Building AI to drive B2B marketing through the Integration of Content Intelligence, Recommendation and Conversational Agents
Building AI to drive B2B marketing through the Integration of Content Intelligence, Recommendation and Conversational Agents The Challenge A leading SaaS platform for B2B marketing in the US, aims to nurture prospects, improve content performance by delivering intelligent content experiences and virtual events across the buyer’s journey and improve win rates. Tatras Data was asked […]
A LLM based customer service tool in complex engineering environments
A LLM based customer service tool in complex engineering environments The Challenge World’s leading specialist in water treatment needs to unlock the knowledge within a large repository of technical specifications, user manuals and product sheets to support their customers and customer service representatives/account managers in supporting issues with a customer installations. The objective is to […]
Generative AI/LLM Based Customer Service and Advanced Product Recommendation Engine For Ecommerce
Generative AI/LLM Based Customer Service and Advanced Product Recommendation Engine For Ecommerce The Challenge A startup in the US aimed to provide boat owners with expertise on boat and engine maintenance through use of a GenAI based chatbot. The firm also aimed to generate revenue through highly personalized product recommendations for boat maintenance items in […]
Intelligent Chatbot Authoring Platform using Sentiment Analysis & Neural Network
Intelligent Chatbot Authoring Platform using Sentiment Analysis & Neural Network The Challenge Well before the advent of Generative AI, our client (in 2016), identified an opportunity to disrupt chatbot technology by building an intelligent chatbot authoring platform. Platforms for chatbot creation, at the time, required significant crafting from chatbot authors and had limited domain definition […]
Predicting In-Store Promotion Effectiveness Linked To Macro Marketing Campaigns
Predicting In-Store Promotion Effectiveness Linked To Macro Marketing Campaigns The Challenge A leading electronics retailer invests in marketing to increase the footfall in their stores. In-store promotions then try to convert visitors to buyers and increase the value of their basket. The company wanted to predict the effectiveness of different campaigns given the marketing campaigns […]
ML Based Optimization Model Of Merchandise Product Mix Using Neural Networks
ML Based Optimization Model Of Merchandise Product Mix Using Neural Networks The Challenge Our client, a popular retailer in the United States, wanted to increase revenue from each of their stores by improving merchandise effectiveness in their physical stores . They wanted to determine what products should be introduced, stored, or discontinued at each store […]
Improved Resource Allocation Based On Footfall Forecasting In Stores Using Neural Networks
Improved Resource Allocation Based On Footfall Forecasting In Stores Using Neural Networks The Challenge A leading electronics retailer in the Middle East invests in various forms of online advertising to increase footfall in their stores. The management wants to understand the impact of the different investments. They also want to forecast what footfall they can […]
Fashion Apparel Product Recommendation Engine With Automated Tagging and Consumer Preference Data
Fashion Apparel Product Recommendation Engine With Automated Tagging and Consumer Preference Data The Challenge A large fashion retailer in the UK wanted to build an online apparel fitting application as the manual effort in tagging dresses was fraught with inconsistency, errors and not efficient for online shoppers. The current process resulted in incorrect sizing and […]
Leveraging AI/ML In Ecommerce For Lifetime Value Analysis & Autonomous Bid Management System
Leveraging AI/ML In Ecommerce For Lifetime Value Analysis & Autonomous Bid Management System The Challenge A US-based ecommerce player, was facing a squeeze on profitability. Given rising cost of customer acquisition through digital marketing and having to drop prices due to competitive pressures, the firm wanted to optimize marketing spend on consumers with positive long-term […]
Improve Power Generation Forecasting by Neural Networks & Time Series Forecasting
Improve Power Generation Forecasting by Neural Networks & Time Series Forecasting The Challenge A wind farm in Europe, supplying power to the electric grid was having a high margin of error of 30% in its output prediction, resulting in high penalty to the grid. ( Errors greater than 10% incurred a penalty ). They needed […]