevant databases for every related attempt, study, write-up, article, interview, company, etc. and draw insights and conclusions to a high level of statistical significance.

Artificial IntelligenceConsider that IBM’s Watson Discovery Advisor “builds on Watson’s turbocharged text-mining and identification technology…In its current version, Discovery Advisor is tuned for science, specifically the life sciences and medicine. Beyond mining text, the discovery tool not only finds connections among words but also links related concepts together to generate hypotheses. What might be the right place to look? What path of scientific inquiry is most likely to yield new knowledge?”

What if the Watson Discovery Advisor, or a similar solution, could help entrepreneurs significantly narrow down, to a high level of confidence, the hypotheses, ideas, and assumptions that should be validated further. Essentially, AI would conduct the type of research a human could not by finding every known piece of information on it and indicating which ones deserve further human-led pursuit. This is one example of how humans and AI can work together, as partners, to produce value that could not have existed before. According to a New York Times blog article, John Gordon, VP for strategy and commercialization of Watson, “is confident that Watson can scale up in “co-creation projects with clients that can transform an industry.”

The human must play a critical role in this endeavor by providing the initial hypotheses, that is, knowing what he or she wants, and stating it in a clear manner so that AI can perform the research on already existing content. AI would then return, ranked by measures of confidence, the ideas worth pursuing further thus saving the entrepreneur significant time and money. Furthermore, perhaps AI can even propose follow-up hypotheses and assumptions for additional testing based on what it learned in its initial research.

According to the “Our Cognitive Future” report by IBM, Baylor University leveraged IBM’s Watson to build a system that is “trained to ‘think’ like a human research expert by unlocking insights, visualizing possibilities, and validating theories at much greater speeds…The solution analyzed 70,000 scientific articles on p53 [cancer-related protein] to predict proteins that turn on or off p53’s activity – a feat that would have taken researches years to accomplish without cognitive capabilities.”

What if we designed a similar cognitive “co-founder” for entrepreneurs?