3 ways Artificial Intelligence and Machine Learning improve CX

3 ways Artificial Intelligence and Machine Learning improve CX

Artificial intelligence (AI) tools make it possible to easier anticipate customer needs in multiple ways. For example, marketers can analyze vast volumes of customer data, identifying the characteristics of high-value past customers which allows businesses to create highly personalized campaigns. Sales teams can quickly identify customer purchasing patterns and customer service reps can deliver relevant actions and sales offers.

3 Benefits of Using Artificial Intelligence

1. Improved matching of customer needs and products

Improving relevancy when it comes to offering products is a major factor for increasing customer lifetime value and the return on investment.

By using big data and machine learning, businesses can offer relevant products that match their customer’s exact needs. Recommendation systems are used to suggest products to customers that they are more likely to buy. Having access to vast amounts of customer data such as price range, preferences and buying cycle, businesses can target customers with specific offers.

With the help of AI recommendation programs, customers can be given personalized information at the right time in the customer’s journey. What this means for businesses is improved and more sophisticated communication with customers, and consequently increased revenues and in the long term, customer satisfaction.

2. Personalization remains key in customer communication

Customers today are savvy and can sense when they’re being marketed to by generic email blasts (when was the last time you deleted an email feeling it wasn’t relevant or not personalized enough – not too long ago, we suspect!).

This is nothing new for marketers. If you don’t personalize content, you lose out on valuable communications opportunities. Over 85% of mobile marketers’ report success with personalization in the form of higher engagement, revenue, and conversions (Wharton University, 2016).

Personalization techniques such as geo-fencing and loyalty programs are combined with AI algorithms to predict customers’ needs and desires. Geo-fencing provides location-based marketing messages, and loyalty programs reward customer loyalty and intensify customer advocacy over time.

3. A smooth virtual experience is a priority

Today, purchase decisions are often based on emotional needs, not just practical needs. The actual pleasure and ease of the buying experience are equally as important as the quality of the product itself. Thus, customers prefer brands who can cater to both of these needs.

By studying customer behavior in various stages of the buying cycle, and on websites, advanced analytics helps to test and improve the customer experience over time. For example, companies use it to make it as easy as possible for customers to navigate their site or answer customer queries faster, ultimately saving customers time (NewgenApps, 2017).

Watch this space for more blogs and AI insights.

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