Customer expectations have changed massively thanks to the internet. Instant gratification is simply expected as normal and it’s harder than ever for service to stand out. Meanwhile, significant growth in customer contact is also putting serious pressure on organisations to offer a prompt response.
It’s great that customers feel more connected to brands, but as we’ve come to expect instantaneous replies to queries, organisations are reaching their physical limits in terms of how much their human workforce can handle.
But when we talk about AI for customer service, we don’t just mean customer service bots replacing human agents. AI technology is also easing admin workloads – allowing representatives to focus on providing the human touch.
Here are four important ways AI is transforming how organisations communicate with their customers and manage increasing workloads.
Remember the last time you demanded to speak to a call handler’s supervisor? If only that escalated complaint could have been nipped in the bud early. That’s why AI is now helping organisations to deal with small issues early, before they become big ones.
If customers are provided with the means to contact a company with minimal effort, such as through a messenger window while they work instead of a phone call, they’re more likely to report minor concerns, rather than waiting until the problem can no longer be avoided. This can prevent issues from escalating beyond what’s necessary – improving brand satisfaction.
In turn, reducing the number of escalated complaints means human agents are under less pressure when it comes to getting to grips with more complicated cases. That’s good for brand satisfaction too: according to the Ombudsman Service, 75% of shoppers in the UK feel encouraged to make a repeat purchase if their complaint is well dealt with.
Customers spend a lot of time on their smartphones, communicating through messaging apps. So if this is how your customers prefer to communicate, why wouldn’t you give them this option?
Messaging means talking to your customers on their terms, through their choice of application. But the Harvard Business Review says the biggest benefit is the ability for a brand to immediately understand the customer’s query in context – helping to provide quick, no-nonsense responses.
More organisations than ever are now allowing their customers to contact them this way, to good effect – research by Aberdeen Group suggests that companies with a strong omnichannel presence have on average an 89% customer retention rate.
The challenge is handling the resulting increase in customer contact. Automation can help, but only for basic enquiries – and that’s where AI for customer service can help. By using intelligent deep learning capabilities, AI can make decisions on whether to reply to a customer automatically – giving an instant response – or transfer them to a human agent if the enquiry is more involved.
AI customer service bots – whether on a website or a messaging app – allow customers to address their own issues instantaneously – without putting unnecessary pressure on contact centre teams.
But it’s important that AI complements the human aspect of customer service.
A recent report from Accenture suggests that AI will dominate the way the big 3 banks in the UK interact with their customers – but it also notes that, even though customers are willing to embrace AI, they still want to be safe in the knowledge they can speak to a human.
And the great news is, bots are getting better at making that happen. Organisations gather more data from their customers, AI becomes more competent at diagnosing customer issues and offering first point resolution – allowing physical agents to optimise those human-to-human interactions.
Good predictions about customers’ likely behaviour are among the most prized assets an organisation can get its hands on – because it means you’re ready to respond.
Whether it’s being able to predict stock demand based on the weather, or identifying problems before they affect customers, AI has the ability to make real-time decisions on a scale we’ve never seen before.
Customer issues are generally not unique. And if one customer is contacting customer service with a problem, it’s safe to assume there are more to follow. But it’s this repetition of issue cases that helps AI to learn and understand the common – but sometimes complex – reasons why customers interact with a brand, and the solutions that go with them.
This is where AI deep learning comes into its own. By linking up data silos across the organisation, companies can pinpoint customer issues and resolve them quickly.
And this will only get better with time. As organisations accrue more data on customers, their predictive accuracy will increase.
There’s no doubt, great customer service still leaves a lasting impression – and AI has an increasing role to play in providing what your customers demand. That’s why we’re excited to introduce Service Cloud Einstein:
To discover more about how AI can revolutionise your customer interactions, download our e-book on AI for CRM.