Until now, the omnichannel, cloud-based, 360-degree customer view-enabled contact center was mostly a pipe dream, touted by technology vendors and thought leaders, with a majority of businesses falling short of this gold standard. Most customers still expect to fight their way through a dead-end IVR, endure multiple transfers, and repeat their information to agents who have zero context on who they are or why they’re calling.
As technology grows more robust, however, more and more businesses are starting to overcome these bottlenecks, more of which are related to a lack of data transparency. Businesses are using AI and machine learning-enabled platforms to unify their data across the organization, route customers based not only on queues but context, and design self-service platforms that facilitate end-to-end support.
Treat Every Customer Touchpoint as a Potential Data Source
For many businesses, their website is the seat of personalization. By collecting data on customer’s viewing history and purchasing habits, they can provide personalized recommendations and proactive support based on context, such as offering help through web chat to a customer who’s having trouble completing an online purchase. But a truly omnichannel experience is one where personalization follows the customer, whether they’re on the phone with an agent, shopping online or visiting in-store.
This means that data you collect from your website must be reconciled with the customer’s activity in all other channels to build a complete 360-degree view of each individual customer. When an agent interacts with a customer, regardless of channel, they should be able to see the customer’s buying history, sentiment and previous interactions (across every channel), status of their orders and customer’s preferred channel.
Says Kustomer CEO Brad Birnbaum, “Imagine having a conversation with a friend but not being able to remember anything about that friend, or any interactions you’ve had with them previously. It would be difficult to have a truly personal or meaningful conversation. That’s how traditional retailers have historically interacted with their customers, with a large blind spot around customer preferences and history.”
Optimize Human to AI Interactions
“Agents for complex issues, AI for simple ones” is an oft-repeated principle for successful human-AI interactions in the contact center. However, customers still find themselves calling when a chatbot does not function as anticipated. For this reason and others, the contact center is often still considered a cost center rather than a revenue driver. Once businesses learn how to optimize their self-service channels, while giving customers recourse to contact a live agent if needed, agents will automatically become the go-to touchpoint for complex issues and expert recommendations, and thereby come to be perceived as subject matter experts.
Without the burden of responding to repetitive inquiries, agents can focus on building a relationship with the customer. As Birnbaum says, “It will become the customer service agent’s job to reflect the company’s mission and values, and act as a trusted partner. The changing expectations of consumers means that customers want to do business with companies they believe in, feeling as though they are a part of the brand. Customer service agents can help do just that, through both proactive and reactive support.
