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 & retail

The manufacturing, consumer products, and retail industries have always been ripe for new methods, with seemingly infinite ways to attract new customers, encourage more purchases, and drive costs down. For example, online shopping exploded in the past decade, with so many preferring the experience at home to visiting a store. But there have been downsides, for both the customer and retailer. For example, there are no employees to ask for help finding something online, leaving the shopper frustrated and the seller missing out on a potential profit. Machine learning and artificial intelligence look to bridge that gap, allowing the buyer-seller interaction to happen more smoothly, helping one better understand the other, as well as creating surplus value that had not been realized.

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Cloud Data Platform

One of the most important capabilities is trying to predict what a customer will want to buy and how to market their products to that person based on those predictions. Artificial intelligence works to log and categorize each product in a store according to its characteristics, and it uses a customer’s viewing and purchasing history alongside what other customers who bought similar products have liked. A computer algorithm then judges which products they’ll be most likely to find attractive next.  Building a Cloud Data Platform to provide nearly unlimited real-time data for consistently more accurate recommendation engines is the next frontier in retail and consumer goods.

Learn how retail and CPG organizations are scaling their analytics capabilities to optimize every area of their business, from driving supply chain efficiency to optimizing inventory management and fulfillment.


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.


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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