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Measuring The Impact Of Strategic Pricing with the help of Price Elasticity and Price Optimization

Price Sensitivity and Pricing Optimization
By
Niki Khokale
April 19, 2022
5
min
Share this
Blog

Measuring The Impact Of Strategic Pricing with the help of Price Elasticity and Price Optimization

Price Sensitivity and Pricing Optimization
Share this

Retail, DTC, QSR, E-commerce, and Q-commerce companies, as a result of their business model, operate in a fiercely competitive environment. It is imperative for them to create differentiators for themself to protect their brand and create a competitive advantage for themselves. There are many ways to build differentiation including, innovation, inciting emotions, creating an experience, and pricing.  

Pricing, when handled properly, can be a very effective differentiation strategy, especially in the aforementioned industries. A company like Walmart may want to be perceived as a value brand, offering low prices and providing good value to its customers. Another company like Starbucks would want itself to be a premium brand, charging high prices. Companies often struggle to identify strategies that work best for them.

Common Price Optimization Challenges

Traditional rule-based pricing algorithms
Traditional rule-based pricing algorithms take into account only historical data to arrive at dynamic pricing. It does not factor in factors like seasonality, cannibalization, stockouts, holidays, weather, or competitor information to predict demand at various price points.

Establishing price sensitivity
Businesses need ​​to establish price elasticity for the product. If elastic products, changes in prices will result in a substantial impact on the demand for the product. Whereas, for an inelastic product, any price changes will have little impact on the demand for the product. This is a challenging affair as the calculations need to be done at the most granular levels.

Factoring in revenue and margin targets
Most pricing algorithms do not take into account the price elasticity, future revenue targets, and the maximum margin hit a business is willing to take to come up with the most optimized pricing strategy that maximizes profits.

Demand planners and marketers regularly face the difficulty of visualizing the potential impact of price changes on the demand for a product. There is a possibility of friction between the end objectives of both these individuals. One with the object of accurately predicting demand and the other’s objective being to maximize revenue. It is essential for both these individuals to collaborate effectively so as to maximize revenue while minimizing operating costs.

Also, demand planners face the difficulty of predicting demand for price changes to a product whose price has never been changed before. An example of this scenario can be a new product that has just been launched in the market. Most marketers and demand planners end up using gut-based or other non-statistical methods to predict demand at various price points. There is a high probability of inefficiencies, stockouts, and wasted working capital in this case. Demand planners and marketers need to fall on robust real-time demand prediction solutions to plan and mauver price changes and predict demand accordingly.

Kronoscope- Measuring The Impact Of Price Changes

Kronoscope is a new-age AI-powered demand sensing and inventory management product for DTC, Retail, E-commerce, Q-commerce, and QSR companies. Kronoscope’s AI engine constantly senses changes in demand patterns, helping demand planners adapt quickly and eliminate inventory pile-ups and stockouts while your customers always get what they are looking for. It uses overall nine different signals like historical trends, seasonal effects, and cyclicity to provide base-level demand predictions. The Baseline demand prediction further factors in changes in pricing, promotional campaigns, and holidays or weather for a sharper, more accurate demand pattern.

Demand planners can utilize Kronoscope’s scenario planning module to refine demand predictions or run simulations to incorporate the impact of change in pricing. Let's have a look at how Kronoscope addresses price optimization challenges:

Price Sensitivity
Kronoscope’s AI engine has the capability to calculate price sensitivity at the most granular levels and forecast future demand based on such uplifts. This is done in the pricing and promotions planning module by establishing a price sensitivity curve established for each SKU, geography combination is used to determine the impact of price change. Users with Kronoscope can formulate a strategy for the coming time period directly by editing the predictions chart. They can edit the price point and see what the adjusted demand would look like.

Behind the scenes, Kronoscope derives the demand values by running calculations on price sensitivity for every SKU at every store, thereby providing price-adjusted demand numbers.

Price Optimization
Based on a company’s wallet share/revenue targets and margin constraints Kronoscope can calculate and recommend price points to maximize objective function and meet revenue targets.

Kronoscope also recommends the percentage target that can be achieved with optimized pricing.

Demand planners can then freeze the calculations and pull the updated demand numbers into the purchase and replenishment planning modules. Kronoscope also has the capability to predict the demand for new product launches. It is done by intelligently associating similar or existing products assortments.

