Easily identify comparable products despite inconsistent descriptions and multiple reference systems
Maintain reliable and comprehensive competitive intelligence
Structure the product chain over time (new packaging, changes in product codes, innovations)
Managing the complexity of the three-pronged approach: National Brands (NB) / Private Label Brands (PLB) / First Prices (FPx)
Secure pricing decisions through relevant and audited comparisons
Drastically reduce the time spent on manual chaining
Smart association of non-comparable products
BOOPER MPS relies on visual recognition and machine learning algorithms capable of identifying matches between products even when labels and attributes are incomplete or inconsistent.
The models automatically analyze:
- Product labels and descriptions
- Technical attributes (weight, size, capacity, recipe, composition)
- Categories and subcategories
- Brand and price positioning
- Price behavior history
The association is based on multiple criteria in order to obtain reliable, contextualized associations that can be used by pricing teams.
The result: a consolidated view of product equivalencies across brands, formats, and markets.
Automatic chaining of your products
BOOPER MPS dynamically links your references to maintain continuity of analysis despite:
- Changes to item codes
- Packaging developments
- Range renovations
- Supplier substitutions
- Product innovations
Each product is linked to a logical chain that allows you to keep track of sales performance and price history.
You avoid breaks in analysis and ensure the temporal consistency of your indicators.
Cloning with competing products
BOOPER MPS allows you to automatically create product clones between your assortment and that of your competitors in order to:
- Compare equivalent products of the same brand, or simply those with a different EAN.
- Identify pricing positioning gaps
- Identify opportunities for adjustment • Monitor competitive developments over time
Competitive cloning directly feeds into pricing analytics and simulation modules.
Chaining of the MN / MDD / PPx triptych
BOOPER MPS structures relationships between:
- National Brands (NB)
- Private Label Brands (PLB)
- First Prizes (PPx)
AI identifies substitutable and comparable products based on their functional attributes and price positioning.
This modeling allows:
- Analyze cannibalization effects • Optimize pricing architectures
- To steer strategies for moving upmarket or defending prices
Statistics and indicators of quality of associations
BOOPER MPS incorporates advanced statistical tools to manage the quality of associations:
- Competitive coverage rate
- Correspondence reliability rate
- Number of active chained products
- Product volumes matched by category
- History of human validations
These indicators ensure complete control over the data used for pricing decisions.
Dynamic dashboard and operational management
BOOPER MPS offers dashboards that enable you to:
- View product matches
- Filter by category, store, brand, or geographic area
- Monitoring product line developments
- Identify unmatched products
- Prioritize validation actions
The pricing, purchasing, and data teams have a clear, shared, and actionable view of the product repository.
Visual recognition products
To go beyond the limitations of text labels and attributes, BOOPER MPS incorporates AI-based image and label recognition technologies.
The algorithms automatically analyze:
- Packaging and product design
- Distinctive shapes, colors, and visuals
- Variations in format and appearance
This approach is particularly effective when:
- Product descriptions are incomplete or inconsistent
- References differ between brands (e.g., private labels).
- The products are visually similar but described differently.
Visual recognition enhances the reliability of associations and ensures competitive comparisons across complex categories (food, non-food, fresh produce, DIY, gardening, etc.).
Associations multimodal (text + image + attributes)
BOOPER MPS combines multiple sources of analysis in a single engine:
- Semantic analysis of product labels
- Technical and categorical attributes
- Visual recognition by image
- Price and behavior history
This allows:
- To reduce false positives and false negatives
- Identify substitutable products that are not strictly identical
- Improve overall competitive coverage
The models continuously learn from business validations in order to increase accuracy over time.
Advanced identification substitutes and purchasing behaviors
Visual similarity directly influences consumer perception and substitution mechanisms.
By integrating images into associations, BOOPER MPS enables:
- Identify products that are truly competitive from the customer's perspective
- Anticipating cannibalization effects
- Better model interactions between MN, MDD, and PPx
- To enrich elasticity and pricing analyses
This approach improves the relevance of pricing decisions in highly competitive environments.
Price simulation
BOOPER MPS incorporates a price simulation engine (PSS) based on elasticity and AI to measure the impact of a pricing scenario on volume, revenue, and margin. It combines historical data, forecasts, and business rules to manage multiple objectives under constraints and support operational decision-making.
Geopricing and Price Tiers
BOOPER MPS manages geo-pricing and price tiers. Prices are simulated and optimized according to elasticity levels, margin targets, and business constraints, ensuring global consistency, local differentiation, and multi-level performance management.
Assortment management
BOOPER manages assortments according to formats, zones, and channels, integrating packaging sizes, sales forecasts, and product life cycles. Margin simulations enable decisions to be made on whether to introduce or withdraw products based on economic performance and profitability targets.
Governance and management
BOOPER secures pricing decisions through structured governance based on explainable models, business rules, and complete traceability of simulations. Multi-level validations ensure strategic consistency, risk control, auditability, and control of margin and performance variances.
What is product bundling in retail pricing?
Product matching, or matching in certain situations, consists of automatically identifying equivalent products between different brands or ranges in order to compare their prices, performance, and competitive positioning on a consistent basis.
How does artificial intelligence improve product pairing?
AI simultaneously analyzes labels, attributes, formats, brands, and price behaviors to detect similarities invisible to human analysis. It continuously learns from user validations to improve its accuracy. When available, AI also takes image recognition into account.
What is the difference between product cloning and product chaining?
When there is no direct association by EAN, cloning takes over and links the retailer's products with those of its competitors; this applies to both private labels and national brands. The other type of complementary relationship is chaining: the retailer's products are grouped together to establish links in terms of hierarchy, coefficients, and historical models.
How does BOOPER handle MN, private label, and budget brands?
BOOPER identifies substitutable products based on their functional attributes and price positioning in order to structure MN/MDD/PPx chains and analyze the effects of cannibalization and upmarket positioning.
Is the association fully automated?
No, although recommendations are becoming increasingly intelligent and automatic, the association requires human validation in order to train the algorithms.
What data is needed to set up an effective association?
MPS uses product databases, descriptions, technical attributes, price histories, and competitive data. The richer the data, the more accurate the association proposal.
What is the ROI of a product association and chaining module?
The gains come from reduced manual time, reliable price comparisons, improved business decisions, and overall competitive performance. The first benefits are usually seen in less than three months.
Solutions
Pricing Analytics
AI pricing platform focused on margin performance and business governance control.
Sales forecasting using AI
Anticipate demand and improve your business decisions with AI
Product matching: Cloning and chaining
Make your product comparisons more reliable with AI
Promotion management
Manage your promotions with precision and maximize their profitability
Markdown and Clearance Sale
Optimize your markdowns and accelerate the sale of your inventory
Studies & Data
Price surveys and web scraping
Monitor your competitors' prices online and offline
Diagnosis Price
Optimize your pricing strategy and secure your decisions
Price strategy development
Use your pricing strategy as a lever for creating sustainable value
Council
Operational Pricing Consulting
Bring clarity and control to your pricing decisions
Change management
Make your teams the driving force behind your pricing transformation
Pricing Training
Develop your operational or strategic skills
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