Pricing
Pricing is key in B2B companies. Even minor improvements can have a major impact on profitability.
In business-to-business (B2B) markets, getting the best price possible on every deal is fundamental to maximizing margins. The bottom-line impact of optimizing prices can even dwarf those of cost reductions and volume increases combined.
Price optimization technology leverages a company's transactional data and combines it with statistical science and business application software to improve how companies set prices in market. At its core, price optimization measures opportunities to differentiate prices for individual sales transactions on the basis of their unique circumstances. The power of price optimization is that is also reveals additional opportunities hidden in the data to differentiate price including dominant product, end use and deal source. Prices are then delivered to the sales force as a "band" of price points—a start, target and ceiling—enabling them to negotiate with more confidence and consistency while maximizing prices and profits.
Despite the underlying mathematical sophistication, the output of price optimization software is intuitive and simple for business users to understand and act upon. By deploying this specialized software, companies are able to automatically analyze every deal in real time, providing profit-optimal price points to salespeople for every product on every order. Ultimately, they maximize their margin contribution and profitability without sacrificing top-line revenue.
So how does it work ?
The software sifts through volumes of historical pricing data and cull out price response patterns. The variations in price response are correlated with circumstances under which the deals were priced, and are used to establish differentiated, profit-maximizing pricing policies. Using the price segments to group pricing and margin data for customers, products and channels produces rich insights into their relative performance against peer groups. This provides an actionable view of relative pricing and profitability, and allows pricing decision makers to quickly and easily identify areas ripe for pricing improvement. Prices can then be optimized to maximize total margin or revenue, while taking into account pricing strategies, market and customer constraints, and overall corporate objectives. Quantitative, segment-specific price setting produces significantly higher gross margins than legacy, undifferentiated pricing.
Just because optimal prices and margin targets are known does not guarantee they will be achieved in the market. Adopting a more quantitative, disciplined approach to price execution can eliminate unnecessary concessions without adversely affecting win rates. Through the combined use of quantitative benchmarks and end-to-end automation, data-driven price execution helps sales teams and pricing analysts to make more informed pricing decisions, ensure accurate quoting, and enforce key pricing policies company-wide. Ultimately, they maximize their margin contribution and profitability without sacrificing top-line revenue.
In business-to-business (B2B) markets, getting the best price possible on every deal is fundamental to maximizing margins. The bottom-line impact of optimizing prices can even dwarf those of cost reductions and volume increases combined.
Price optimization technology leverages a company's transactional data and combines it with statistical science and business application software to improve how companies set prices in market. At its core, price optimization measures opportunities to differentiate prices for individual sales transactions on the basis of their unique circumstances. The power of price optimization is that is also reveals additional opportunities hidden in the data to differentiate price including dominant product, end use and deal source. Prices are then delivered to the sales force as a "band" of price points—a start, target and ceiling—enabling them to negotiate with more confidence and consistency while maximizing prices and profits.
Despite the underlying mathematical sophistication, the output of price optimization software is intuitive and simple for business users to understand and act upon. By deploying this specialized software, companies are able to automatically analyze every deal in real time, providing profit-optimal price points to salespeople for every product on every order. Ultimately, they maximize their margin contribution and profitability without sacrificing top-line revenue.
So how does it work ?
The software sifts through volumes of historical pricing data and cull out price response patterns. The variations in price response are correlated with circumstances under which the deals were priced, and are used to establish differentiated, profit-maximizing pricing policies. Using the price segments to group pricing and margin data for customers, products and channels produces rich insights into their relative performance against peer groups. This provides an actionable view of relative pricing and profitability, and allows pricing decision makers to quickly and easily identify areas ripe for pricing improvement. Prices can then be optimized to maximize total margin or revenue, while taking into account pricing strategies, market and customer constraints, and overall corporate objectives. Quantitative, segment-specific price setting produces significantly higher gross margins than legacy, undifferentiated pricing.
Just because optimal prices and margin targets are known does not guarantee they will be achieved in the market. Adopting a more quantitative, disciplined approach to price execution can eliminate unnecessary concessions without adversely affecting win rates. Through the combined use of quantitative benchmarks and end-to-end automation, data-driven price execution helps sales teams and pricing analysts to make more informed pricing decisions, ensure accurate quoting, and enforce key pricing policies company-wide. Ultimately, they maximize their margin contribution and profitability without sacrificing top-line revenue.