The Day I Learned That Cheap Is Not a Strategy
I presented a pricing strategy for a GTM project during my product internship, and came out with one of the most firsthand learning experiences I could trade from a seasoned entrepreneur.
The task sounded straightforward. Competitive benchmarking. Pricing strategy. Present it to leadership. I had a spreadsheet, a lot of tabs open, and the quiet confidence of someone who has read exactly enough to think they understand something.
So I did what felt like the most logical thing. I looked at every competitor, noted their prices, and built my recommendation around a simple thesis: we should be cheaper than all of them.
Lower barrier to entry. More signups. More revenue. I had even drawn arrows. The arrows were very convincing.
The feedback I got in that room changed how I think about building products entirely.
What They Actually Said
Nobody told me I was wrong harshly. They let me finish, and then started asking questions I did not have good answers to.
Who is this price designed to attract? What does this price communicate before a customer even tries the product? If we start here, where do we go from here, and what kind of customer base are we building along the way?
I had volume projections. Not answers.
The core thing that came out of that conversation was this: your pricing determines your revenue, yes, but more importantly it determines your positioning and the kind of customer you attract. Those two things matter far more in the long run than whatever short-term acquisition bump cheap pricing might give you.
The Filter Nobody Talks About
When you price something low, especially defensively low as in "lower than the competition" as the primary logic, you are not just setting a revenue expectation. You are selecting for a customer type.
And cheap pricing selects for price-sensitive customers. Which sounds fine until you realize that price-sensitive customers are not loyal to your product. They are loyal to the number. The moment a competitor shows up with a lower number, and someone always does, your customer base was never really yours. It was just sitting there waiting for a better deal.
That is not a moat. That is just a countdown.
The Psychology Side of It
Human beings do not experience value objectively. They infer it from signals. And price is one of the loudest signals available before someone has even touched your product.
Cheap triggers doubt before it triggers gratitude. The first instinct is not "great deal," it is "what is wrong with it."
People do not actually want the cheapest option most of the time. They want to feel like they got something genuinely valuable and paid a fair price for it. The first makes you feel like you settled. The second makes you feel like you made a smart call.
This is why a ₹300 Starbucks coffee that probably costs ₹20 to make has no shortage of buyers. The price is part of the product. It tells you something about the experience before you have even stepped inside. The underlying mechanic is the same for anything: pricing shapes perception, and perception shapes the relationship a customer has with whatever you built.
What Shark Tank Kept Reinforcing
Watch enough Shark Tank and once you have had that boardroom conversation, a pattern becomes impossible to ignore. Founders who build their pitch around being the affordable option get a particular kind of wariness from the Sharks. Not anger. Just this quiet "we have seen this before" energy.
Because cheap pricing communicates one of two things: either the founder does not fully believe in the value of what they built, or the margins are already thin enough that the whole business only works if everything goes perfectly forever.
And everything never goes perfectly forever. Costs go up. A well-funded competitor decides to go cheaper and can bleed longer than you can. Suddenly you have no margin buffer, your price-sensitive customers are gone, and your only options are raise prices or quietly shut down.
There is no version of the cheap-first story that ends well unless you eventually transition away from it. Which means the cheap pricing was never the strategy. It was just a delay.
The AI World Is Showing Both Sides of This Right Now
OpenAI and Anthropic both launched at $20 a month. Smart, but not for the reason it seems. That price was never really a pricing strategy. It was a distribution strategy that happened to involve a price. Get the product into as many hands as possible, build habit, find the power users.
But just as investors started nudging Sam Altman to justify the potential trillion dollar valuations, they eventually had to pivot. The $100 and $200 plans are being pushed hard now. Sora quietly wound down, partly to save on compute costs. The low price was a chapter, not the book.
What is interesting is that they can make this transition because they built genuine product dependency first. The price goes up and users follow, because the product became something people actually need. That is the move.
The mistake most startups make is starting cheap without building that dependency, then trying to raise prices later with nothing to justify it except higher costs. Customers do not respond well to "we need more money" as a value proposition.
What I Actually Took Away
I went in thinking pricing was a math problem. Lowest price wins the most customers.
I came out understanding that pricing is a positioning decision that happens to involve math.
The right question is not "what is the minimum we can charge to reduce friction." It is: who do we want as customers, what do we want them to believe about this before they try it, and what does this number signal about what we built.
Price low and the signal is: we are not sure this is worth more. And if you are not sure, there is no reason for them to be either.
Cheapness is not a strategy. It is a starting gun for a race you are already losing.
That is the thing I walked out of that internship actually understanding. Not from a textbook. From presenting a bad idea to people who had seen it fail enough times to explain exactly why.