EFA - Protecting your rights as an ecommerce business and expressing your needs to the relevant government departments and opinion formers

Getting the most out of Customer Data

There have been an increasing number of articles and TV programmes on the use of personal data. As this Newsletter has reported, the POPIA law is still not fully implemented, although there are signs of movement. In a recent study of 1,000 individuals (from Gen Z to Baby Boomers), reported on by Oracle, 57% said they would share their personal data with brands in exchange for custom-tailored experiences. But only 15% of those respondents had any faith that brands would actually deliver personalized experiences to them. As Oracle points out, the biggest problem for most marketers is that they lack a customer data strategy.  Oracle advises:

  1. Unify customer data across business applications, communications channels, and connected devices.

In most companies, customer data is managed in discrete storage silos, which have limited direct integration to marketing, sales, service, and commerce applications. These data silos make it difficult for marketers, or any customer-facing personnel, to understand who their customers are, let alone influence their purchasing decisions in any meaningful way.

  1. Organize customer data so it can be modeled by AI and then used in a way that aligns to your company’s top business priorities.

Machine-learning algorithms can model massive amounts of customer data instantly. This helps marketers predict which leads are most likely to convert into sales, and then prescribes what actions they should take in order to help sales teams quickly close those deals.

  1. Use a decision-making platform to recommend certain products or services to offer customers in the precise moments when the customers are most likely to purchase them. Most marketers today only know when certain offers were sent to customers and how those customers responded. This is where customer intelligent platforms can help, by instantly capturing online and offline marketing, sales, and service data, applying machine-learning algorithms to that data in real time, and then presenting each individual customer with offers that are most relevant to them. Marketers will make their customers happier and more loyal, and their companies more profitable.

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