Demand for self-service is soaring. Consumers expect more than ever, beginning with the 24/7, always-available convenience of finding solutions to their problems themselves. Though most businesses now offer at least one self-service app,
a Gartner survey found that just one in 10 customers report resolving their issue using self-service entirely.
When self-service can’t answer questions, customers inevitably seek out live interactions, creating a two-fold challenge for contact centers—higher customer frustration and increased costs. Live interactions, through voice and chat, are exponentially more expensive than self-service channels.
Gartner estimates live channels cost an average of $8.01 per contact versus just $0.10 per contact for self-service channels, including company websites and chatbots.
Self-service, when done right, reduces costs and improves customers’ experiences. In fact, Abderdeen research found that consumers who resolve issues in self-service report higher levels of customer satisfaction, which positively impacts the brand. What’s more, they statistically make more complete payments, more frequently,
according to McKinsey.
As a result, a growing number of organizations are prioritizing improvements to their self-service capabilities. Most (71%, according to a
survey by NiCE) agree that self-service channels, including chatbots and virtual assistants, simplify customer interactions. Still,
nine in 10 of them say chatbots and virtual assistants need to get smarter before customers are willing to use them regularly.
Building Smarter Self-ServiceSelf-service budgets are significant and growing. Verified Market Research® estimates
$6B in global spend with 19% annual growth from 2021 to 2028. Self-service development today, however, is ineffective, but it doesn’t have to be. Now, Enlighten XO makes it easy to evolve from reactive guesswork into a data-driven strategy by solving two key challenges:
- Challenge 1: Understanding expansive data sets
Self-service apps are ripe for optimization, but they need expansive data sets for training and tuning, something that’s difficult to manufacture at scale.
For example, could a human…
- Review every interaction to categorize every customer intent?
- Identify the root cause of each interaction?
- Track and follow each task and every conversational turn?
- Find every agent activity required to resolve each customer intent?
Add in millions of interactions across dozens of channels - that’s a tall order – perhaps impossible. Instead of relying on manual processes, Enlighten XO transforms self-service with an AI-powered data-driven strategy. AI and machine learning automatically and continuously identify customer needs while prioritizing self-service opportunities for the most significant business impact.
Enlighten XO takes the tasks that were impossible in manual work and does them continuously, consistently, and automatically across every interaction on every channel.
- Challenge 2: Harnessing the most valuable data to improve self-service
Live agent conversations contain an untapped wealth of data – with valuable insight into improving digital channels. From live conversations, businesses gain insight into the customers’ intents, each conversational turn, the agents’ responses, and their activities to resolve the customer’s question. Until now – this valuable, live conversation data was not a part of developing self-service applications. Enlighten XO seamlessly includes live conversational data, the most beneficial and most complete source of insights for self-service to improve digital channels.
Prioritizing self-service improvement is the first step in meeting the evolving needs of today’s digital-first consumers. When customers are unable to solve their issues without moving to an agent-assisted channel, CX suffers.
“
For businesses, the key to understanding the digital transformation of consumer life is realizing that consumers do not just want to interact with you via digital channels; most of the time, they don’t want to interact with you at all. They want a fully self-serve digital experience.” - Sheila Monroe,
ForbesNiCE introduces the key to smarter self-service:
Enlighten XO. By continuously learning from agent-assisted interactions, Enlighten XO transforms self-service development with a data-driven approach, leveraging AI and analytics to improve experiences with every interaction. Enlighten XO is the only solution that gathers insights from live agent interactions to improve self-service experiences and improves self-service containment.
With Enlighten XO, organizations are building smarter self-service
faster by:- Identifying the best self-service opportunities from employee-assisted interactions and discovering thousands of training phrases
- Creating a detailed conversational flow that models ideal resolution paths for every identified intent
- Prioritizing the most automatable opportunities for ROI, making it clear where to invest time and effort to improve customer experience.
Faster, better, smarter self-service, powered by Enlighten XO, results in:
- Improvements to first contact resolution by replacing guesswork with precise insights, and actionable next steps
- Increased automation that resolves more complex customer intents using specific training phrases and ideal resolution paths for every intent
- Higher customer satisfaction by driving greater engagement driven from smarter digital channels
The pandemic accelerated customers’ preferences for self-service. When it comes to checking a balance, paying a bill, or resolving another support need, consumers expect to solve their problems independently—no customer service rep required.
The standard for self-service experience is rapidly increasing. With every interaction across every brand, your customers gain more self-service experiences that consistently give them higher expectations. Are your digital channels ready to set the bar higher, or will you fall short of expectations? Enlighten XO helps organizations become more digitally fluent in delivering smarter self-service for the digital-first experience generation.
