Infosys Equinox Strategic Pricing

Infosys Equinox Strategic Pricing, powered by Consumer Surplus Factor (CSF), is an advanced analytics tool that supports next-generation Revenue Growth Management (RGM) for leading consumer packaged goods companies.

Challenges
Features
Business Impact

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 advanced capabilities and data-driven recommendations. Track consumer and customer behaviour across markets and channels, monitor competitor pricing and sales velocity in near real-time, and employ data to model and predict the impact of pricing adjustments across brand and product portfolios. CSF measures the pricing power of your brand using brand strength or equity in a competitive environment, using actual real-time market data and a proprietary econometric AI model.

Business
Challenges

The classic dilemma for revenue managers

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    Should I lead the price
    increase or follow the competition?

  • How do I insulate my business against
    inflation pressures without compromising brand equity?

  • 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

    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

    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

    Predict market share based on the
    pricing decision made for your brand and competition

Business
Impact

With AI-driven Revenue Growth Management

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    Raise prices above the rate of
    inflation (while preserving/growing market share)

  • Hold off on price increases
    to defend against share loss

  • Identify products that are over-indexed
    and would benefit from price reductions

  • Understand cross-elasticities and how a change in one
    brand/product’s price impacts performance across your portfolio

  • Develop more targeted
    and effective D2C offerings

90%

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


Just 4 weeks to demonstrate results