Tuesday, August 20, 2019

How Artificial Intelligence and Machine Learning Shape Customer Journey


Customer experience professionals have been obsessed with mapping customer journeys — optimizing business processes and streamlining the passage of engagement.
Leveraging the power of artificial intelligence (AI) and machine learning, using real-time insights, — and proactively engaging at the right the moment through the best channel for prospects, customer and the business — drives outstanding business results.
Carl Jones, Predictive Engagement Lead ANZ at Genesys said in an online interaction that there are multiple points where #AI and #machine learning can play a positive role in customer experience.
Jones gave the example of searching “low rate credit card” which lands on financial services site from a Google Ad.
“It’s obviously important that the site personalizes the landing page and content offers to reflect the customer’s intent — there’s not much point in showing insurance offers if they are looking for a credit card.
“But, it’s also really important that the customer is proactively assisted to apply for the right card for them. This proactive approach isn’t simply a matter of popping a chat window after 20 seconds and hoping for the best, but recognizing that the customer has issues or questions or is struggling and interacting with them in the best way possible.”
For example, in the UK, Smyths Toy Superstores reduced its shopping cart abandonment rate by 30 percent and increased high-value sales by three percent by engaging customers at the right time.
Jones said this is where AI and machine learning really assist, as its simply not possible or cost-effective for humans to watch all the traffic on a web site, decide what the prospect is trying to achieve, and interact with the most valuable prospects via the most effective method.
AI can decide how to interact with a customer — for instance a chatbot or a human and in fact which a human agent would be the most effective to interact with the customer based on agent previous success.
“The overall  outcome of this multi-touchpoint AI approach is that more prospects reach the point, sometimes with assistance, of completing the purchase or application process”.

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