Customer experience professionals have been obsessed with mapping customer journeys — optimising business processes and streamlining the passage of engagement.

These maps or flowcharts are meticulously designed to guide customers effortlessly from Point A to Point B, to complete their purchase, or to get help. Yet prospects and customers still get off the planned route, choose a different path, or simply get distracted.

In business, it’s imperative to guide prospects and customers to where they should be. We need to shape customer journeys — in real time — not just map them and hope they follow the directions.

Web sites are built with a purpose: sell products, enable signup for services, or provide help. Guiding users when they are distracted or lost has massive benefits for prospects, customers and the businesses with which they deal.

Enabling this predictive engagement beyond the web site — and across other channels — adds greater value and guides prospects and customers to positive outcomes.

Leveraging the power of artificial intelligence (AI) and machine learning, using real-time insights, — and proactively engaging at the right 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 a financial services site from a Google Ad.

“It’s obviously important that the site personalises 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 recognising 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 per cent and increased high-value sales by three per cent 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 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,” he added.

About the author

Brendan Dykes is the senior director solution and product marketing at Genesys who is a member of the Which-50 Digital Intelligence Unit. Members provide their insights and expertise for the benefit of the Which-50 community. Membership fees apply. 


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