AI-Driven Strategic Pricing Solutions

Infosys Equinox Strategic Pricing, powered by Consumer Surplus Factor (CSF), is an advanced analytics tool that supports next-generation RGM for leading consumer packaged goods companies. Available through the cloud-native Infosys Equinox platform, Strategic Pricing leverages AI modules to help CPG brands simulate, enact, adjust, and track pricing and promotion strategies at the brand, pack, and channel level.

Unlock profitable competitive growth, win customer mindshare, and scale decision making with AI-driven recommendations. Track consumer behavior across markets and channels, monitor competitor pricing and sales velocity in near real-time, and use data models to predict the impact of pricing adjustments across brand and product portfolios. CSF measures the customers willingness to pay for your brand in a competitive environment, using real-time market data and a proprietary econometric AI model.

Business
Impact

Generate revenue and save for your future innovation with AI-driven Revenue Growth Management. How ?

Capture
Consumer Surplus
Automate Decisions
With predictive modelling and real time data
Strengthen
Competitive positioning
Identify
Price-Pack Opportunities
Optimize
Pricing across your portfolio

90%

accuracy in predicting brand portfolio growth and market share in 12 months.

Just 4 weeks to demonstrate results

Business
Challenges

The classic dilemma for revenue managers

Should I lead the price
increase or follow the competition?
How do I protect my margins against
inflationary pressures without compromising market share?
How do I determine
the pricing for each channel?

Problems with Traditional RGM

Lack of
Precision data
Operational
Silos
Manual
Processes

Features

Infosys Equinox Strategic Pricing powered by Consumer Surplus Factor takes the guesswork out of pricing decisions for CPG revenue managers without disregarding the impact on the market share. AI-driven predictive tools.

Such tools must track consumer and customer behavior across markets and channels, including competitor data, which can be drilled down to the brand, product, and SKU levels. This can be used to model and predict the impact of pricing adjustments across brand and product portfolios.

Analyze sales and pricing
data at the channel level
Measure customer’s willingness to pay
for your brand as well as your competition’s brand
Predict market share based on the
pricing decision made for your brand and competition