In a recent NiCE CXone Webinar, we examined how new consumer expectations and behaviors create a high-stakes challenge for businesses, and how to make self-help the best help with new ways of engaging customers across any channel of their choice. The topic was such a success that we received more than 70 questions during the live session! In the spirit of building helpful self-help, we’ve created a blog for you with some quick tips from our webinar session, along with a special Q&A section that covers many of the great questions we received during our webinar session.Read on to explore the following:
Webinar recap: How to make self-help the best help
Post-webinar Q&A: Your questions, our responses
Webinar recap: How to make self-help the best help
Did you know that according to Accenture, 73% of consumers prefer to visit your website before contacting customer service, and a full 68% prefer self-service channels for simple tasks?[i] Just as critically, PWC reports that one-third of customers will walk away after one bad experience.[ii] But do you know how many customers walked away from your business without ever contacting customer service?In the past, self-help was prioritized by contact centers as a way to reduce costs by reducing contact volumes, handle times, and automating more repetitive customer tasks. These are still valid KPIs, but what has changed is that consumers now have a vast number of ways they can communicate digitally, and they now expect—and demand—self-help options on the channels they use on a daily basis.This presents a great opportunity for businesses, because not only is self-service economical, customers have come to prefer it. In fact, a CXone benchmark study found that 8 in 10 customers are more willing to do business with companies that offer self-service options.[iii]Given this newfound expectation and willingness to self-serve, businesses should respond by shifting resources and budget toward successful self-service journeys. Consider the stark reality of the average cost of helping a customer across the various channels available to them, as reported by Contact Babel: $7.46 for a phone call and $6.95 for a webchat—but only 40-60 cents for IVR self-service, and a mere 5-15 cents to self-serve on the web.[iv] That amounts to a possible $731,000 saved per 100,000 self-service interactions!But be careful not to fool yourself into thinking this is a simple fix. There is another stark reality: According to the CXone benchmark, 50% of consumers who try to self-serve end up interacting with a contact center agent anyway, and 90% of consumers think chatbots and virtual agents need to get smarter before they will regularly use them.[v] We’ve all been there—you ask a chatbot a question, and it either returns a completely inane response or asks you to repeat yourself before finally telling you it can’t help. That terrible experience just creates more friction for your customers and can lead to erosion of brand loyalty and even customer churn.A Harvard Business Review article reports that “fully 81% of all customers attempt to take care of matters themselves before reaching out to a live representative.”[vi] This number is growing year over year—so what should you do to provide successful self-help experiences for your customers? Consider this checklist for achieving successful, customer-first self-service:
Enable customers to search for and access information they need in channels and locations where they prefer, at all hours and days of the week before an interaction becomes necessary
Pull from a single source of truth where knowledge is always up to date and written in the language customers use
Understand where the customer is coming from and offer recommendations for where they’ll need to go next
Provide value by linking contextually related content and stating why the suggested answer is the best fit
Personalize experiences to show only the most relevant content by using conditional content and dynamic permissions
Identify when self-service isn’t the best option and proactively suggest the ideal path to a resolution
Optimize mobile-responsive knowledge content so customers can find what they need when searching your website or using search engines
Post-webinar Q&A: Your top 5 questions on self-help, answered.
The best webinars are the ones with lots of questions—and we’re so glad to hear from you! Though we can’t address all 70+ questions received during our live webinar, we identified the top five questions that cover most of your curiosities:
How do you ensure customers get an agent before they hit maximum frustration when the AI doesn’t help?
The advantage of bots trained with AI is that they can detect complexity and use a decision model if properly trained to do so. The AI is trained to handle complex issues, but it can also be trained to recognize when it can’t answer. Take, for example, an AI bot trying to help a customer with a bank charge for an unauthorized transaction. There are two issues here: The charge from the bank and the fact that it wasn’t authorized. The AI can conclude that the bank charge was due to an overdrawn account, but the reasoning engine can detect that there are two issues and it only solved one. It can also detect that “unauthorized” is a topic that needs to be escalated immediately. In a matter of seconds, the AI bot answers the customers with the reason behind the bank charge and escalates directly to an agent in the fraud department to further help the customer freeze her account and figure out the source of the unauthorized charge.
If relationship building is a big part of how the company does business, how can you still accomplish this if they self-serve with a chatbot?
