My framework to achieve product-market fit with 0 industry experience (15k€ MMR)
Disclaimer from author : I'm posting here the part of a Whitepaper most relevant to indie hackers. Our fledgling solar startup is now a 5 figure MRR business and soon (finally) launching a brand. Indiehacker myself when I started 4 years ago, I had no experience in neither software nor energy. The Whitepaper focuses on Digital Microeconomics and Business Strategy, and is inspired by James Clear's quote : « Without a great strategy, hard work becomes a nightmare. »
Success for software start-ups
"There is humility in eagerness to learn" - John D. Rockefeller
Start-ups are human organisations designed to create new products under conditions of extreme uncertainty. This uncertainty arises from a complete lack of both product and market knowledge. Nevertheless, start-ups are catalysts that transform ideas about problems into solutions. Their purpose is to learn how to build a sustainable value creating enterprise that grows.
Software enterprises have no tangible assets on their balance sheet. A digital technology company builds a service that can scale due to technology as opposed to labour hours - companies requiring extra labour hours or material to produce more units of output cannot scale as fast as software. A digital enterprise needs no extra labour hours to scale, has no non-cash receivables nor payables, and holds no inventory (and inventory risk) on its books.
Previously a good plan, thorough market research, and a timeline (ie. a fat business plan) were perceived as signals that an enterprise would succeed. It is tempting to apply this framework to start-ups too, but that doesn't work, because start-ups operate with too much uncertainty.
Instead, all effort that is not absolutely necessary for learning what customers want and need should be eliminated. Unfortunately, learning is frustratingly intangible. Demonstrating progress over months (and years) when one is embedded in an environment of extreme uncertainty demands a rigorous method and actionable metrics.
To face uncertainty start-ups must explore and experiment with hypotheses. A hypothesis is a supposition made on the basis of limited evidence as a starting point for further investigation. Such a supposition appears as a Null Hypothesis; with an Alternative Hypothesis if otherwise.
The founder's vision is actually just a rationalised qualitative conceptual map (ie. theory) that precedes any statistical analytics. Its rationalist not empiricist.
Citation from Descartes' Discours de la méthode
"… the principal precepts of logic :
The first was never to accept anything as true that I did not evidently know it to be so: that is, to carefully avoid haste and prejudice; and to understand nothing more in my judgments than what presented itself so clearly and distinctly to my mind, that I had no occasion to doubt it.
The second, to divide each of the difficulties that I would examine into as many parts as possible and required to best solve them.
The third, to conduct my thoughts in order, beginning with the simplest objects to be known.
And the last, to make everywhere such complete enumerations, and such general reviews, that I was sure of not omitting anything.
… These are long chains of very simple and easy reasons."
The vision ought to then be broken down into its constituent parts. Contingent causal modelling outlines vision into respective hypotheses of principles, assumptions, logical relationships, technicity, regulatory framework, market trends, and above all customer behaviour.
Validated learning is the essential unit of progress for start-ups: "Validated learning is the process of demonstrating empirically that a team has discovered valuable truths about a start-up's present and future business prospects. It is more concrete, more accurate, and faster than market forecasting or classical business planning. It is the principal antidote to the lethal problem of achieving failure: successfully executing a plan that leads nowhere".
Validated learning is backed up by empirical data collected from real customers. As these early adopters interact with the product, they generate feedback (data). This helps in turn gauge interest of customers and enables segmentation of early adopters into groups with similar perceived needs.
Pricing also acts as information capture. Your first product thus also includes price testing. Payments must occur from the get-go (no freemium models!) as this will instantly and directly offer feedback from users. There is no clearer validated learning outcome than a sale.
The pricing mechanism for marketplaces
"There are two kinds of companies, those that work to try to charge more and those that work to charge less. We will be the second" - Jeff Bezos
The supply curve in digital microeconomics is fundamentally different from traditional (industrial) microeconomic theory of the firm. Digital products are free (marginal cost is near zero), perfect (a copy is identical to the original) and instant (distribution is immediate). These properties create a powerful combination.
Digital platforms take advantage of all three characteristics; their marginal cost of access, reproduction and distribution is near zero. Costs are dissociated from revenues : digital platforms have no inventory nor receivables risk.
Thus, the economic interest of a digital platform is to maximise consumer surplus benefit to harness network effects.
