We know that customers use an increasingly broad spectrum of communication channels to interact with companies, moving seamlessly between them dependent on their context and preferences. They also use several channels simultaneously if it makes sense to do so.
And we know that customers use self-service as a first point of contact with companies, and if self-service fails, typically only then will customers pick up the phone and call. If customers are offered lower-friction channels like chat or messaging, they will increasingly prefer to use those. It's because these channels don't carry the overhead of a phone call and allow them to quickly connect to agents.
We also know that customers are using visual engagement, like cobrowse, video, or screensharing, as it allows them to quickly cut through conversation clutter and be easily understood. These modalities help establish customer intimacy and trust during high-value purchases, like mortgages or an insurance policies.
What does this mean for customer service organizations? They are drowning in inquiries as their customers contact them at an increased rate and over an ever-increasing number of channels, compared to historical contact volumes. And customer service organizations are reacting by adding staff year over year, despite the cost. But this strategy is not sustainable. They must rework their operations, leveraging self-service and automation whenever and wherever possible. To do this, they must do the following:
- Shore up the foundations of self-service. They must use modern knowledge solutions that can discern intent and optimize content retrieval by learning from prior searches. They must couple community content to enhance self-service. Question-and-answer community threads create a massive volume of content that customer service, product, and marketing teams cannot hope to match internally.
- Add conversational interfaces to static self-service content. Customer service organizations must explore chatbots to add conversational interfaces to static self-service content, which results in greater overall self-service success rates.
- Meet customers where they are. As intelligent assistants like Google’s Assistant and Amazon Alexa continue to penetrate households and become local hubs of consumer experiences, contact centers should explore moving customer service away from their walled garden with authentication and security considerations front and center. For example, today, Capital One allows customers to pay their bills by asking Alexa to do so. Similarly, explore supporting customers via common messaging platforms and applying the same service-level agreement management discipline for these channels as used for chat.
- Digitize existing processes. Customer service organizations must work with other parts of the company to tag digital properties, like websites and mobile apps, to track customer behavior. They must collectively use CX techniques like journey mapping to understand current pain points, drop-offs, and disconnects. They must review existing end-to-end processes from customers' standpoints and determine where best to digitize to improve productivity and the quality of service.
- Leverage process guidance. Customer service organizations must leverage vendor-defined best-practice process flows and extend these process flows in ways that uniquely differentiate their offerings. These process flows lead agents through steps that map to user interface (UI) screens. Agent screens contain the scripts, content, and back-end data that are relevant to each step of the process so they can effectively and efficiently resolve customer issues.
- Add robotic process automation (RPA): RPA software performs routine business processes and makes simple decisions by mimicking the way agents interact with applications through a user interface. Organizations can automate entire end-to-end processes, such as account onboarding or insurance claims awards, with humans typically only managing exceptions.
- Explore agent-facing intelligence. Agent-side virtual assistants shadow agent, and learn from their interactions, to the point where they can recommend next-best steps to take or content for an agent to use in an interaction, or at times take over the entire conversation. They are fairly simple but quickly evolving to provide real value.
- Infuse AI into processes. AI can uplevel contact center operations. AI streamlines inquiry capture, routing, and resolution. AI extracts useful information from voice and digital conversations, images, and machine-to-machine communications to quickly surface trends in issues and customer sentiment that could affect customer retention and loyalty. AI schedules maintenance appointments, pushes fixes to connected devices, and makes field operations more efficient by restocking parts based on needs or intelligently optimizing field resources to provide on-demand service.
Customer service organizations with established processes and technologies cannot explore each of these transformation steps sequentially. Instead, they must put the customer and their journey at the center of each project and modernize each journey with a combination of these approaches.
Kate Leggett is a vice president and principal analyst at Forrester Research.