Businesses no longer have to play the guessing game of balancing revenue and demand numbers. Kronoscope provides a powerful tool to demand planners and marketers alike to achieve their objectives in harmony by viewing the impact of strategic pricing on demand planning in real-time.

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Blog

Measuring The Impact Of Strategic Pricing with the help of Price Elasticity and Price Optimization

Price Sensitivity and Pricing Optimization
Share this

Retail, DTC, QSR, E-commerce, and Q-commerce companies, as a result of their business model, operate in a fiercely competitive environment. It is imperative for them to create differentiators for themself to protect their brand and create a competitive advantage for themselves. There are many ways to build differentiation including, innovation, inciting emotions, creating an experience, and pricing.  

Pricing, when handled properly, can be a very effective differentiation strategy, especially in the aforementioned industries. A company like Walmart may want to be perceived as a value brand, offering low prices and providing good value to its customers. Another company like Starbucks would want itself to be a premium brand, charging high prices. Companies often struggle to identify strategies that work best for them.

Common Price Optimization Challenges

Traditional rule-based pricing algorithms
Traditional rule-based pricing algorithms take into account only historical data to arrive at dynamic pricing. It does not factor in factors like seasonality, cannibalization, stockouts, holidays, weather, or competitor information to predict demand at various price points.

Establishing price sensitivity
Businesses need ​​to establish price elasticity for the product. If elastic products, changes in prices will result in a substantial impact on the demand for the product. Whereas, for an inelastic product, any price changes will have little impact on the demand for the product. This is a challenging affair as the calculations need to be done at the most granular levels.

Factoring in revenue and margin targets
Most pricing algorithms do not take into account the price elasticity, future revenue targets, and the maximum margin hit a business is willing to take to come up with the most optimized pricing strategy that maximizes profits.

Demand planners and marketers regularly face the difficulty of visualizing the potential impact of price changes on the demand for a product. There is a possibility of friction between the end objectives of both these individuals. One with the object of accurately predicting demand and the other’s objective being to maximize revenue. It is essential for both these individuals to collaborate effectively so as to maximize revenue while minimizing operating costs.

Also, demand planners face the difficulty of predicting demand for price changes to a product whose price has never been changed before. An example of this scenario can be a new product that has just been launched in the market. Most marketers and demand planners end up using gut-based or other non-statistical methods to predict demand at various price points. There is a high probability of inefficiencies, stockouts, and wasted working capital in this case. Demand planners and marketers need to fall on robust real-time demand prediction solutions to plan and mauver price changes and predict demand accordingly.

Kronoscope- Measuring The Impact Of Price Changes

Kronoscope is a new-age AI-powered demand sensing and inventory management product for DTC, Retail, E-commerce, Q-commerce, and QSR companies. Kronoscope’s AI engine constantly senses changes in demand patterns, helping demand planners adapt quickly and eliminate inventory pile-ups and stockouts while your customers always get what they are looking for. It uses overall nine different signals like historical trends, seasonal effects, and cyclicity to provide base-level demand predictions. The Baseline demand prediction further factors in changes in pricing, promotional campaigns, and holidays or weather for a sharper, more accurate demand pattern.

Demand planners can utilize Kronoscope’s scenario planning module to refine demand predictions or run simulations to incorporate the impact of change in pricing. Let's have a look at how Kronoscope addresses price optimization challenges:

Price Sensitivity
Kronoscope’s AI engine has the capability to calculate price sensitivity at the most granular levels and forecast future demand based on such uplifts. This is done in the pricing and promotions planning module by establishing a price sensitivity curve established for each SKU, geography combination is used to determine the impact of price change. Users with Kronoscope can formulate a strategy for the coming time period directly by editing the predictions chart. They can edit the price point and see what the adjusted demand would look like.

Behind the scenes, Kronoscope derives the demand values by running calculations on price sensitivity for every SKU at every store, thereby providing price-adjusted demand numbers.

Price Optimization
Based on a company’s wallet share/revenue targets and margin constraints Kronoscope can calculate and recommend price points to maximize objective function and meet revenue targets.

Kronoscope also recommends the percentage target that can be achieved with optimized pricing.

Demand planners can then freeze the calculations and pull the updated demand numbers into the purchase and replenishment planning modules. Kronoscope also has the capability to predict the demand for new product launches. It is done by intelligently associating similar or existing products assortments.

