UPPMO applications use predictive analytics, algorithms, and optimization capabilities to plan and manage every aspect of pricing (i.e., initial, regular, promotion, markdown, and contextualized real-time). These technologies can provide improved pricing and promotion planning and management throughout the entire life cycle of the merchandise. The balancing act between discounting “pain” and margin “gain” is the core function of UPPMO solutions.
The outlook on the Global economy for 2022-2023 is uncertain and challenging. Businesses and consumers face unprecedented inflationary pressures with the rise of material costs, geopolitical tensions, the increase in the energy price cap, and upward pressure on energy and commodity prices.
In this environment, Gartner acknowledges that “ Now more than ever, UPPMO is a “must have ” business process for retailers. Allowing retailers to streamline data and processes across the organization to support and drive new and advanced pricing models. Gartner also identifies the need to utilize AI-based pricing optimization capabilities leveraging price elasticity and advanced data modeling as well as enabling autonomous experience to support frequency and magnitude (the latter is mostly relevant for long lifecycle products).
“Automation, greater accuracy and greater specificity will be the hallmarks of a successful pricing strategy for unified commerce retailers”
The 2022 report highlights the imperative of streamlining data and processes across the organization to support and drive new and advanced pricing models and the growing need for AI-based pricing optimization. When mapping the impact of different AI-based initiatives in retail, Gartner placed implementation of AI in pricing as High Business Value and High Feasibility. Making a strong case for implementing AI pricing solutions.
Quicklizard offers retailers a unified platform for building, evaluating, and maintaining pricing strategies. The Quicklizard platform allows integration (REST API/SFRP) of all data points relevant to building powerful dynamic pricing policies. The most common data sources are the retailer’s product catalog including all custom attributes, competitive pricing, and user behavior analytics.
Once the data layer is set the Quicklizard pricing engine applies pre-defined or customized rules and AI to determine the optimal price. The platform allows full flexibility in determining rules and functions based on the retailer’s bespoke pricing strategies and business goals.
The Dashboard and management tools allow retailers to set workflows, log and track pricing decisions, and view supporting analytics at every level (Item, Group, Category, Channel).
Specializing in B2C & D2C pricing Quicklizard has active implementations across different verticals, markets, and Sales models. The built-in best practices offered by a SaaS solution with the flexibility of the open platform allow us to offer our customers a robust yet highly configurable and dynamic solution.
Gartner, Market Guide for Retail Unified Price, Promotion and Markdown Optimization Applications, Jonathan Kutner, 28 July 2022
GartnerDisclaimer: Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with
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