Data-Driven Retail Assortment Optimization
Stop relying on manual work to determine which product mix to carry and start capitalizing on data. Retailscape uses machine learning to surface product gaps and deliver data-supported assortment optimization recommendations for retail.
Assortment Optimization: Maximize Market Opportunity
Value matters to shoppers – and it’s about more than just prices.
Today’s shoppers aren’t making comparisons based on prices alone. Things like quality, convenience, and relevance are all major aspects of a shopper’s purchase decision. If you’re not stocking the products your customers want, they’ll easily find what they’re looking for elsewhere. Leverage omnichannel competitive data and machine learning to perfect your product mix.
- Evaluate brand and product gaps by category and competitor
- Prioritize assortment opportunities with simple rankings
- Seamlessly integrate your sales data from NPD, IRI, or Nielsen
- Quantify the potential revenue impact of new products
ML-DRIVEN PRODUCT MATCHING
- Achieve scalable match coverage for national brands, perishables, and private labels
- Understand assortment overlaps and category gaps
- See all matches in your customized match library
Actionable Retail Assortment Intelligence
Competitive Analysis
Analyze competitor assortments to determine gaps and overlaps. Analyze market intelligence for better assortment decisions.
Delight Your Shoppers
Find out which products are relevant to your customers in the categories you operate.
Attribute Analysis
Use machine learning to identify gaps – in flavor, product size, or location – so you can fill them quickly.
Calculate Impact
Apply rules-based modeling to quantify potential revenue impact for new products.
See the Whole Picture
OMNICHANNEL SOURCES
Collect price, promotion, and assortment data from competitor catalogs.
ACCURATE MATCHING
Harmonize all collected data and match products for assortment analytics.
MEASURE SUCCESS
Produce the most accurate geo-specific analytics for assortment and pricing.
AUTOMATED ALERTS
Receive alerts based on pricing and assortment variances.
How to Conduct an Effective Market Basket Analysis
We’ve outlined best practices and tips for conducting a differential market basket analysis for grocery products.
Pricing Analytics
Harness data to fine-tune your pricing strategy
- Dive deep into pricing data to identify risk and opportunity
- Track price changes and competitive position
- Centralize and visualize your pricing data for actionable insights
Pricing Optimization
Set the perfect price for any product
- Ensure pricing consistency across channels
- Execute competitive prices based on your strategy
- Set pricing rules and receive pricing recommendations
Competitive Intelligence
Be informed to be competitive
- Receive data from hard-to-access sites and hard-to-match categories
- Leverage ML-driven product matching to streamline competitive analysis
- Improve decisions with a clear view of your position relative to competitors
Stock the Products That Will Help You Stand Out
Get reliable, data-supported insights so that you can curate the optimal assortment that drives sales.
Increase in catalog year-over-year
Saved in inventory write-offs across categories
Increase In Sales Based On Product Popularity And Category
Reduction in cleansing and auditing time
Increase In Data Insights
Resources to Enhance Your Pricing
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Retail Trends & Challenges: 2025
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Data to Dollars: Achieving Success with Pricing Intelligence
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Webinar Recap: Why Grocers Need Flexible Pricing
Grocery retailers face constant pricing pressure. Unlike discretionary purchases like TVs or clothing, groceries are essential, so shoppers want value every time they fill their carts. How can grocers deliver value while staying competitive and protecting margins? Industry expert Scott Winburn joined Bungee Tech’s Matt Shachter to talk about the importance of a modern
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