Tune Asymmetric Node
The Tune Asymmetric node is designed to take Customer Distributions for Products from the Focus Store and apply them to Identical Products sold by other Competitor Stores in order to tune a wider Market.
The node is typically used when a lot is known about the Focus Store but much less is known about the sales of Competitive Stores. The Focus Store might be a brick-and-mortar retailer or an eCommerce vendor with full accounts of its own Store sales but little knowledge of other retailers.
What must be known about the Competitive Stores is the following: (a) the set of Identical Products sold by each Competitive Store, (b) the Prices of those Identical Products, and (c) a starting Guess Quantity sold for each Identical Product. The starting Guess Quantity may be based upon knowledge of overall traffic flow to the Competitive Store and relative Prices.
This Tune Asymmetric node will tune the wider Market. The output from tuning is a Willingness To Pay (WTP) Matrix. A WTP Matrix quantifies the maximum Price that each Customer would pay for each Product in the Market. The Willingness To Pay (WTP) Matrix output of the Tune Asymmetric node can be fed directly into a downstream Profit Engine node in order to optimize the Price of a target Product or generate a Product Demand Curve. The Willingness To Pay (WTP) Matrix output of the Tune Asymmetric node can also be fed into a downstream ‘Tune Market’ node to fine tune the Mean and the SD of the Competitor Products (the Correlation can not be fine tuned in this way).
The Tune Asymmetric node takes the WTP Matrix for Products from the Focus Store to generate a larger WTP Matrix for a wider Market. The node can be used when a lot is known about the Focus Store but much less is known about the sales of Competitive Stores other than what identical Products they stock, their Prices, and their relative magnitude.
Input Product Array
The set of Products from both the Focus Store as well as the Competitor Stores that define the Market. Each row corresponds to a Product that competes for customers in the Market.
Input Competitor Factors
The optional Input Competitor Factors contains information that describe how each Competitive Store will initially differentiate the Focus Store Identical Product from the Input Product Array before the Competitor Factors are tuned.
Customer Distribution Matrix
The set of Product-level Customer Distributions for the Focus Store’s Products. The incoming Customer Distributions can be either Unit Distributions or a partially-tuned Willingness To Pay (WTP) Matrix.
Input Price Elasticity
Additional measurements that can be used to tune the Market Simulation. Analyzing historical sales data often yields information about the Price Elasticity of individual Products, and about the Cross Elasticity between Products in the Market.
The Tuning Algorithm can operate in two phases. During the first phase, just the Quantity values are taken into account. During the second phase, both the Quantity values and the Price Elasticity measurements are taken into account. The ‘Two Phases’ method takes longer as the entire Tuning Algorithm needs to run twice. Select ‘Two Phases’ if it is important to get Quantity estimates for Competitors accurately tuned. Select ‘One Phase’ if the Price Elasticity and Cross Elasticity measurements are more accurate than the Quantity Estimate.
Output Product Array
The Output Product Array corresponds to the Input Product Array but will change the Product name to be unique, and has updated values in the ‘Mean’ and ‘SD’ columns that reflect the tuned results.
Output Competitor Factors
The Output Competitor Factors contains information that describe how each Store is different to the Focus Store.
Output WTP Matrix
The tuned Willingness To Pay (WTP) Customer Distribution matrix for each Product column in the Market by each Virtual Customer row. The WTP Matrix quantifies the Price that each Customer would pay for each Product in the Market. The Output WTP Matrix will be extended to also include all the Products sold by each Competitive Store. The Products listed in this Output WTP Matrix use the ‘Unique Product’ name found in the ‘Output Product Array’ so that this WTP Matrix can be directly connected to a downstream ‘Profit Engine’ node.
The Output KPI Indicators contain select information about the tuning process and the quality of the final results.
Output Price Elasticity
Compares the measured Input Price Elasticity against the forecasted Output Price Elasticity from the tuned Market Simulation model.