Pricing and
Market Share Analyses

Increasing the price of a product increases profit per unit but decreases total sales volume. Finding the balance between these two opposing forces is the fundamental problem of microeconomics. This model plots the relationship between price and demand not as a simple ratio, but as a continuous curve using a log-linear function.

The Power that Distinguishes This Analysis: While traditional approaches focus solely on sales volume; this model, with its Dual-Axis structure, collides demand and total revenue in the same space. By finding the peak of the revenue parabola through derivative calculations, it identifies the "Optimum Price Point" (Maximum Revenue) which is completely mathematical, not theoretical.

Brand Equity is not an abstract measurement of love; it is the very money the customer pulls extra out of their wallet not to go to a competitor. BPTO analysis measures how long and against what magnitude of price difference (premium) your brand can resist competitors' price cuts. It doesn't ask consumers directly if they like the brand; it puts them in a realistic competitive scenario. The algorithm systematically drops competitor prices and step-by-step detects that critical "Tipping Point" where the customer abandons your brand.

It is a classic and powerful method used especially in pricing innovative products (NPD) that will newly enter the market. By presenting consumers with sequential price points (price laddering) for a specific product, it calculates the probability of "Definitely Would Buy" at each level.

Its Power: Dynamically tests the threshold of Maximum Willingness to Pay (WTP) in the consumer's mind for the relevant product. It translates the declining demand curve at each step into a revenue index by multiplying it with the price.

Traditional market research works via surveys (Stated Preference). Hedonic models, however, analyze the actual shelf prices of thousands of products in the field and the features on their packaging (Big Data) using Multiple Linear (OLS) or Lasso Regression.

The Main Difference: It doesn't ask the consumer anything. It solves the market's own dynamics. For instance, it proves via actual sales data as a "Shadow Price" that the term "Organic" or "Glass Packaging" on a product label adds a net value of "+12.50 ₺" to the shelf price.

Price is not just an economic figure, but a powerful psychological signal. The Van Westendorp (Price Sensitivity Meter) determines that psychological confidence interval between the point where a product is so cheap it is perceived as "poor quality" and the point where it is so expensive it feels like a "robbery".

Our Difference: While standard PSM draws only 4 intersection lines; we also integrate "Probability of Purchase" data into the model. Thus, we offer an expanded algorithm that shows not only the price the consumer finds "fair," but also the "Optimum Price Point" (OPP) that will generate the most cash inflow for the brand.

It is the transformation of massive data obtained from all advanced pricing and Bayesian models into an interactive "Simulator" that company boards can use directly. By pulling the data out of a static report format; it converts it into a dynamic strategic decision support module where you can test your brand's future market scenarios taking absolutely no financial risk.

Its Strength: The algorithm accepts the current product range of every player in the market as a baseline. It models probability distributions via "Randomized First Choice" (RFC) or "Share of Preference" algorithms, instantly calculates possible scenarios, and predicts competitors' counter-moves.