The key to delivering the type of service customers want (and expect) these days is to leverage technology to offer more personalized experiences every time they engage with their favourite brands.
Why? Because customers will remember good brand experiences, and will certainly never forget the bad ones. The challenge for companies is to learn and continuously improve the customer experience.
Today’s customers have endless amounts of information at their fingertips at any given moment. More importantly, they know which brands are going out of their way to understand their needs and provide more individualized service. And many times, that factors into their buying decisions.
The “State of the Connected Customer” report by Salesforce Research revealed that nearly 69 per cent of consumers and 82 per cent of business buyers said personalized customer care influences their brand loyalty. Customers want to feel valued wherever they go, and they are willing to take their business elsewhere if they don’t.
We’ve entered the era of connected service, where customer experience is not only an indication of customer loyalty but a means of rising above the competition. Across industries and business units, it’s now imperative to clearly define, understand and optimize customer experiences. Intelligent customer service has never been more critical.
But how do you get there?
Years ago, it was about putting on a smile and holding true to the adage that “the customer is always right.” More recently, brands have focused on using technology to assure consistently positive experiences across most (or all) digital and physical channels. Moving forward, the emphasis will be on anticipating customer needs — often before customers even know they might want or need them.
Artificial intelligence (AI) will be the key technology making this possible, which is why many service centers are considering its capabilities for improving customer satisfaction.
Here are a few ways AI will improve customer service:
The ideal scenario for any customer service supervisor is not to wait for a customer to call about an issue, but to proactively reach out to them as soon as an issue is identified. While this sounds relatively straightforward, it’s actually more difficult to do in practice. The biggest challenge is monitoring and understanding data as it becomes available. Ideally, as customer information comes in there would be AI executing over the data constantly to detect potential patterns that could notify a supervisor so a proper escalation process and solution could take place. For example, say you purchase the same items from an online retailer each year. Your order arrives and you assume everything is correct, but a day later, you receive an email from a service rep saying you will be issued a credit because of a discrepancy they noticed with your order — one of the items was the model number. This error was caught before you were able to notice it. Though this is a simple case, it’s easy to see how this issue could come up in any business. Increasingly, the pinnacle of service is going to be proactive or even anticipatory. Leveraging data and past behaviors, service organizations will shift to proactively heading off issues before they happen. AI will help achieve this by making supervisors smarter and empowered to make more specific targeted recommendations to improve customer experience.
According to the second annual “State of Service” research report, top service teams are nearly 4 times more likely than underperformers to say this kind of predictive intelligence will have a transformational effect on their work by 2020. And customers seem to agree as the “State of the Connected Customer” revealed that 51 per cent of consumers and 75 per cent of business buyers predicted that, by 2020, brands will be able to anticipate and address their needs before they have to engage customer support.
Intelligent case resolution
Rather than replace human contact, as some fear it might, AI will actually make service agents smarter by drawing from earlier case resolutions and making recommendations. For instance, agents will be equipped with information on similar cases that were previously solved — including tagged information like knowledge articles and digital content. The agent can leverage the experience of others who have solved it before because the case resolution is smarter. Even in new cases that haven’t been resolved before, AI can also find information related to the case by looking at similar examples. AI-based case management makes routing and answering cases more efficient and effective — ultimately resulting in better customer service experience.
Intelligent field service
Here’s an all-too-common scenario: you wait at home most of the day for your cable technician to show up at your house to add service. You want voice-activated remote controls for TVs in three different rooms, but the technician says he can only install one. The problem? They need to put a new line into the house to enable voice activation in rooms without the main cable box — and the technician doesn’t have the gear to do that today.
So, you got back in the queue to wait for another appointment (as your annoyances grow each day).
AI would help overcome such annoyances in a couple of ways. First, it might have collected all necessary information about the job, reviewed location-based data to determine signal strength in the area and looked at whether voice-enabled lines were coming into the house. Then it could have digitally ordered all necessary equipment before the technician was even dispatched. That might also have included not only the gear needed to enable voice activation but, quite possibly, a signal booster if AI systems had discovered your reception wasn’t on par with nearby households. Once all the equipment was ready to go, then (and only then) would a service visit be scheduled. AI could have also helped reduce the time you had to wait around by reviewing the technician’s workload that day, considering historical data about how long it takes to complete each specific job and providing the rep with optimal routes between each appointment, considering recent traffic patterns. In the end, the technician could’ve shown up with a specific solution for your needs and you’d be up and running in no time.
Intelligent problem solving, customer interaction and technician visits are just three examples of how AI could transform customer service as soon as 2020 — this will be a big focus at our annual Salesforce World Tour in Toronto on April 20. No doubt, as the technology continues to evolve, we’ll see plenty more business-critical benefits emerging.
Start planning for this trend now. It’s the intelligent thing to do.
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