π = R - C
Profit (π) is a function of revenue (R) and cost (C).
π = q * (p - cV) - cF
Expanding the equation, profit is a function of price per unit (p) minus variable cost per unit (cV) of all quantity sold (q) subtracting fixed cost (cF).
Digital microeconomics has transformed this equation, however. Prices (p) are low (or can even be free where p=0) and variable costs are lower still. Fixed costs (cF) are also falling thanks to cloud computing infastructure and widespread subscription solutions.
Covering fixed costs requires breaking-even through growth of quantity of units sold (q). As operational expenses increase, more units are needed to cover the fixed cost. The unit economics of one extra unit of quantity (q) must therefore contribute greatly to covering fixed cost. The gross profit per unit of quantity, known as contribution margin, is therefore the key metric to measure the unit economics of the business to scale fixed costs.
Thus, value is only captured through quantity (q), as it costs almost nothing to have more of it (assuming favorable contribution margin). Profit is maximized through sales volume and growth. Hence, the first priority is to maximize the user base.
If pricing (and non-pricing standards) is calibrated towards benefitting the demand-side, two things happen. Firstly, expect higher growth from the demand-side. Secondly, the supply-side will always have an incentive to participate. This is known as "cross-side" network effects - if we attract enough "subsidised" buyers, "cash cow" providers will pay us handsomely to reach them. Demand-side driven growth in volume will always drive subscription-based revenues from the supply-side.
Given the combination of properties of digital microeconomics, digital platforms emerge by best executing a freely functioning pricing mechanism. Prices in marketplaces perform three functions: (i) they transmit information, (ii) they provide incentives to adopt methods that are least costly and create most value, (iii) they determine who gets how much from the generated incomes.
A freely functioning and thus efficient price mechanism is determined by today's and tomorrow's demand and supply. The price mechanism therefore transmits only important information and only to relevant people; it is made most efficient (real-time, transparent, instant, accurate, etc.) by digital marketplaces. Anything that prevents prices from expressing freely the conditions of demand and supply interferes with the transmission of accurate information.
A price mechanism, if free and efficient to transmit information, ipso facto also provides both an incentive to react to the information and the means to do so. An efficient price mechanism provides incentives for the supply-side to improve their offer within the marketplace in order to charge higher prices. Price transparency allow the supply-side to optimise their pricing based on their current competitiveness; price accuracy allows the supply-side to optimise their cost structure.
Ultimately, an efficient price mechanism allows the demand-side to self-select themselves based on their preferences. The demand curve in turn allows the supply-side to further optimise their offer based on demand-side preferences, and so on.
Parallel to the price mechanism's informational role, the marketplace also offers the ability for the supply-side to input additional non-price information (signals of quality, timeliness, intangibles, etc.) to communicate their ability to satiate demand-side preferences.
The best suppliers will earn higher income; the worst will have incentives to improve, or adapt their offer, or leave the market; other ambitious suppliers will desire to enter the market. An efficient marketplace emerges.
The marketplace platform defines the standards for entry, for interfaces, and for interactions. A successful digital platform defined the effort and costs to input information, and the emphasis of some communicated information versus other information.
Trust is essential. Pricing must always be transparent and visible. Always remind users of incoming payments and pro-actively inform of price changes; this will also allow preventive risk management of pricing tactics directly from the user. Any price change or premium positioning must be analysed against growth-maximisation priorities. This will include advocated-based aggressive price discounts (whereby marquee users that are especially important to attracting other users pay less).
That is why demand-side B2C customers should never be charged directly on a digital platform (the demand-side is "subsidized"). This is essential as their presence is highly valued when attracted in volume by the "cash-cow" supply-side customers (B2B professionals).
Obviously, pricing cannot not be static and will evolve. It is essential to continue testing pricing strategies to continue learning about our customers.
To read more on Digital Microeconomics and Business Strategy, find the complete Whitepaper here :
https://solaire-georges.medium.com/whitepaper-digital-business-strategy-c074e132d0b2
It explores the following :
- Success for software start-ups
- The pricing mechanism for marketplaces
- Learning with statistical rigour
- MVP that does not fail
- Data-driven decision-making culture
- Sustaining value creation over time
- Customer is always right
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- Footnotes
Hope you find these insights helpful in your journey !
