Growing Customer Loyalty with Targeted Promotions
Company Size
1,000+
Region
- America
Country
- United States
Product
- AnswerRocket
Tech Stack
- Natural Language Processing
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Natural Language Processing (NLP)
Applicable Industries
- Food & Beverage
Applicable Functions
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
Services
- Data Science Services
About The Customer
Food Service Rewards is the industry’s largest loyalty program, working with over 60,000 restaurants and 350 food manufacturers. Chefs earn rewards for the products they buy from distributors like Sysco and US Foods, while manufacturers like Tyson and Unilever gain downstream visibility into customer purchase patterns. Leveraging this data, manufacturers can combat substitution, expand product placements, and sell more cases by offering targeted rewards.
The Challenge
Food Service Rewards was facing a challenge with their traditional data analytics platform. The platform was not user-friendly and could only be operated by specialists with technical training. This led to a bottleneck situation as requests for data queries piled up. Moreover, by the time the results were generated, the need for that particular insight had often passed. To run a successful loyalty program, the team needed faster insights that would help them better understand customer churn and purchasing behavior to create more effective promotions.
The Solution
Food Service Rewards adopted AnswerRocket, a solution that uses natural language queries to enable everyone, regardless of their technical skill, to query the data and receive instant insights. AnswerRocket saves hours of time each week, allowing teams to show customers critical data insights directly on Zoom calls. These insights on customer purchasing behavior are an enormous competitive advantage, as most manufacturers in the restaurant industry don’t control their distribution. This newfound visibility into when customers start or stop buying has enhanced the team’s ability to create targeted promotions and minimize churn.
Operational Impact
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