Case Studies > Nutritional Products Company Improves Financial Health with Test and Learn Program

Nutritional Products Company Improves Financial Health with Test and Learn Program

Customer Company Size
Large Corporate
Region
  • America
Country
  • United States
Product
  • Test And Learn Program
  • Predictive Analytics Solution
Tech Stack
  • Predictive Analytics
  • Machine Learning
  • AI
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Revenue Growth
  • Customer Satisfaction
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Analytics & Modeling - Data Mining
  • Analytics & Modeling - Machine Learning
Applicable Industries
  • Consumer Goods
  • Retail
Applicable Functions
  • Sales & Marketing
  • Business Operation
Services
  • Data Science Services
  • System Integration
About The Customer
A leading nutritional products company that leverages a robust promotional program including price reductions, coupons, and distribution of samples to health care professionals. The company sought to improve its promotional strategies and overall financial health by better understanding the impact of its marketing initiatives. They partnered with Antuit, a global analytics solutions provider, to develop a more data-driven approach to their promotional campaigns. Antuit specializes in serving the retail & eCommerce, consumer products, and manufacturing & logistics industries, combining deep domain expertise with proprietary solutions and technologies like machine learning and AI.
The Challenge
The company wanted a simple way to measure the revenue lift, margin impact, and effectiveness of promotional campaigns before they were rolled out nationwide. They relied on historical campaign performance to select future promotions, which limited their ability to understand initial campaign performance before making significant investments. The company tasked Antuit with developing an analytics-powered solution to measure the impact of promotional campaigns, planogram changes, and other marketing initiatives before rolling them out nationally.
The Solution
Antuit established a 'Test And Learn' program to incorporate predictive analytics into the company's decision-making processes for marketing initiatives. Using a wide range of internal and third-party data, such as demographic profiles, volume, seasonality, historical sales numbers, and weather data, Antuit helped identify suitable test and control participants and regions. Matching test and control markets was critical to yield the most accurate metrics. In cases where an appropriate control market did not exist, Antuit created a 'pseudo-control' using an accurate base forecast to replicate a relevant control market. Through the program, Antuit enabled the company to measure revenue lifts as small as 0.1% with good statistical confidence, an especially powerful capability for products with razor-thin margins. The results have been used to make better decisions regarding when, where, and how promotions should be rolled out across regions, markets, and retail distributors.
Operational Impact
  • Within the first 6 months of the initiation of the program, Antuit helped the company test more than 30 promotions across the adult nutritional products business.
  • The Test And Learn program provided distinct profiles of the top-performing test locations for each promotion, allowing the organization to better determine where future campaigns should be launched.
  • The company now has increased visibility into promotion performance prior to full-scale rollout.
  • By obtaining these early learnings, the company can profitably target promotions and allocate resources to drive the greatest revenue lift per store and ROI from campaigns.
  • The organization continues to utilize Antuit’s 'Test And Learn' solution to evaluate other types of marketing initiatives such as product consolidation and the addition of new products.
Quantitative Benefit
  • The Test And Learn program measures lifts in revenue as small as 0.1% with good statistical confidence.

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