In the News: Any Place, Any Time, Any Channel

“The sell it and forget it kind of relationship with customers just doesn’t add to a full brand experience,” says Art Schoeller, Vice President and Principal Analyst at Forrester Research. “We want to drive enrichment, we want to drive retention, and we want to drive loyalty.”

Companies like Airbnb, Amazon, and Lyft have trained consumers to expect seamless, reliable service experiences with omni-channel support communications. Those positive experiences “aren’t just a feel-good kind of thing,” Scholar says. They have a material impact on lifetime customer value.

Whether it’s issuing recalls, scheduling service visits, or handling payment or leasing and purchase inquiries, customers are increasingly using many different communication platforms to interact with their chosen brands. That can include chat, email, phone, social media, text, even video chatting.

Automakers and dealerships are increasingly looking to anticipate customer needs throughout the ownership lifecycle and have solutions ready to respond to them with the right message at the right time on the customer’s preferred communication channel.

Ford redesigned how its large contact centers operate in 2019 as part of a plan for improving customer loyalty. “When experiences are good, we’re rewarded with higher loyalty,” Elena Ford, the automaker’s chief customer experience officer said at the time. That means more service visits, more purchases, and happier customers.

Auto Retailers are also automating conversational lead capture and nurturing as well as supporting outbound business development center efforts.

The mechanics of customer service and contact centers are changing, says Schoeller, and at the heart of that change is cloud technology. Cloud contact center solutions aren’t new, but the more powerful the machine learning and the bigger the IT infrastructure, the more effective they become. “Artificial intelligence is not just for chat bots or reducing costs, though it can do those things,” he says. “AI cuts across many areas of customer support.”

Robotic process automation can help assist agents. Prescriptive AI can help route customer concerns expediently. Machine learning algorithms can decipher trends within calls and even intake data from devices, and they can put that information onto live agents’ screens. That leads to quicker and more accurate resolutions of customer concerns.

“The technology that’s at the core of having a contact center as a service is the routing, the filtering, and the matching of the right agent with the right customer at the right time,” Schoeller says. “It also informs the agent’s workspace itself. What’s presented on the agent’s desktop has to be useful and relevant.”

Cloud technology, he says, empowers agents to be researchers and problem solvers rather than people who look something up that could be found elsewhere via self-service.

Recently Amazon Web Services (AWS), CRM provider Salesforce and IT consultancy Slalom teamed up to create a call center for an electric car startup. Functionally the team was able to deliver chat, email-to-case, knowledge base, and telephony (including personally identifiable information redaction) in a relatively short amount of time while integrating with many other systems.

Cloud-based contact center solutions make it easier to integrate customer service with other systems such as account management, customer profile data platforms, metadata and order management, and retail platforms.

Cloud systems like this also make it much easier to communicate with customers across different channels, Schoeller says. Email and the phone may be the most popular, but customers are used to being able to make contact through SMS, social media, even through video chat. It can be hard to integrate lots of different platforms into a single tool, but ignoring those channels isn’t wise.

“When I talk to Forrester customers who say they want to force customers onto their website so they can reduce live calls, that’s a red flag,” Schoeller says. “Customers will go where they go. Brands that really want retention, enrichment, and loyalty need to meet customers on their channel of choice.”

Few companies handle as many support requests as Amazon, and in 2007 the company began engineering ways to improve its contact centers. Demand is seasonal, says AWS’ Director of Productivity Applications Scott Brown, but up to 70,000 customer service agents may be providing support to Amazon’s customers on any given day.

“We wanted to build a platform that could make the customer experience frictionless,” says Brown. “But when we looked at customer service centers around the world, we faced many challenges: cumbersome tool sets, difficulty integrating with CRM platforms, hardware and telephony problems, and security and scalability.”

To create a single system, AWS leveraged its cloud computing technology to create an omni-channel cloud based contact center software package, eventually called “Amazon Connect.” It features skills-based contact routing, voice and chat recording which is later analyzed through machine learning, and a comprehensive analytics suite.

“We decided to put this service on the market because many of our customers were experiencing the same challenges we had when we were evaluating our own customer support needs,” Brown says. AWS began offering the system to customers in mid-2017.

