AI for


Revolutionizing Retail Intelligence with Unified Data Management


Use Cases for AI in Retail

Shakudo is proud to be working with leading Retail organziations on many AI use cases, including:

Robust Demand Forecasting

Retail organizations are layering AI across their data to predict demand based on various factors such as historical sales data, seasonal variations, weather patterns, and even events.

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Accurate Inventory Management

Retail companies are layering AI across their data to predict demand based on various factors such as historical sales data, seasonal variations, weather patterns, and even events.

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Price Optimization

Dynamic pricing based on AI analysis of competitor pricing, demand elasticity, and customer behavior helps retail remain competitive while maximizing profits. These complete data signals mean more fine-grain control and the ability to adjust pricing in real time.

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Personalized Marketing and Recommendations

With integrated data across the customer journey, retail can now analyze purchase histories with AI to personalize recommendations. This includes targeted promotions, coupons, and suggestions enhancing the overall customer experience.

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The Pitfall of Data Silos in Retail Chains

In the dynamic world of retail, the underutilization of data from customers to suppliers often lies at the heart of missed business opportunities. To effectively uncover business intelligence as a retail, data needs to be accessible to stakeholders across the entire organization. And as today’s retail companies deal with an ever-expanding amount of valuable data, their previous data management solutions are not scaling with the increased business demand around data use cases.

Data fragmentation has many repercussions: ineffective demand forecasting, poor supplier management, inaccurate pricing models, and even untapped customer segments. These data silos are not merely obstacles but, when left unaddressed, can significantly impact profits and escalate losses for retail chains. The shift toward scalable solutions to data integration and orchestration within retail chains is critical to maintaining a sustainable, competitive edge.

Why Industry Leaders in Retail Choose Shakudo

Seamless Data Integration

Shakudo simplifies the integration of diverse data sources through user-friendly tools like Airbyte. We ensure a seamless connection to any data source, and remove the need for custom integrations. Whether it’s supplier, logistics, customer, or operational data, our platform can handle it.

Robust ETL Pipelines

Leveraging tools such as Airflow, Dagster, and Prefect, the platform offers robust Extract, Transform, Load (ETL) pipelines. These pipelines form the backbone of a reliable data ecosystem, ensuring data flows consistently and continuously throughout the retail chain's data stack.

Access to Powerful BI Tools

The platform brings immediate access to leading Business Intelligence (BI) tools like PowerBI, Superset, Looker, and more. This access empowers commercial real estate organizations comprehensive analytics and reporting capabilities, transforming raw data into actionable insights.

Data and AI in a Single Platform

Beyond the data and business intelligence, Shakudo offers direct access to leading AI solutions like vector databases, large language models (LLMs), model experiment tracking, and more.

Shakudo Enterprise Data Platform

Shakudo: The Operating System for the Data Stack

Shakudo serves as the centralized operating layer for all retail chain data, providing complete visibility and control. It offers data scientists and analysts an integrated platform to develop and deploy applications utilizing the industry's best-in-breed tools, with security and privacy controls at the center of the solution.

Reach out to speak with a Shakudo expert to learn more about how the platform can unify your organization’s data for improved intelligence.

Thank you.

We’ll be in touch shortly. In the meantime, feel free to check out our latest data insights, Shakudo success stories, and resources that help data teams win.
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