Daisy's Theory of Retail™ Overview

Daisy’s Theory of Retail™ examines the relationships between merchandising variables to inform decision-making. This understanding enhances revenue and profit generation.

Use Cases

Customers recommend Merchandising, Forecasting, Workflow Management, as the business use cases that they have been most satisfied with while using Daisy's Theory of Retail™.

Other use cases:

  • Engaging With Scheduling & Cadence
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Business Priorities

Increase Sales & Revenue is the most popular business priority that customers and associates have achieved using Daisy's Theory of Retail™.

Other priorities:

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Daisy's Theory of Retail™ Use-Cases and Business Priorities: Customer Satisfaction Data

Daisy's Theory of Retail™ works with different mediums / channels such as Promotions.

Comprehensive Insights on Daisy's Theory of Retail™ Use Cases

How can Daisy's Theory of Retail™ enhance your Merchandising process?

Case Studies

CASE STUDY Midsized US Retailer

Daisy’s Promotional Item Selection and Price Mix Optimization helped a midsized US grocery retailer improve pricing and promotions. The retailer used Daisy’s AI to analyze years of transaction data a...nd simulate new strategies. This led to better promo product and price mix decisions. Merchants spent more time on innovation and brand experience. The retailer achieved a 2.9% increase in topline sales. Daisy’s platform made promotional planning faster and more effective.

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CASE STUDY Major North American retail chain

Daisy’s Demand Forecasting solution helped a major North American retail chain improve their forecasting accuracy. The merchant team struggled with poor forecasting and its negative effects. Daisy us...ed the retailer’s TLOG data to train its AI and forecast promotion impacts across sales, transactions, and seasonality. After three months, Daisy’s forecasts replaced the old system and became central to weekly marketing meetings. The retailer saw over $6M in sales lift and a 23% drop in forecast error, with an additional 5% decrease after launch.

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Insurance

CASE STUDY Large North American Insurer

Daisy Fraud Detection helped a large North American insurer find and avoid fraud in group health benefits claims. The client wanted to improve fraud detection with AI, as current recoveries were belo...w industry expectations. Daisy's AI system was used for dental and drug claims, integrating with the client's existing fraud flags and data. The system found $10M to $50M in possible annual fraud recoveries and delivered over $10M in fraud, waste, and abuse avoidance. The client achieved a 10X ROI and needed only about 1000 days of investigative effort to reach these results.

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Insurance

CASE STUDY Canadian division of a large multinational insurer

Daisy Claims Automation and Fraud Detection helped a large Canadian insurer automate claims processing. The client wanted to cut costs and stop fraud. Daisy's AI platform increased straight-through p...rocessing by 554%. Fraud investigations rose by 130%. The client saved over $1.4 million in labor and avoided more than $4 million in fraud. Each claim saved over $50. The system matched 90.4% of historical claims with only a 7% false-positive rate.

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Insurance

CASE STUDY Large North American insurer (Canadian headquarters)

Daisy Fraud Detection helped a large North American insurer find new fraud cases in group health benefits claims. The client wanted to improve fraud detection with AI. Daisy's system found 183 new fr...aud cases, leading to over $100,000 in immediate recovery. The solution enabled more than $1 million in future fraud avoidance and $10 million in annual fraud avoidance for one business line. The client achieved a 10X ROI from the project.

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CASE STUDY A Fortune 400 company and one of the largest food distributors in the United States

Daisy’s Promotional Item Selection helped a major US food distributor boost basket sales from their weekly flyer. The retailer wanted to pick the best mix of products for promotions but faced challen...ges with department coordination. Daisy’s solution used a color scoring system to guide Category Managers to top-performing items. By following these recommendations, the company saw a 7X increase in promo sales lift compared to the bottom 25 items. Merchants now spend more time on innovation and brand experience, with bigger baskets and more trips, all without extra margin costs.

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Daisy's Theory of Retail™ Features

  • Low
  • Medium
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FEATURE RATINGS AND REVIEWS
AI Powered

3.60/5 ★

Read Reviews (5)
Analytics

3.31/5 ★

Read Reviews (3)
CAPABILITIES RATINGS AND REVIEWS
AI Powered

3.60/5 ★

Read Reviews (5)
Analytics

3.31/5 ★

Read Reviews (3)

Software Failure Risk Guidance

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for Daisy's Theory of Retail™

Top Failure Risks for Daisy's Theory of Retail™

Daisy Intelligence Profile

Company Name

Daisy Intelligence

Company Website

https://www.daisyintelligence.com/

HQ Location

260 King St. E., Suite A400 Toronto, ON M5A 4L5

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