By 2020, customer care will overtake product and price as the number one way for a business to differentiate itself. This is the age of the customer, and companies must progress to meet changing consumer expectations. In the words of famed economist Arthur F. Sheldon, “He profits most who serves best”. Half of consumers will take their business elsewhere within a day as a result of poor customer service.


Business Survey

Image Credit: Hong, Daniel, 2016 US Customer Engagement Index


Call centers house hundreds of thousands of agents at a cost of $4 to $12 per service request. The costs of keeping customers happy is skyrocketing. Even with small startups, one of the first ten hires is typically a customer service representative.

Business have long recognized the potential of automating simpler customer service queries. Recently, customer management software options, employing various levels of artificial intelligence (AI), have flooded the market. Automation and “virtual” employees allow businesses to scale up their services and revenue without a concurrent increase in costs.

Along with the rise of technology, customer preferences are evolving. 64% of consumers expect real-time responses at any time, and 65% say they are likely to switch brands if they receive inconsistent customer service across platforms (online, in-store, phone, text, email).  Customer tastes have also shifted from talk to text. Studies reveal that 64% of people, millennials in particular, prefer texting to talking.1 A TIME Mobility Poll in 2013 began analyzing this trend and found Americans ages 18-29 send and receive nearly 88 text messages per day vs. 17 phone calls. Additionally, the poll found 32% of all respondents would rather communicate by text, even with close friends and family.  

The move towards texting is not necessarily indicative of antisocial behavior. As “quiet media”, texting and messaging are less disruptive in public spaces. They are also regarded as “more private” because they do not require speaking aloud when providing sensitive information such PINs, passwords or account numbers.

Messaging can also be a richer medium than just voice. People add emojis, stickers, photos, animated GIFs, links to Web sites, and video to their messages. In this agile, API-rich environment, people can launch apps, initiate transactions and make payments inside messaging apps. The implications for customer care and digital commerce are profound.


Historical Trends In Customer Experience & Service

Customer service is in a period of flux and moving towards automation and self-serve. Initially, customer service departments were exclusively staffed by onshore representatives reachable by toll-free numbers. As costs in this model grew too high, call-centers moved offshore. When offshore models became less cost effective, automation was introduced. However, early attempts, such as IVR, were clunky and functionally limited, leading to increased frustration for consumers and limited cost savings for businesses.

Today, the technology for virtual assistants and automated self-serve customer service has arrived. The ultimate goal is fully AI-based autonomous intelligent assistants, but the current best practice is to pair an agent with a bot in a hybrid “cyborg” model. This partnership allows agent and AI to compensate for each other’s weaknesses and work as one team. More on this later in the report.


Customer Experience Service History


Traditional Customer Service Routing

Updating call routing strategies should be the first point of attack to improve customer experience. Delivering the customer to the right agent on the first try leads to greater satisfaction, more efficient transactions, and cost savings. The challenge lies in having a fixed set of resources (agents, time) faced with highly variable customer demands. Intelligent customer routing is an imperative. Six main intelligent routing strategies are available:

  1.  Customer retention routing: intelligent business systems can rank customers based on their risk of churn. Calls are then routed such that customers with the highest flight risk are assisted first and agents are given warning.
  1. Routing calls to the last agent spoken with: a common customer complaint is that they rarely speak to the same agent on sequential calls and must repeat the context. This problem can be addressed by routing callers to the last agent they spoke with.
  1. Best prospect routing: the best prospective customer is routed to the top agent for the best close rates. However, the business intelligence required to rank prospective customers is difficult.
  1. Cross-selling in the queue: while on hold, a customer is offered products or services they are likely to desire. The offerings can be customized based on previous customer data. This takes advantage of what would otherwise be down time to potentially increase profits and benefit the consumer.
  1. Multi-channel queuing: customers increasingly demand multi-channel access to representatives. Simply providing a toll-free number is no longer enough, businesses must be able to properly route calls, texts, and emails. Routing in this case is typically done based on the agents’ abilities on each platform.
  1. Routing outside the contact center: cases that require specialized knowledge should be routed to experts within the enterprise that are not call center staff. The concept can be further developed into “virtual” contact centers with calls routed throughout the business


Customer Pain Points

Customers report that inconsistency in experience across different channels and agents is the most frustrating problem with customer service. Other commonly reported complaints include conflicting experiences on different platforms, unacceptable complaint resolution times, minimal accessibility on social media, and unsatisfying experiences with support centers. The results of this survey, conducted by Gatepoint Research in 2016, lay bare the many aspects of customer service that could improve with increasing automation.


Customer Experience Automation:
Cut Costs & Grow Business With Machine Intelligence