Using Machine Learning to Drive Deep Personalization with Data: The Salesforce Model

The application of artificial intelligence (AI), known as machine learning, involves generating predictions from data inputs. One of its most surprising strengths is how machine learning (ML) drives the relationship between digitization and customer personalization.

“Digital has bred customer-centricity,” said Neeracha Taychakhoonavudh, Salesforce’s EVP of Global Customer Success and Strategy.

Harnessing digital and data, especially through ML, enables speedy, rich customer relationships and allows companies to move toward hyper-personalization.

“Personalization is the lifeblood of customer loyalty,” Taychakhoonavudh said.

Thanks to ML such as Salesforce Einstein, companies can create highly relevant messaging for the customer journey that improves the experience and increases brand loyalty.

Think of it this way: Machine learning can reinforce a company’s well-established strengths.

For instance, experts recently singled out Salesforce as one of the world’s “most admired brands” in the report “Moving Beyond Trust: Making Customers Trust, Love, and Respect a Brand,” published in MIT Sloan Management Review. The authors used a decade’s worth