Why is it used as a term and is it relevant in a new industry like artificial intelligence?
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Having a strong answer to the question of 'product market fit' is a favourite of the 'start up' scene.
Here is one quote:
We argue this consensus is misplaced in early stage industries - and many start ups are entering these new or quickly evolving markets.
Asking an early stage company what their 'product-market' fit is may be apt when the company is entering an existing market with existing competitors with clear strategies and customer segmentation.
Investors can work out what the basis of competition in the market is - what the key purchasing factors are within the industry - and make a call on how existing consumers calibrate their purchasing decisions.
They can then identify where they 'fit in' to the existing market.
But we argue product market fit is not an appropriate metric when determining the potential success of a company that is entering an industry going through rapid transformation or evolution.
Often in early stage markets, the buyers are not aware of the product benefits - there is no identifiable market that can be analysed.
So, by definition, in fast-evolving industries, the very act of defining the market itself can be challenging, and the metrics used to gauge product/market fit may not be well-established or may become quickly outdated.
This can lead to misconceptions about whether a product truly fits the market or not.
Early stage companies in evolving industries must maintain maximum flexibility to ensure they can adapt to market changes. While this may be unsettling to those that believe in business plans and long term strategic planning, this is the reality.
Often when new industries begin, the rules of the game are unknown, the market is unknown - so why pretend you have a perfect pre-defined notion of product/market fit?
At best your product/market fit narrative is a hypotheses, that will be tested in the market. Early stage companies should apply the scientific method - start with a hypothesis, test it, prove it or otherwise, move on or further iterate on the hypothesis.
Product development is an ongoing, iterative process - to suggest you have a well defined 'product market' fit in the early stage of an industry life cycle is a mirage.
You may have a story that could be believable to investors, but forecasting how industries evolve is extremely difficult.
In rapidly changing industries, customer preferences and needs can shift quickly, making it difficult for companies to establish a sustainbale product/market fit.
What may seem like a perfect fit today might become obsolete tomorrow as new technologies emerge and consumer behaviour change.
And even if you achieve 'product-market' fit - what is your sustainable edge? Why cannot incumbents copy you?
Rapidly evolving industries often attract numerous competitors, each trying to establish their own version of product/market fit.
This intense competition can lead to rapid changes in the industry landscape, where a company's perceived product/market fit can be disrupted by new entrants or shifts in competitive strategies.
While achieving product/market fit is a significant milestone for any startup, in rapidly evolving industries, it's crucial for companies to remain agile, continuously adapt to changing market conditions, and not rely solely on product/market fit as a measure of success.
The artificial intelligence has many components to it, and each of them are rapidly evolving. Why pretend that you have a 'product/market' fit, when you do not.
