01 · MARKET & DEMAND
Demand is not simply divided among the companies.
Each quarter begins with a potential market that scales with the number of competitors and grows as the simulation progresses. Potential customers are distributed across five customer groups. Their exact population shares are deliberately not shown for free: teams must use market research if they want better information about the current and next-quarter mix.
The demand engine resolves the market in two stages. First, customers decide whether any available product is attractive enough to buy at all. A No Purchase alternative means weak products do not automatically receive sales just because they are present. Second, customers who are willing to buy are allocated among the competing offers.
02 · CUSTOMER BEHAVIOR
Five customer groups value the same offer differently.
Students, Professionals, Casual Consumers, Fitness Users and Tech Enthusiasts have different purchase activity, feature priorities, willingness to pay and sensitivity to price. Product fit is evaluated relative to each group’s expectations rather than against one universal “best product.”
Expectations rise as the market develops. In longer games, purchase activity can also change after the first year. The customer population itself shifts gradually between quarters while staying bounded, so a strategy that worked early can become less attractive later.
Quality can support a higher acceptable price, but only within limits. Very weak feature fit is penalized so an underdeveloped product cannot inherit normal demand simply because stronger products sell out.
03 · MARKETING, POSITIONING & CHANNELS
Marketing improves an offer; it does not replace one.
Advertising
Advertising has diminishing returns. Repeating the same audience and message across consecutive quarters creates campaign fatigue, so spending more is not automatically the best answer.
Targeting
Specialist targeting improves positioning with relevant customers, but several companies chasing the same specialist audience create mild competitive crowding.
Distribution
Wholesale improves reach while direct-to-consumer sales improve margin. Mixed-channel strategies can create an omnichannel benefit, while very high direct-to-consumer volume creates additional fulfillment burden.
Brand memory
Awareness, reputation, satisfaction, customer ratings and word of mouth persist between quarters. Their effect is intentionally bounded so brand cannot overwhelm product, price and execution.
04 · OPERATIONS & INVENTORY
Production creates a real capacity and cash problem.
Manufacturing budget is converted into whole units using the product’s manufacturing cost. Pushing production above the factory’s efficient capacity creates overtime pressure: unit costs rise and defects increase. Quality-control spending and factory capability reduce defects, but both consume cash.
Unsold inventory can carry into the next quarter up to the factory’s storage limit. Older inventory becomes less valuable when sold and can weaken the customer experience. Excess stock beyond storage capacity is written off. This creates an explicit trade-off between avoiding stockouts and tying cash up in inventory.
05 · PRODUCT DEVELOPMENT
Short games emphasize execution. Full games add product-generation timing.
Every company privately designs Product I before Quarter 1. Unused pre-launch development allowance becomes operating cash, so teams can intentionally trade launch quality for liquidity.
In a four-quarter Quick Game, Product I remains the company’s product for the full year. In an eight-quarter Full Game, teams may develop Product II while Product I remains on sale. A new generation requires both funding and engineering time, normally two or three quarters, plus a launch cost. An early launch is possible only after meaningful progress and carries a reputation penalty because unfinished improvements are abandoned.
06 · FINANCE & COMPANY VALUE
Winning is broader than market share.
Quarterly profit is driven by unit revenue, manufacturing and operating spending, research, product development, launches and factory investment. Cash carries forward, so aggressive spending today changes what a team can do tomorrow.
Company Value combines five dimensions: ending cash, average profitability, market position, the replacement engineering value of technology currently launched in the product, and brand equity. Unfinished R&D receives no technology valuation credit. This is intended to discourage single-metric play and make strategic coherence matter.
07 · VALIDATION APPROACH
The model is stress-tested for dominance and instability.
During development, Markup Markets has been exercised through more than 10,000 simulation runs across randomized markets, deterministic seeded tournaments, pricing and advertising sweeps, channel tests, product-development timing tests, company-count tests and deliberately extreme strategies.
Testing has covered two through ten competing companies, both four- and eight-quarter formats, multiple AI strategy archetypes and pathological behaviors such as extreme pricing, overproduction, excessive advertising, all-in distribution choices and indiscriminate R&D. The objective is not to force every strategy to win equally; it is to remove obvious mechanical exploits and preserve multiple credible paths.
Automated simulation is a development tool, not evidence that the model perfectly predicts real firms or real consumers. Professor and student playtesting remains important because classroom clarity, perceived fairness and learning value cannot be established by computer tournaments alone.
08 · MODEL BOUNDARIES
An educational market model, not an econometric forecast.
Markup Markets uses explicit rules and bounded stochastic market movement to create repeatable strategic trade-offs. It is not calibrated to forecast the real headphone industry, a particular country, or an actual company’s financial performance. Customer groups are teaching abstractions, dollar amounts are simulation economics, and Company Value is a game performance measure rather than an investment valuation.
The public methodology explains the logic that students and instructors should understand, while some exact coefficients and hidden customer-population information remain inside the simulation so research and uncertainty continue to have instructional value.