Because Amazon’s global teams need to be self-sufficient, the system was as well. For external customers that means they can easily interface with it to quickly update Interactive Voice Response setups and contact flows.

Amazon Connect isn’t dependent on any local hardware. That makes it possible to easily onboard new agents in an industry known for churn, and makes it easier for agents to work from anywhere – a major advantage since the onset of COVID-19. “That’s part of our mission,” Brown says, “Creating experiences where employees can be safe and still continue to be productive and impactful.”

Cloud technology makes adding custom functions easier than making multiple vendors work together.

The system’s costs aren’t based on the number of agents or any specific sales plans, Brown says. “Like all AWS services, it’s a consumption model. The time that you’re actually using the service and helping your customers? That’s all you pay for.”

To get a sense of what kinds of gains in both efficiency and customer satisfaction were possible with this technology, Forrester Research conducted an extensive survey of customers who converted their contact center technology to Amazon Connect in 2019 and early 2020.

Forrester surveyed six large companies across different regions – two in Asia, two in North American, and two that are global. The number of customer service agents at the firms ranged from 300 up to 20,000, says Benjamin Brown, a senior consultant at Forrester and principal author of the study.

Using data gathered from these companies, Forrester created a composite organization that handled about 6 million calls a year with an average call duration of about 7 minutes.

Forrester modeled for significant seasonal changes in call volume. In slow months, this amalgam organization would need 540 agents, but during peak times, it needed 950. In older call center models that might mean paying for 950 licenses for months at a time when only a fraction of them were being used.

Forrester’s research found three areas of savings – the first was reduced technology costs.

According to the data, the hypothetical company saw a 31 percent reduction in annual contact center fees, reducing its cost per user, per month, from $187 to $129. “That’s just technology costs going down. The consumption-based model helps the cost scale with the seasonality of the business,” Brown says. “That’s especially important now with call volumes changing so much because of the pandemic.”

“We heard significant savings across the board [from our survey participants],” Brown says, “with one of them stating that they’d seen a 2.5M reduction every year from their IT budget.”

The second area was a cascading improvement in how calls were handled and the time and money it saved.

Being able to more quickly update IVR setups enabled more customers to find what they were looking for without having to talk to an agent. With self-service options easier to use, agents handled 24 percent fewer calls.

Because calls are recorded and transcribed, AI machine learning helped identify the intent of the calls, which meant they could be more quickly routed to a proper specialist. That reduced the average handle time of the calls by 3 to 15 percent. One of the customers that contributed data to Forrester’s study saw a 15 percent reduction in workforce as a result of those kinds of changes.

Those changes cascade upwards. With fewer calls and a streamlined workforce, managers could, in Forrester’s estimation, free up 4-8 hours of work time per week. Systems administrators saved 40 hours per month in labor. With the cloud replacing operational tasks like managing licenses and hardware, system administrators can concentrate on being engineering teams and building value, rather than maintaining operational pieces.

The monetary savings or gains from streamlining operations or reducing labor are only half the story, says Brown. “We make our investments to provide a better experience,” he adds, noting that in Forrester’s research, “Customers had shorter wait times. They were able to get routed to the right person at the right time. They were able to address issues via self-help.”

Because quick edits could be made to the contact flows and IVR setup, Brown says, it was easier to head off a wave of calls before it happened. “If a company had a service outage, it was easy to change their IVR messaging so customers didn’t flood the contact center.”

“Companies can deflect calls that way and yes, that helps save money,” Brown says, “But more importantly it helps those customers have a better experience.” In Forrester’s research, those better experiences reduced customer churn and refunds or remunerations for transactions gone awry.

“They can also use the AI analysis of their calls to spot problems outside the contact center system,” Brown says. If the AI notices that many customers are calling about a pricing error on a particular web page, it can be traced and fixed at the source by such analysis.

All that, Brown says, leads to more positive customer experiences, though the customers will never see all the back-end work that makes their self-service options functional and routes their calls to the right person at the right time. It’s seamless, and that’s the way it should be.

To learn more about Amazon Connect, click here.