Businesses no longer have to play the guessing game of balancing revenue and demand numbers. Kronoscope provides a powerful tool to demand planners and marketers alike to achieve their objectives in harmony by viewing the impact of strategic pricing on demand planning in real-time.

Access the

Blog

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Retail, DTC, QSR, E-commerce, and Q-commerce companies, as a result of their business model, operate in a fiercely competitive environment. It is imperative for them to create differentiators for themself to protect their brand and create a competitive advantage for themselves. There are many ways to build differentiation including, innovation, inciting emotions, creating an experience, and pricing.  

Pricing, when handled properly, can be a very effective differentiation strategy, especially in the aforementioned industries. A company like Walmart may want to be perceived as a value brand, offering low prices and providing good value to its customers. Another company like Starbucks would want itself to be a premium brand, charging high prices. Companies often struggle to identify strategies that work best for them.

Common Price Optimization Challenges

Traditional rule-based pricing algorithms
Traditional rule-based pricing algorithms take into account only historical data to arrive at dynamic pricing. It does not factor in factors like seasonality, cannibalization, stockouts, holidays, weather, or competitor information to predict demand at various price points.

Establishing price sensitivity
Businesses need ​​to establish price elasticity for the product. If elastic products, changes in prices will result in a substantial impact on the demand for the product. Whereas, for an inelastic product, any price changes will have little impact on the demand for the product. This is a challenging affair as the calculations need to be done at the most granular levels.

Factoring in revenue and margin targets
Most pricing algorithms do not take into account the price elasticity, future revenue targets, and the maximum margin hit a business is willing to take to come up with the most optimized pricing strategy that maximizes profits.

Demand planners and marketers regularly face the difficulty of visualizing the potential impact of price changes on the demand for a product. There is a possibility of friction between the end objectives of both these individuals. One with the object of accurately predicting demand and the other’s objective being to maximize revenue. It is essential for both these individuals to collaborate effectively so as to maximize revenue while minimizing operating costs.

Also, demand planners face the difficulty of predicting demand for price changes to a product whose price has never been changed before. An example of this scenario can be a new product that has just been launched in the market. Most marketers and demand planners end up using gut-based or other non-statistical methods to predict demand at various price points. There is a high probability of inefficiencies, stockouts, and wasted working capital in this case. Demand planners and marketers need to fall on robust real-time demand prediction solutions to plan and mauver price changes and predict demand accordingly.

Kronoscope- Measuring The Impact Of Price Changes

Kronoscope is a new-age AI-powered demand sensing and inventory management product for DTC, Retail, E-commerce, Q-commerce, and QSR companies. Kronoscope’s AI engine constantly senses changes in demand patterns, helping demand planners adapt quickly and eliminate inventory pile-ups and stockouts while your customers always get what they are looking for. It uses overall nine different signals like historical trends, seasonal effects, and cyclicity to provide base-level demand predictions. The Baseline demand prediction further factors in changes in pricing, promotional campaigns, and holidays or weather for a sharper, more accurate demand pattern.

Demand planners can utilize Kronoscope’s scenario planning module to refine demand predictions or run simulations to incorporate the impact of change in pricing. Let's have a look at how Kronoscope addresses price optimization challenges:

Price Sensitivity
Kronoscope’s AI engine has the capability to calculate price sensitivity at the most granular levels and forecast future demand based on such uplifts. This is done in the pricing and promotions planning module by establishing a price sensitivity curve established for each SKU, geography combination is used to determine the impact of price change. Users with Kronoscope can formulate a strategy for the coming time period directly by editing the predictions chart. They can edit the price point and see what the adjusted demand would look like.

Behind the scenes, Kronoscope derives the demand values by running calculations on price sensitivity for every SKU at every store, thereby providing price-adjusted demand numbers.

Price Optimization
Based on a company’s wallet share/revenue targets and margin constraints Kronoscope can calculate and recommend price points to maximize objective function and meet revenue targets.

Kronoscope also recommends the percentage target that can be achieved with optimized pricing.

Demand planners can then freeze the calculations and pull the updated demand numbers into the purchase and replenishment planning modules. Kronoscope also has the capability to predict the demand for new product launches. It is done by intelligently associating similar or existing products assortments.

Businesses no longer have to play the guessing game of balancing revenue and demand numbers. Kronoscope provides a powerful tool to demand planners and marketers alike to achieve their objectives in harmony by viewing the impact of strategic pricing on demand planning in real-time.

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