Avoid product ideas which won’t work
PMF
99.9% of product ideas do not work. There’s a concept called Product-Market Fit (PMF). Unless the product hits PMF, the success never happens.
Ultimately, any of the product ideas are just hypotheses. We usually build a prototype called MVP (Minimum Viable Product) and run through long ways of validation to confirm the PMF. However, implementing MVP is already a heavy load, especially for young startups.
This article writes about how to find the right product concept efficiently. It’s not possible to find 100%-sure product concept, but through the thinking process, it’s possible to push it up to 20%-30% possibility of success, by learning patterns of low-quality ideas.
Four typical mistakes
#1: Nice-to-have
The most common mistakes are that the products are just nice to have, not “must-have” for the target users. Nice-to-have products can also be sold, but it can’t be disruptive enough hence not worth investing money and time.
For example, if you invent an eraser which is amazingly smooth with the most advanced nanotechnology, the product inevitably brings benefit to students, but it’s nice-to-have. However, it is not critical to the students.
Even it is nice-to-have for some targets, it could be must-have for some other target users. For example, if the eraser is for architects to make many try-and-error steps, the eraser usability could be critical.
#2: Technology-oriented
Technology is always a great enabler of something, but unfortunately, 99% of us are not smart enough to find the exact problems to solve.
Google Glass is one of the examples. Everybody can agree on the ambition of it, which looks like a great future. They proposed many use cases which sounds compelling, but they couldn’t finally reach to the exact problems which users have.
#3: You don’t genuinely know
People can quickly imagine the chance in some verticals. For example, the medical field is one of the largest industries which may be disrupted by AI technologies. Real estate could also be a great market.
However, in most of the cases, outsiders of the verticals cannot understand the reality of the problems, and hence the product ideas come to be too shallow.
For example, provided that I was a 3D rendering specialist, and I would invent some 3D rendering software which demonstrates furniture placements in my room before purchase. First, for end users, would they want to pay money for this software? A consumer might have the problem of placement imagination, but the pain wouldn’t not as intense as letting me pay for it. Second, then as a furniture shop, would it be necessary? The shop might have other problems, such as logistics, inventory management and so on. The budget to IT solution could never be unlimited, so they might not be able to allocate their IT budget to something not critical.
My problem here was that I didn’t know the furniture retailers well, so I would have come up with some ideas I could do, rather than profoundly understand the pains of them.
#4 Everyone can agree
The e-commerce recommender engine is one of the most typical cases of the problems that everyone agrees. Almost all e-commerce merchants have a revenue problem, and they are starving for solutions. However, nearly none of recommender engine providers could be a unicorn.
Why? Because the problem is too well known. Therefore too many competitions have happened among startups, and even more in-house developments have occurred.
Key success factor
Then what are the good ideas? It’s too difficult to say how to succeed. However, there may be one universal rule.
Most of the good ideas have great secrets that 99% of people do not know.
For example, only patent attornies know about the exact complicated process and critical points of patent applications. It could be a common thing for them, but 99% of us, ordinary people, do not know, then it turns to be a secret.
Secrets stem from the following three things.
#1 High specialty
Lawyer for legal tech. Medical Doctor for MedTech. Ex-CFO for FinTech.
#2 High domain expertise
Only those who experienced the work can understand what happens in the factory.
#3 High market understanding
Change of policy and regulation (GDPR, Blockchain, government support)
What Toyota tries to do now?
Conclusion
It’s almost impossible to come up with great product ideas if the product owners are not familiar with the problems. That is why product owners should focus on what they’re familiar with.
