How Online Self-Service Speeds Time to Resolution

Online self-service results in faster answers. Here’s how self-service tools get customers the answers they need while reducing time-to-resolution.

Online self-service options are in demand. In just three years (2012 to 2015), Forrester says, the percentage of people using online communities for support nearly doubled.

One important reason that consumers seek out online self-service is that it results in faster answers. That means lower time to resolution (TTR) - not only an important metric for support teams but a proxy for customer satisfaction. After all, as we talk about here [link], consumers want companies to value their time, and are more likely to be repeat customers of those that do.

How does online self-service add value by reducing TTR?

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People close to and knowledgeable about the issues are responding

When they go online to get help, people can find a range of solutions from a variety of experts - both brand representatives and other users.

Particularly with technically complex products, consumers benefit when they can interact with those who have similar issues.

And people flock to platforms that let them ask and answer questions in an authentic way. For example, Sonos launched its voice-controlled One speaker in late-October 2017. As of this writing, a month later, the Sonos-plus-Amazon Alexa subforum on the Sonos community has over 900 topics. That’s an average of 30 created per day!

Self-service generates a constantly growing knowledge base

Sonos’ experience is typical. When people can interact authentically to share insights, they end up having real conversations about products and services.

With the right knowledge management system in place, brands can collect and repurpose this valuable user-generated content in a knowledge base that others can use.

Unlike a conventional help pages that must be manually updated, a user-powered knowledge base always features fresh, relevant content.

The inSided platform even lets companies publish user-generated KB content on other digital platforms, like an app or a FAQ page.

This kind of cross-platform content sharing helps consumers get answers faster, and leads to big savings for brands. Companies that use an inSided community for customer service typically see support calls drop by 15 percent to 25 percent.

Answers are sorted and indexed to serve the right answer to the next person

This reflects the value of collecting user-generated help content in a knowledge base. Support questions tend to be repetitive, and if you collect them in a library that others can refer back to, your support agents won’t have to address the same issues over and over.

What’s essential in this process is making sure consumers see the right answers at the right time. The next frontier for peer-to-peer support - something that’s already built into the inSided platform is content intelligence powered by machine learning.

This next-generation method of serving support content recognizes context. If a person is looking at the “specs” section of a smartphone product page, they might see user-generated Q&A about device specs.

The goal is to always provide the right answer at the right time, at all stages of the customer journey. With machine learning powering support, people can get help and advice even before they realize they need it. That will accelerate support even further - and improve customer satisfaction into the bargain.




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Ben Foster

Content Marketer at inSided. Having worked in B2B tech in San Francisco and Boston, Ben's now happy to be in New York City. He'll never root for the Yankees, though. Connect on LinkedIn

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