The best way to a customer’s heart is understanding—for chatbots, that means personalization, context, and built-in traits. Your bot should exhibit behaviors we all respond to positively: Friendliness, acknowledgment of who we are or the situation we are trying to solve, and taking ownership to try to resolve the customer need quickly. Don’t forget that first impressions are everything. When a customer engages with your bot, it should already know something about their situation. Are they on a specific web page trying to find specific information; are they loyal subscribers of more than three years; can the bot mention something about the current situation—such as the holiday season? Even if the bot knows nothing upon first engagement, it can be “friendly” and engage the customer with a kindly-worded message such as, “I would be glad to assist you as best I can today, but if I am unable to help, I will connect you with a live agent.” Bots are not just machines—they are built and trained by humans, even if they are using AI. The source of all the data bots use is human-based. They are perfectly capable of infusing human traits into their functionality, and our humanness can’t help but respond well to that.
How many different scenarios can realistically be coded into a chatbot? How do you make that decision?
It’s statistically impossible for a person—or even a team of bot builders—to code every scenario into a bot. This is why newer bot solutions are starting to adopt AI technology, because the AI continuously learns scenarios based on patterns in interactions data, making it possible for it to “learn” scenarios without being specifically coded to do so. It also makes it possible for the bot to reason when it hits a scenario it doesn’t understand, and when this happens, to immediately escalate to a live agent.
What is your strategy for winning back dissatisfied customers?
The bottom line is proactive outreach. There are many ways to handle this, however. If customers are dissatisfied while interacting on chat or a call with agents, real-time interaction guidance can help agents work toward a positive outcome at the moment. But they may not be successful every time, so consider using a post-transaction survey system that uses AI to engage customers on their preferred channel of communication with contextual questions regarding their transaction. If they indicate dissatisfaction, the AI can escalate the customer to a remediation queue for a call back by a manager or agent trained to solve escalations. Interaction analytics and quality management with AI that automatically detects low-sentiment interactions or complaints are extremely helpful for several reasons. First, those complaints and low-sentiment interactions can be sent through an escalation queue for fast review and remediation, making it possible for a remediation team to reach back out to the dissatisfied customer and try to resolve the issue. Second, the root causes behind the low sentiment and complaints can be identified and corrected, whether it be a product defect, process problem, or even an agent behavioral issue. This makes coaching more personalized and effective for each agent and works to keep negative sentiment and complaints to a minimum.To learn more about how you can implement real-time, CSAT-amplifying strategies, check out Aberdeen’s report: The ROI of Real-Time Agent Guidance.
How can you keep current staff engaged so they don’t leave?
It may sound counterintuitive, but adopting solutions that are built on native AI is the best way to keep your staff engaged and reduce your turnover. AI is not taking over jobs, it’s enhancing them: By helping agents with contextual information about a customer for a better experience on both sides of the conversation; by delivering relevant knowledge base articles so they aren’t left searching for what they need; by gently reminding them at the moment to follow compliance procedures; by objectively measuring their soft-skill behavior performance so they feel a part of the solution and not unfairly judged. Further, AI that assists customers with self-service provides a richer job environment for agents because they are left to solve harder and more interesting and engaging issues. These are just a few examples of how AI is helping to up-skill agents so that they feel more challenged and more satisfied with their own day-to-day performance—and all these methods of engagement work across remote or hybrid office environments.If you’re looking to get self-service, AI implementation, and all-things digital right in 2022, CXone has compiled everything you need to know.
We enlisted industry-leading experts from Forrester, Aberdeen, and more for a one-of-its-kind Digital CX Week series to introduce emerging trends and opportunities for digital-driven contact center solutions. The strategy for 2022 is all about leveraging digital-first CX solutions to meet customer expectations and drive satisfaction higher.In this webinar series, learn key components of a CX-driven, omnidigital strategy:
Learn to anticipate customer needs and deliver instant results and satisfaction
How to leverage smarter self-service to keep up with customer needs
The top 5 forecasted customer trends defining 2022
How AI and automation capture micro-moments and fulfill customer demands
Customers expect instant gratification—learn how you can deliver
Make the smartest buying decision with the latest Gartner analysis
NiCE has been named a Gartner® Magic Quadrant™ Leader for Contact Center as a Service for the 10th consecutive year and is positioned furthest on Completeness of Vision.
Make the smartest buying decision with the latest Gartner analysis
NiCE has been named a Gartner® Magic Quadrant™ Leader for Contact Center as a Service for the 10th consecutive year and is positioned furthest on Completeness of Vision.
In the past, self-help was prioritized by contact centers as a way to reduce costs by reducing contact volumes, handle times, and automating more repetitive customer tasks. These are still valid KPIs, but what has changed is that consumers now have a vast number of ways they can communicate digitally, and they now expect—and demand—self-help options on the channels they use on a daily basis.This presents a great opportunity for businesses, because not only is self-service economical, customers have come to prefer it. In fact, a CXone benchmark study found that 8 in 10 customers are more willing to do business with companies that offer self-service options.[iii]
