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Sigmoid’s ML based solution enabled a leading CPG company specializing in health, hygiene, and nutrition products to improve target audience conversion rate on Amazon ads portal by leveraging extensive data from both first party and external data sources.

Sigmoid optimized Snowflake's performance by implementing best practices for data migration, resulting in a 10X improvement in the efficiency of data pipelines.

Sigmoid implemented cloud-agnostic, Low Code/No Code tools that integrated multiple data sources with varying levels of granularity. The solution leveraged data pipelines to create multilayered dashboards with critical brand performance metrics such as brand loyalty, operational excellence, profitability, and more.

Sigmoid built a unique AI deployment environment for a leading CPG brand that allowed multiple business teams to run ML models and scale them across multiple departments and geographies. It ensured faster deployment of ML models across while reducing the cost of running models by 2x.

Sigmoid built an efficient and near real-time ETL data pipeline for the customer that resulted in faster query processing time and increased scalability. The solution facilitated centralized monitoring of dashboards allowing quick identification and resolution of machine downtime.

Sigmoid helped a global F&B major with a ML solution to align their brand strategy with business rules and promotion guidelines that led to an improvement in market share by 0.8% and 3% improvement in contribution margin.

Sigmoid helped a leading alcoholic beverage company predict demand accurately to optimize their supply chain, improve inventory management and improve risk mitigation.

Watch this case study to find out how Sigmoid helped a leading FMCG in the oral care segment build automated data pipelines to migrate their digital media data to Snowflake to overcome inconsistency and manual efforts of loading data.

Sigmoid developed an end-to-end Google cloud monitoring and optimization solution to reduce wastage on the data infrastructure costs for a leading CPG company.

Sigmoid developed an ML-based order recommendation engine for a leading CPG company for effective management of inventory and recommending new products to boost retail sales growth.

Sigmoid helped a top-tier investment bank set up trade surveillance and make it regulatory compliant by setting up Spark-based ETL pipelines. We revamped existing systems to ensure optimal performance for the order of their trade surveillance while ensuring resource optimization and creating faster response times.

Sigmoid built a solution to efficiently predict scenarios based on optimization of important KPIs such as capacity utilization, safety stock maintenance, inventory to be maintained, raw material availability and scrap minimization for a fortune 500

Sigmoid built a tactic-based data model for a Fortune 500 food manufacturing firm to standardize the input files from different data providers, agencies, and channels.

The interactive dashboards help marketing managers and brand leaders to optimize performance, justify media spend and improve ROI.

Sigmoid developed a solution using MLOps that reduced the time to train the model and automated the model training. The solution resulted in 90% improvement In ML model run time.

Sigmoid created an automated solution to suggest recommendations and campaign strategy changes for various online platforms such as Amazon and in the long run, improve organic sales.

Sigmoid built and automated an AI system for a leading CPG – food and beverage company to improve the overall equipment effectiveness (OEE) of machines on their production lines.

Sigmoid developed ML based prediction models based on granular understanding of different customer segments to predict those likely to churn and improve the retention rate.

Sigmoid developed highly scalable data systems to ensure 99.99% uptime, zero outages and seamless deployment of new applications for a leading cloud service provider.

Sigmoid built a data foundation for a leading CPG company to leverage data from different retailers in near real time and enabled automated reports, reducing the time to access data from 7 days to 2 hours!

Sigmoid’s accurate demand forecasting solution reduced inventory handling costs & reduced time to plan campaigns by 66%.

Sigmoid productionized the MAB model for a major restaurant chain that delivered tailored emails to over 12Mn customers resulting in 8% sales uplift.

Sigmoid developed a Spark based system for a leading AdTech company that optimised their data infrastructure landscape resulting in $2.5Mn+ annual cost savings and faster query processing.

Sigmoid improved CLTV& increased sales per order by 24% for a leading cosmetics giant by developing scalable personalised strategies using advanced ML algorithms.

Sigmoid enhanced marketing effectiveness by building Multi-Touch Attribution models on Azure using Rule mining and predictive ML algorithms leading to an increase in Marketing ROI.