From purchasing a product to resolving support issues, today’s consumers want instant gratification. For support organizations, that means making it as quick and easy as possible for customers to find answers and resolve issues — whether they’re calling your support line, or visiting your help portal. An increasing number of organizations are offering digital self-service options backed by artificial intelligence (AI) and automation, like chatbots and avatars, that allow customers to resolve support issues when they want, where they want.
What’s more, customers expect self-service options. In fact, recent data from Gartner on customer self-serve channels shows that 70 percent of customers use self-service channels. However, only 9 percent report that they get their issues resolved using those channels. For organizations that get it right, the payoff is worth it.
“Improving self-service is one of the best ways to increase customer engagement and boost agent productivity,” says Andrew Knobloch, Director Customer Success for Grazitti Interactive, SearchUnify’s parent company. “If you make it easier for customers to complete their tasks, satisfaction goes up and those customers are more likely to return. Self-service also frees up your agents to spend time with customers who need extra attention, rather than repeatedly answering lower-level questions.”
A key component of effective self-service is enterprise search. With search as your foundation, you can empower customers to solve their own issues faster. By providing customers with one place to access the most relevant information from multiple platforms, businesses can increase case deflection, reduce support costs and improve the customer experience.
Related Article: How AI Is Powering the Next Generation of Support Agents
Essential Elements of Self-Service Support
Below are four essential elements that every customer support organization should incorporate into their self-service offerings to save customers time and keep them satisfied.
1. Be Proactive
One way to provide excellent self-service is to anticipate what customers need before they come to you with a support issue. This means understanding what users are searching for in your community, for example, in order to predict incoming cases and ensure you have the right articles in your knowledge base to address them.
Imagine a customer visits your support community, types in a question, and comes up with zero results. Not only will that drive them to more expensive support options, like a call to your support agents, but they also may share that bad experience with their friends, putting your company in a negative light.
You can stop this before it happens by taking simple actions, such as eliminating the number of searches with no results or clicks. The problem is, only 35 percent of companies have any kind of process to identify knowledge gaps, according to Technology Services Industry Association (Source). A cognitive search engine can help you find out where you have gaps in your help articles based on analytics, and then assist agents in creating relevant articles to fill those gaps with just one click. So, next time customers search for answers, they’ll always find what they’re looking for.
2. Personalize Throughout the Customer Journey
Customers expect personalization, not only as they’re considering your product but also as they move along in their journey with you — including, and perhaps especially, when they need support. But with so many support inquiries to handle, your agents can’t possibly provide personalized attention to each person who needs help.
A cognitive search engine powered by AI and machine learning (ML) can change how the game is played. Let’s say two people — Carl and Joanna — have visited your help portal. Carl needs help transferring photos from his digital camera to his cloud account, and Joanna wants to know how to access photos she’s taken with her smart phone on her desktop. Both type in “transfer photos.”
To surface the best answer for each customer, machine learning goes to work, analyzing each customer’s preferences, behaviors, roles, past searches and sentiments. Algorithms also assess the progress of each piece of content in the knowledge base in order to display the most relevant recommendations for each customer — at the top of the list, saving clicks and preventing escalations.
For Carl, it’s articles about how to transfer photos from his specific model of digital camera to his particular cloud service. For Joanna, it’s a video showing her how to transfer photos from her smart phone model to the type of desktop she owns. By populating search results based on user context, you can increase engagement by giving customers exactly what they need, while freeing up your support agents to help other customers with more complex issues.
3. Keep It Effortless
Help customers find the information they need faster — at any time of the day or night — with the help of AI-powered chatbots or virtual agents. Chatbots make use of natural language understanding (NLU) to understand the context of user questions, so you can go beyond simple keyword matching to deliver the most relevant information.
And because chatbots learn with every interaction, not only do answers get even more pertinent over time, but they can deliver more personalized experiences, as well. Here’s an example: Let’s say a customer asks your chatbot for help installing an update for their software. Rather than asking the customer for additional information, the chatbot can access data from past interactions to provide the customer with the download link for their particular software update.
Best of all, because search-powered chatbots can access information from knowledge bases, blogs, FAQs, discussion boards and other sources, customers don’t have to go anywhere else to find what they need. And if the customer needs further assistance, the chatbot can easily connect them with a live agent.
4. Make It Seamless
When customers need support, they don’t want to bounce between multiple sites and portals to find answers. One question and one click should display the most relevant results at the top of the list, no matter where that content is stored within your enterprise.
A cognitive search engine not only indexes content from disparate sources across the enterprise but also makes sense of this unstructured data for content classification. This allows the system to power smarter faceting which helps elevate the user experience by making knowledge discovery easier.
An intelligent search engine can interpret relevant facets from the search query and the intent of the user. Automatic faceting analyzes user behavior and search history over time to pre-select the most relevant facets for your users. This ensures the seamless discovery of your content and guides users to relevant results faster. On top of that, search analytics give you insights into the usage of these facets to help you understand what type of content is being used by them more frequently.
Why Intelligent Self-Service Is the Only Choice
An intelligent self-service portal makes use of AI, machine learning and advanced cognitive search to better understand where your customers have been, what they need today, and what they might need tomorrow.
One of the biggest benefits this brings to your organization is enhanced case deflection. While there are many approaches to measure and boost case deflection, it’s important to find the methods that are most appropriate for your implementation, and have the most impact on customer satisfaction. A few things to consider include ensuring customers can access recommendations in the most efficient way, personalizing the information on your support pages based on case history and profile information, and understanding how your content is performing so you can surface the most relevant results.
“I’ve come across support communities where there’s a tendency to minimize the visibility of the ‘create case’ or ‘contact support’ button. You really don’t want to mess up the experience of the end user or make them feel that support is really not reachable. Make sure there’s a balance in your strategy for case deflection and your customer satisfaction (CSAT),” says Vishal Sharma, CTO, for SearchUnify.
When customers can solve their own problems, organizations can also reduce staffing expenses, increase agent retention, and reduce customer expansion costs. Organizations can also see an impact on revenue by allowing customers to log into their accounts to renew subscriptions or purchase upgrades.
“If properly implemented, enabling customers to automatically renew their service contracts as well as browse a catalog of services to purchase and complete the purchase online can reduce the manual involvement of sales and renewal teams, streamlining the purchase of additional products and services,” writes TSIA.
Great Self-Service Starts with AI
The key to improving the customer experience is to provide customers with the answers they need in the moment they need them. With the help of AI and cognitive search, you can deliver these personalized experiences to every customer, while taking the burden off your support teams. For example, the way content performs in your self-service community affects content ranking seen by agents in your CRM. On the other hand, the content that agents use to resolve cases gets pushed to the top of search results in your customer community. This closes the loop between self-service and support, enabling you to provide the frictionless experiences your customers are looking for.
SearchUnify is a cognitive search platform that revolutionizes information discovery, fuels an insight engine, and provides a robust platform for AI-based apps like customer-facing and agent-assist chatbots. Its parent company, Grazitti Interactive, is a digital innovation leader with extensive experience in developing solutions that unlock data insights, increase operational efficiency and drive customer success.