Der nächste große Anwendungsfall für KI-basierte Suche: Kundensupport

Als sich unser Alltag im Jahr 2020 vollständig in die digitale Welt verlagerte, wurden Unternehmen im Internet mit einer regelrechten Flut von

By Yext

Juni 11, 2021

5 min

When the world went digital-only in 2020, businesses faced a deluge of questions online.

From queries about COVID-19 protocols to how to handle no-contact returns, website visits from consumers seeking information about businesses increased by as much as 376% in some industries throughout the pandemic spring — rising in tandem with line-clogging customer support calls. (Raise your hand if you heard, "Please hold, your call is very important to us…" in the past year.) To handle the crisis, many businesses rushed to rethink their customer support operations. Did they need to hire more agents? Update their FAQs?

Great questions. But one year later, even as businesses reopen and we inch closer to "normal," we're (largely) dealing with the same old approach to customer support that, quite frankly, still can't solve every issue.

The two primary options? On the one hand, investing in a team of agents. This can give the benefit of seeming "high-touch," but "high-touch" can also mean high cost: according to Harvard Business Review, the average cost of a live support interaction (phone, email, chat, etc.) for a B2B company is a whopping $13. On the other hand, providing scaled support — service via an automated phone system, chatbots, FAQs, etc. — is much more cost effective. But the problem is execution: according to Gartner, 70% of a business's customers use these self-service tools, but only 9% end up fully resolving their issues.

To make matters worse, Forbes reports that poor customer support is costing businesses $75 billion a year — serious money that no company wants to waste.

So, the $75 billion-dollar question is: how can businesses reimagine their help sites to actually scale their service model — without compromising quality of support?

The self-service future?

Those stats are a little doom-and-gloom, but there is some good news for businesses: Dimension Data says that 73% of customers prefer to use a company's website for support. And according to Parature, 84% of customers want to resolve their own issue using search, before raising a support ticket or calling customer service. So, people actively want to solve their own problems; it's just that they (mostly) can't with the self-service solutions that exist online today.

Why? Well, it's tricky for businesses to answer customer service questions online. Yext research shows that a business may have to field 1000+ unique, complex queries related to support alone — which means FAQs just won't cut it. And at the same time, support queries have been on the rise.

But there is a better way: search. Search can help deliver answers to customers without requiring more costly phone calls or manually sorting through 1,000 page long FAQ lists. But here's the key: it has to be the right kind of search.

Enter AI-powered search for support — which can help serve your customers and empower your agents. Here's how.

Turning your website into a support hero

Let's back up for a minute.

Search on a business website isn't a new thing: millions of businesses have been using keyword search to "power" their websites for the past 20 years. The problem is… the technology behind keyword search hasn't evolved since 1999. So, when customers seeking assistance type a question into a search box, they get back a list of hyperlinks that contain the keyword, but lack the context. In other words, the search bars on most business websites don't know what people's questions really mean.

But consumer search engines are a different story. Over the last 20 years, Google has led the charge on making consumer search more robust. Instead of only using a single algorithm to scan for keywords and return blue links which may or may not be relevant, Google has incorporated natural language processing (NLP) to understand questions and intent to deliver actual answers.

So the key is to ensure that the search powering your business' help site is truly modern, based in AI, and thus designed to enhance the customer experience by understanding and answering important user questions. Features like NLP and extractive QA (an algorithm that allows your website to deliver featured snippets of information from long-form and unstructured data like product manuals, tutorials, or ebooks) ensure the rich content about your business is accessible, so that your customers to actually self-serve when they have an issue – no combing through blue links or endless FAQ pages necessary.

This benefit applies to your own support agents as well. Beyond affecting the bottom line, having information spread across systems affects productivity — according to IDC, 36% of a typical knowledge worker's day is spent looking for and consolidating information. If agents are equipped with AI search, they can deliver the most helpful information more quickly, providing a better experience for both themselves and the customers they're serving.

As a last line of defense, this modern search experience can also be embedded as a customer fills out a support ticket. In real time, AI-powered search can turn a customer's ticket description into a live search query intended to deliver helpful information, meaning customers no longer need to submit a ticket because they got the answer they needed through search.

Pretty useful, right? We think so — and that's exactly why we decided to launch Support Answers, a suite of enterprise search solutions built just for customer support teams. It's not just us who saw the upside; our customers did too. We noticed that Yext Answers customers were already using Answers for support use cases, which helped drive our decision to build on that demand formally and create a truly customer-driven, AI-powered solution in Support Answers.

Coming off a year of recession, there's never been a better time to make your help site work harder for you — and for your customers — without breaking the bank on an agent hiring-spree.

Now, with Support Answers, you can help your customers resolve issues on their own, empower your support agents to provide answers more quickly, and streamline the process of addressing support tickets. That's a truly modern on-site search experience — with a potential $75 billion-dollar upside.

Curious? To learn more about how AI search like Yext's Support Answers can help scale your service model and improve quality of support, visit:

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