Industry Reinvigorated

Consumer Products & Retail

Machine Learning Optimizing the Ways We Shop

Industry Reinvigorated

Consumer Products & Retail

Machine Learning Optimizing the Ways We Shop

Advanced Analytics in Consumer Products and Retail

The retail industry has always been one that is ripe for new methods and ideas, 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 for brick-and-mortar and online retailers alike that they may have never even known was there.


Recommendation Engines

One of the most important tools for any store 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 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 consistently more accurate recommendation engines is the next frontier for online shopping.

Learn how enterprise AI is reinvigorating industry.


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.

Our latest thinking

Like what you’ve seen? Get in touch to learn more.

All fields are required