Imagine you run a busy hotel in the centre of Manchester. You’ve got rooms on several floors, so you rely on your elevators to carry hundreds of guests up and down every day. Recently the elevators have started to creak a little – but whatever the problem is, you’ve not noticed it yet.
Thankfully, your elevators are smart and connected, allowing the manufacturer, KONE, to monitor and predict abnormal behaviour and risks.
One afternoon, a technician turns up for a spot of unexpected maintenance. You discover their AI had sensed a serious abnormality in your equipment. Triggering a case in KONE’s customer service management software, the AI ensured a nearby technician had everything they needed to fix the problem before you noticed anything was wrong.
This is the future of service. Smart, connected, and proactive – or in this case, predictive. Because when you can service a customer before a potential issue becomes a real problem, everyone wins.
But what does it take to move from reactive to predictive service?
With the arrival of Industry 4.0 and advanced data science, businesses have powerful new tools to transform the customer experience. Powered by IoT, AI, and cloud computing, B2B companies that make physical products can proactively monitor and analyse their performance out in the field – and in turn, deliver a service that adds value throughout the product’s lifecycle.
In call centres, AI can analyse customer queries for common issues and help service agents take appropriate action in the field before other customers even notice they have the same problem. In fact, AI can automate the sharing of intelligence between any number of teams and departments. For example, imagine customers keep reporting the same problem with your latest banking software. Rather than leave the service team to fight the fire alone, your AI notifies Sales to stop selling the product, before triggering IT to work on a patch for existing customers.
In B2C and B2B alike, manufacturers like Hive and Kuka Robotics are using AI and the IoT to revolutionise the way they serve customers. At Kuka, they use Salesforce IoT Cloud and telematics data from their smart factory robots to identify and resolve pressure and torque issues before they impact productivity.
Over at Coca-Cola, their B2B teams use AI, IoT and the Salesforce platform to anticipate product faults in the field, support Sales to sell the right products to the right customers, and keep on top of that all-important first time fix-rate. Likewise, drinks bottler Coca-Cola Enterprises (CCE) uses Service Cloud to connect and accelerate service cases with complete business visibility, from the call centre agent to the service technician in the field.
But as great as a connected customer view is for improving a service team’s productivity, the real secret sauce comes from AI: the ability to detect, analyse and signal the location and cause of a fault – only to have it fixed before anyone notices something’s wrong. Of course, AI is only as smart as the data you feed it, which is why to get predictive service right, you’re going to need the following:
Whether it’s through sensors or built-in Wi-Fi, you need to be able to track data in real time across the entire supply chain. Once that data starts flowing in, you’ll need…
With intuitive automation and machine learning, your Customer Success Platform can track patterns, identify anomalies and learn from product behaviour to better inform and alert your service people for maximized ROI.
It’s all well and good to have that data back in the office, but to serve customers fast, your agents need to be able to access and act on those insights anytime, anywhere.
If you’re ready to make the move from reactive to proactive service, dive into our Service Cloud Trailhead and start learning how you too can apply the power of AI and automation. Or view a Service Cloud demo to see AI-driven customer service in action.