Digital Self-Service: How to Take it to the Next Level

Do you remember how many times you went into a bank for service in the last several years? Maybe once. ATMs virtually eliminated the need to go inside a bank, and mobile banking has taken it one step further by eliminating the need to even go to the ATM.

When it works, customers like the ease and efficiency with which they can accomplish their goals through digital self-service. They want self-service to be smarter and want to accomplish more with it. Here are some examples of digital self-service failures even for common questions that we have encountered from websites of Fortune 500 companies.

Interactive voice responses (IVRs) struggle here as well — they often lead to conversational cul-de-sacs that cause you to keep making U-turns. In a consumer survey on IVRs, “The State of IVR Customer Experience,” a whopping 88% of 500 respondents said they were not intelligent enough, and 73% complained that they had to repeat what they told the IVR to human agents when their concerns were escalated.

While technologies such as generative AI promise to improve the effectiveness of chatbots, many of the chatbots on company websites barely go beyond meet-and-greets and sending a link to an FAQ page.

How can we take self-service to the next level?

To fix self-service, we first need to deconstruct the steps involved in self-service: connecting, understanding, solving and optimizing. Coincidentally, they also apply to human-assisted service.

Self-service can happen at many touchpoints — including an IVR, website, mobile app, messaging function, live chat and so on. Point products support specific channels, often just one, for connecting with the customer. And do-it-all toolkits, while they might check all the boxes in terms of supported channels, often fail to take advantage of the richness of individual touchpoints. Ask potential solution partners how deeply they support individual touchpoints. Do they have a BYO (Bring Your Own) architecture that will allow you to easily add new touchpoints?

Many self-service systems do a poor job of understanding customer intent, as is evident through the examples I provided earlier. Customers don’t often state their problem. They just know what the symptom is and express it in different ways, which are called “utterances” in tech parlance. Ask potential solution partners how their tools map utterances to true intents and go on to solve problems.

The “solve” phase may entail finding the answer needle in a document haystack or going through a self-service conversation with the customer to resolve an issue. It is like what a doctor might do in the case of a diagnosis or what an expert advisor might do in the case of a product recommendation. When it’s not done well, this can lead to a phenomenon called tech support rage, as the New York Times so eloquently articulated (paywall).

Legacy self-service systems often throw FAQ lists or encyclopediac documents at the customer and do not give them the exact information they need. The result is that the customer has to call the contact center. Or, the self-service system transfers them to human agents, often without retaining the context of their inquiry.

The solution is to make sure your self-service system is backed by a knowledge management system that can help customers (and employees) find the answer in the content haystack, including long documents, and where needed, drive a conversation with the customer and ask clarifying questions to guide them to the answer. For instance, eGain has a feature called Instant Answers™ that leverages a large language model to pinpoint answers in a long document or compile an answer from multiple sources, while pointing to the references.

Without connected insights into customer journeys across touchpoints, agents’ use of knowledge, and the operation of the contact center, customer service managers are often flying blind. We all know about Customer 360, which refers to a state in which you have complete context about a customer. To optimize self-service (and agent-assisted service) performance, you should also work toward creating a state of “Insight 360” to ensure you have connected insights across customer journeys, use of knowledge and contact center operations. For example, connected insights can tell you how knowledge content served agents proactively at friction points in a customer journey to reduce journey abandonment. You can gain insights like these through A/B testing. As another example, you can use A/B testing to assess how the use of knowledge impacts first-contact resolution across two groups of contact center agents: one that’s using the internal knowledge base and one that is not.

While technology clearly matters, so do best practices for self-service success. Here are some you can leverage over time:

Self-service can be a win-win for the customer and the business. Make sure you execute the “connect, understand, solve and optimize” phases well, follow best practices and look for risk-free adoption options to take self-service (and human-assisted) experiences from “rage” to “rave.”
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The article was first published on Forbes.com