Authored by Adrian Towsey, Area Vice President at Salesforce leading the Emerging, Small & Medium Business segments across Australia & New Zealand.
Customer service is in a state of flux. As budgets and staffing levels increase, so have customer expectations, keeping efficiency critical for delivering higher quality of service.
Today’s customers demand fast, consistent, and personalised interactions, yet service teams are spread thin, with inefficient processes and manual taskwork monopolising agents’ time and jeopardising the customer experience.
This is according to Salesforce’s latest State of Service report, a survey of over 5,500 service professionals across 30 countries, which reveals how high-performing organisations are exceeding customer expectations and how laggards can improve in an artificial intelligence (AI)-first world.
While widespread adoption of AI may still be in its early stages, benefits are already clear, enabling teams to achieve the speed and quality of next-generation service. Among service professionals at organisations investing in AI, 93% say the technology saves them time on the job.
With more and more customers – 88% and growing according to our research – saying good service makes them more likely to purchase from the same company again, it’s clear that customer experience will continue to be key to driving revenue.
Service as a source for revenue generation
Where service has historically been seen as a cost center, more and more service decision makers are reporting that their teams are expected to contribute a larger slice of revenue over the coming year through upselling, cross-selling, and customer retention.
On top of increasingly sophisticated demands from customers, higher case volumes mean a rising workload and more time spent on internal meetings, manually logging case notes and other mundane tasks, and less time on servicing customers.
Currently, agents spend just 39% of their time servicing customers amid competing demands like internal meetings, administrative tasks, and manually logging case notes.
A connected experience is a huge differentiator for companies. High-performing service organisations are more connected to other departments, sharing goals and technologies with sales and marketing. Fragmented workflows, on the other hand, not only slow agents down but also increase the risk of error and can be costly for an organisation’s bottom line.
It’s not just a game changer for big enterprises either. Take the perspective of an innovative local SMB here in Australia, Magentus, a health technology company that provides health platforms for every aspect of a healthcare network, from clinical systems and practice management, to health informatics and patient safety.
They spoke in Melbourne recently about how businesses of any size can increase the impact of their sales and service teams using AI, regardless of the size of the business. Vitally, it means that small businesses no longer have to compromise customer relationships for efficiency.
Boosting customer experiences, and helping agents become more strategic
For years, companies have used predictive AI for tasks like providing next best actions and analysing trends. Today’s generative AI can create original content like text, imagery, and video using large language models.
This may be why, despite being fairly new, generative AI is quickly gaining traction, giving employees the time and tools to do their best work. Among service professionals at organisations investing in AI, 93% say the technology saves them time on the job.
AI-powered generation of comprehensive summaries and status reports, deployment of customer-facing AI intelligent assistants to respond to queries in real-time and crafting of self-help knowledge articles all clear the way for employees to focus on more fulfilling and higher value work, such as building customer relationships and resolving complex cases.
Analysing customer behavioural trends by tapping into historical data to provide next best actions also keeps customers satisfied, and most importantly, coming back, and the latest State of Service report found that 83% of decision makers plan to capitalise on this and increase investments in automation over the next year.
Empowering customers to solve their own issues with AI-powered self-service tools can be a win-win for customers and organisations, too, catering to customer preferences while saving resources.
From knowledge-powered help centres, to customer portals, to AI-powered chatbots, self-service tools are transforming the efficiency of high-performing service organisations.
AI Drives demand for trusted data
AI and automation can help agents deliver enhanced customer experiences to balance new demands in ways that benefit the organisation, their customers, and employees. But the AI revolution is really a data revolution. Instilling trust in AI means instilling trust in the data that powers it.
This approach can be seen in the experience of pay.com.au, a leading B2B payment and rewards platform that allows business owners to earn points on payments where they traditionally wouldn’t. To efficiently scale and make it easy for customers to sign-up and make payments, the business turned to automated workflows and personalised marketing journeys built on trusted data, driving deeper insights. The result? They’ve been able to reduce the time to verify customers from days down to hours.
It goes beyond lead generation as well, with the pay.com.au data platform providing the business with an excellent foundation to provide customers with new ways to redeem points, offer redemptions, and more. This leads to a more personalised, and useful, rewards experience for their customers.
While this technology excels at optimizing processes and resolving simple cases, frontline employees are the real experts who engage with customers in uniquely human ways, building trusted relationships that AI could not on its own. The numbers back this up: 92% of service professionals say nurturing customer relationships is increasingly important.
Trust will become even more critical, requiring organisations to ground their AI on a foundation of trusted customer data, knowledge, and service policies.
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