Staying ahead of the curve is critical in today’s dynamic business environment, particularly in the Retail and CPG sectors. Our Gen AI orchestrator- JIVA, tackles key challenges in deploying Gen AI solutions, including accuracy, traceability, security, scalability, and cost-efficiency. By integrating structured and unstructured data, JIVA enables organizations to execute advanced queries with large language models (LLMs), enhancing data analysis across enterprise departments. JIVA can address a multitude of use cases, such as delivering personalized customer experiences, optimizing inventory management, leveraging predictive analytics for market trends, and much more in Retail and CPG.
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Persona-based use cases specific to Retail & CPG
CUSTOMER SERVICE REPRESENTATIVE
Customer query or issue resolution requires unstructured data (e.g., Standard Operating Procedures, Customer Comments) and structured data (e.g. customer profile, customer ticket, relevant promotions, etc.) to effectively and expeditiously resolve customer queries.
STORE ASSOCIATE, MANAGER
Store Associate requires unstructured data (e.g. Store Standard Operating Procedures, Item descriptions, etc.) structured data (e.g., Item Location, Inventory, Promotions, Customer profile, etc.) to execute store processes more accurately and provide better Customer service in-store.
PROCUREMENT MANAGER
The procurement Manager requires unstructured data (e.g. Supplier Contract, RFI/RFP Templates, Responses, Market Reports, etc.) and structured data (e.g. Service levels, Contract Compliance, etc.) to effectively find new suppliers, carry out RFI/RFP process, negotiate better during contract & supplier reviews.
CATEGORY MANAGER
Category Manager requires unstructured data (e.g. Market share reports, product reviews, competition reports, etc.) and structured data (e.g. sales, orders, inventory, promotions, pricing, etc.) to make the winning decision to put the right product in the right store, at the right price.
ECOMMERCE CATALOG OWNER
There is a need to optimize item descriptions in the Catalog using unstructured data (e.g. Brand Item description & features, competitive item description, etc.) and structured data (e.g., sales, market share, share of search, etc.) to drive a higher share of search and conversion.
MARKETING ANALYST
Marketing Analyst requires unstructured data (e.g Market Survey reports, competitive promo content, etc.) and structured data (e.g. Sales, Product Master, Customer Profiles, etc.) to analyze surveys and research reports faster and derive insights to improve product design, communication, and packaging.
