Industry Reinvigorated: Consumer Products and Retail

Bridging the gap

Continually sensing what people want and delivering adaptive value

Industry Reinvigorated: Consumer Products and Retail

Bridging the gap

Continually sensing what people want and delivering adaptive value

Advanced Analytics in manufacturing, consumer products, and retail

The manufacturing, consumer products, and retail industries are always looking for new ways to attract customers and drive costs down. While online shopping has exploded, it has come with its downsides. Machine learning and AI are now bridging that gap, allowing for smoother buyer-seller interactions and creating surplus value. No more frustrating searches for customers or missed profits for sellers.

These companies are constantly adapting to meet the evolving needs of their consumers. However, gaining insight into customer preferences, operating costs, performance trends, and supply chain networks can be complicated by legacy systems and data silos. This can hinder advanced analytics, jeopardize data security, and make sharing live data impossible.

Fortunately, nearly all mid- to large-enterprise organizations have turned to the cloud to transform and scale their analytics capabilities. The Snowflake Cloud Data Platform enables organizations to glean insights across the value chain and use data to drive powerful revenue growth. With Snowflake, companies can optimize inventory management and fulfillment, and deliver personalized multi-channel experiences that consumers expect.  We recommend Snowflake to unlock data-driven insights and stay ahead of the curve.

Retail

Cloud Data Platform

Predicting customer preferences is a crucial aspect of any retailer’s success. With the help of AI, products can be categorized and customer viewing and purchasing history can be analyzed to predict their next purchase. But what’s next? Building a Cloud Data Platform to provide real-time data for more accurate recommendation engines is the future of retail.

Learn how retail, manufacturing, and consumer goods organizations are scaling their analytics capabilities to optimize every area of their business, from driving supply chain efficiency to optimizing inventory management and fulfillment. Discover how these organizations are leveraging data to make informed decisions and stay ahead of the competition.

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Consumer Products

Search Relevance

Again utilizing the millions of searching and buying data points generated by online consumers, a reliable search engine is the first step in retention and satisfaction. A search engine must act as the online sales representative, directing the shopper to exactly the item they were looking for.  And through machine learning, as the system sees more searches and hit results, it will continuously improve its output.

Wholesale & Distribution

Inventory Management

Artificial intelligence can be used for more than just customer interaction. Connect your inventory database to a machine learning system to improve the processes through which inventory is managed and re-stocked as well as predict when certain products will be in high demand and ensure that you can be prepared accordingly.

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Wholesale & Distribution

Supply Chain

Almost every modern consumer product provider is vertically oriented, in that their product passes through many different stages and in many cases through several different enterprises, before the final product is ready to be sold to the public. Artificial intelligence helps to integrate that supply chain and make it more manageable for all parties, limiting carrying costs and conveying information in real time across stages of production.

How Dayton Analytics can help

We help harness the power of artificial intelligence, drive digital transformation and build digital teams via our future of work approach to knowledge worker alignment.

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