Quicklizard

Automates and optimizes pricing strategies across channels and regions with AI-based recommendations, driving up to 3% revenue uplift and 1% profit increase.
Dynamic Pricing Pricing Optimization E-commerce Optimization

Quicklizard is a dynamic pricing platform for retailers and direct-to-consumer (D2C) brands. It provides sophisticated pricing optimization tools so businesses can automate and control their pricing strategy across the entire product lifecycle.

Quicklizard's machine learning and artificial intelligence technology generates optimized pricing recommendations to help clients stay ahead of the competition. Key benefits include:

  • 100% Open Platform: Built on a Python foundation for easy integration of custom pricing logic.
  • AI-Based Recommendations: Sophisticated AI and machine learning algorithms generate optimized pricing recommendations.
  • Omni-Channel Alignment: Align pricing strategies across all channels and regions.
  • Fast Implementation: Typically deployed in 12-16 weeks.

The platform covers a broad range of pricing needs, including catalog and channel management, competitor tracking, and multi-channel synchronization. Customers can expect substantial results, including up to 3% revenue uplift, up to 1% profit increase, and over 280% productivity gain.

Quicklizard offers different pricing tiers to suit different business needs:

  • Quicklizard Light: Up to 5000 SKUs, 1 channel, and 2 paid users, with full automation and competitive data.
  • Quicklizard Advanced: Up to 20,000 SKUs, up to 3 channels, and 5 paid users, with additional features like AI modules, A/B testing, and unlimited product segmentations.
  • Quicklizard for Enterprise: 50,000+ SKUs, unlimited channels and users, with a lifetime collaborative journey, AI modules, and enterprise-grade security.

Quicklizard is suitable for retailers and D2C brands looking to improve their pricing strategy. The platform enables businesses to make data-driven decisions, maximize revenue and minimize manual errors. To learn more or schedule a demo, visit their website.

Published on July 27, 2024

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