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Digital E-commerce PowerPoint Presentation

Digital E-commerce PowerPoint Presentation

I completed successfully our 9th mutual project with Misha Williams, a Harvard graduate, an award-winning entrepreneur and e-commerce business leader, which subject was the importance of neural intelligence in e-commerce.

He was fascinated by the result:

'Perfect as always.'

About Brand Algorithmic

We are an e-Commerce Artificial Intelligence focused consulting firm. We leverage 20+ years of experience in Internet Marketing, Analytics, Data Science and AI to help our clients increase their value proposition to their customers.
We are in the age of the customer - a time when consumers are in the driver's seat - and with the increase of competition in every industry, businesses are fighting to deliver the best experience to users as it has been proven that personalized experiences drive conversions and increase.
Personalization is thus becoming central to the customer’s experience of a brand—and as important as the products themselves in providing competitive advantage.
Machine Learning Analysis is a field of AI where it's all about pattern recognition. Patterns can be discovered through data segmentation, anomaly detection, and  neural networks.  Analytics and AI are a powerful technology package and individually, are the top two drivers of personalization and brand loyalty today.
When brands have this easier way to process and understand millions of interactions with each customer; those interactions can then be used to understand each customer as an individual.
These innovations in technology have made it so that businesses have to change their tactics and communicate with customers in real-time.
Regression is the mathematical relationship between two or more variables. A key business outcome is analyzed against contributing factors to realize the nature of the contribution. Also a method for speculating future values of a KPI.
Recommender systems match customers with products. A database is built of customer demographic information (non-identifying information), and match this up with sales records . In a ARM model, the probability that a user would purchase a product is the result of at least three probabilities:
The probability that others of the user’s age range bought the product
The probability that others of the user’s gender bought the product
The probability that others of the user’s occupation type bought the product
Neural networks learn patterns in human behavior and is able to predict choices. Neural networks mimic how the brain processes information. In the Human brain neurons  ‘fire’ electrical signals when a  stimulus is perceived.
Neural Networks learn on the go with each new user action. Learning incrementally allows NN to evolve a user’s preferences. This means that personalization with NN is contextual (and therefore more ‘personal’) and even predict what they will do next.
It begins with an Ontology of the behavior to be modelled. An Ontology is a classification system for a set of objects. For an e-commerce site, we source our required ontology from the fields in the product database.
The ontology is a multilayer digit mapping procedure that takes the various layers of data we want into consideration (these may include product properties - manufacturer detail, item type, physical properties - size, material/fabric, color, range of functions or features, product prices, payment options and modailities, etc. )


 

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