ice cream Labs uses machine learning to drive ecommerce

ice cream Labs uses machine learning  to drive ecommerce

ice cream Labs uses machine learning and visual intelligence to drive ecommerce

The founder and CEO of the artificial intelligence start-up which is headquartered in San Francisco- Madhu Konety consider the solutions prepared by IceCream Labs to be both sticky and sweet. In order to improve content, increase consumer engagement, improve merchandising productivity and accelerate revenues at two of the world’s biggest retailers the company has leveraged the power of machine learning and visual intelligence.
According to Konety, they help the retailers by providing the product data, marketing data and consumer data, so that the products would be according to the preferences of the customers. If the customers are shopping online, their solutions help them to find what they really want. Moreover, these models are built by using the subset of AI called neural networks, or deep learning. If there is a large amount of data, deep learning has the ability to recognize it and then provide cognitive visibility.
Madhu Konety further says that the content of over 100 million products is processed and profiled by the applications of their platform. Their big data algorithms empower as much as 50 million images. Neural networks work this way. It’s essentially mapping human neurons onto machines.
Moreover, the algorithms developed by them teach machines to learn like human beings. It just works like how we teach kids about different things. For example, if you need to teach a child what a chair is, you need to show him/her various types of chairs. He/she is then able to recognize a chair. Algorithms work on the same principle.
Furthermore, the on-demand intelligent merchandising for retailers, brands, suppliers, and manufacturers is delivered by IceCream Labs’ catalog management, category management and consumer insights systems. For instance, for the automatic enhancement of content listings catalog management uses machine learning models. The product gap with market intelligence is filled by category function. Similarly, the tool that allows users to assess impactful customer insights capable of driving revenue is the consumer insights.
Additionally, according to Konety, they are concentrating on the merchandising space in the present time. They help the retail sector understand what consumers are looking for in order to make sure that they’re presenting the information and product that is relevant to that consumer.
Similarly, to make sure that the product descriptions are relevant for diverse shopper demographics, IceCream Labs systems raise the bar on relevancy. For the convenience of consumers they have created descriptions in multiple writing styles, so a retailer can have a Millennial style, or a Gen X quality. In the same manner, they have personalized the product assortment as well as product content. Neural net can do these kinds of things.
Besides, IceCream Labs have now started working with a very larger retailer which is looking to raise product assortment by a multiple of 100. He further says that a significant bump in revenue has been delivered by the programs it has put in place.  Depending on the product, the retailer has achieved from 20 percent to 200 percent increases in revenue. It is done by making sure that consumers are seeing complete product information.

Konety Elaboration about ice cream

Konety elaborates that, except software installs and security hiccups, what differentiates IceCream Labs is its ability to work with large data sets but the speed of implementation and the fact that it runs in the cloud. Moreover, Konety says that the start-up has a team of computer science geeks which has deep experience building complex enterprise solutions. Additionally, according to Konety they eat and breathe AI which is a type of talent that is not easy to come by. Moreover, it allows IceCream Labs to amortize the cost over multiple customers.

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