The Vital Role of Machine Learning in Customer Loyalty

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The ongoing shift caused by Machine Learning has laid the foundation to increase value from the customer data and anticipate the shopper behaviors’ patterns in order to predict the future buying decision and create a personalized customer experience. 

As retailers and consumer brands invest in Machine Learning, the benefits will extend far beyond business performance. Meanwhile, experts of customer loyalty programs envision that by using automated marketing tools, the customer service will be elevated and the customer journey will be optimized.

A better understanding of Machine Learning

Source: SAS, 2014 and PWC, 2016

Given the dynamic nature of Machine Learning, marketers will come across the below key challenges towards the shift from the traditional customer database model to an advanced CRM, powered by AI solutions.

  • Manage to collect the customer data across all touchpoints in real-time
  • Analyze valuable customer insights; behavioral and transactional activities and turn them into business knowledge
  • Maintain & improve the performance of algorithm and managing at the same time huge volumes of diverse customer data and different patterns

Applying Machine power to customer loyalty programs

The segmentation of customer data into unified profiles, based on shopping patterns, can enhance highly personalized marketing campaign to an accurate target group and maximize the efficiency of the campaign. The hypersegmantation can also be applied, by dividing customers with similar and unique attributes into groups, such as promo-sensitives, seasonal fans or sports lovers. Another insightful example is that valuable insights, along with machine learning tools, can lead to an effective real-time product recommendation, while the customer visits the store, either online or offline.

Automation tools provide a deeper and precise knowledge of consumers’ demographic data, preferences and other important customer information. Therefore, it is of high interest for retailers and brands to conquer the above knowledge and finally manage to optimize marketing campaigns, modify communication messaging, when it is necessary and deliver targeted content, faster and in a more accurate way. In addition, machine learning tools are able to predict fraud in loyalty programs, by detecting inconsistencies and abnormality activities. As a result, the system can provide to the marketer high-end resources regarding customer data, by eliminating fraud issues.

Machine Learning plays a significant role in brand loyalty.
Creating a customer journey that reassures the retention of the existing customers and the acquisition of new ones, which is based on the commerce metrics and shopping patterns. Similarly, executing a successful loyalty campaign management, that is based on leveraging customer data to unlock consumers’ behavior. In conclusion, delivering a holistic customer service across all different channels can boost significant KPIs: conversion/retention rates, store visits and average basket.

Acknowledging the importance of data-driven decisions, the machine learning tools will not only help marketers to gain more time in high-level thinking but also transform the traditional give-and-get relationship to a successful customer engagement journey.

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