How Online Self-Service Speeds Time to Resolution
It’s no secret that online self-service results in faster answers. It’s also not unreasonable to expect that SaaS tech companies have a comprehensive, easy-to-use and high quality self-service offering. But what is it about self-service that delivers so much value over and above static or traditional knowledge base platforms? Here’s how self-service tools get customers the answers they need whilst reducing time-to-resolution …
Online self-service is in demand. In just three years (from 2012 to 2015), Forrester reported that the percentage of people using self-service options for support nearly doubled, and it’s safe to say that this number has been steadily on the increase since.
We are time-poor, and want faster answers.
One key reason that consumers now seek out online self-service is that it simply results in faster answers. That keeps them happy, and means a shorter time-to-resolution (TTR) — not only an important metric for support teams but a proxy for customer satisfaction.
After all, we are all “time-poor”. We’ve all been there before — looking for answers on how to set up our newest gadget or troubleshooting an issue we’ve experienced with a piece of our ‘in-home’ tech. Consumers not only want but expect companies to value their time, and they’re more likely to become repeat customers of those that do.
So how could a self-service online help center add value to your organization by reducing time-to-resolution (TTR)?
Let’s look at three key ways dynamic self-service help centers trump those more traditional static knowledge bases:
People close to and knowledgeable about the issues are responding
When they go online to search for help, people can expect to find a range of solutions from a variety of experts — both brand representatives and other users or peers.
Particularly in the case of technically complex products like B2B SaaS solutions, consumers and end users really benefit when they have the ability to interact with those who have similar issues.
The reality is, 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. Just one month later, the Sonos-plus-Amazon Alexa subforum on the Sonos self-service community had over 900 topics. That’s an average of 30 created every single day! Do you think Sonos’ customer service team could have handled that level of activity without being able to rely on their user base offering peer-to-peer support?
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. This goes above and beyond typical troubleshooting problems and firmly enters the realm of best practice and knowledge-sharing — a wonderful opportunity for your end users to get the maximum value out of your product or service, with no additional cost to you!
With the right help center system in place, companies and brands can collect and repurpose all of this valuable user-generated content into a dynamic, user-driven knowledge base that other visitors can access and use, quickly and easily.
Unlike conventional, static help pages that need to be manually updated — let’s face it, a gargantuan task for your already way over-capacity service team — a dynamic and user-powered help center will always benefit from fresh, relevant and insightful content that needs minimal maintenance to keep attracting and serving visitors and their burning questions.
Answers are sorted and indexed to serve the right answer to the next person
The value of collecting user-generated help content within your knowledge base or help center just grows and grows, especially when it comes to those pesky support questions that tend to be repetitive, complex and mundane.
Typically, companies create a set of static FAQs. The problem here, is that you’re always second-guessing what it is that your customer or end-users really most need or want to know, and often those FAQs become outdated or even useless scarily fast.
On the flipside, imagine if you could collect these typical answers or pieces of knowledge content — dynamically, as they are asked and answered — within a library that is continually maintaining itself, so that hundreds or even thousands of visitors to come can easily access them and move on, quickly and happily … you’ll free your support agents up from having to address the same issues, over and over (and over!) again, and you’ll be ensuring that you’re actually addressing your users’ real needs. Wow!
Perhaps the most essential element of the self-service process and the piece that ensures all three of these benefits can come together in one powerful package, is making sure that consumers or users see the right answers at the right time, wherever they are in their digital journey. This next-generation method of serving support content based on context-recognition and machine learning — right where the user is at any moment in their online self-service journey — is a true value differentiator for self-service help centers.
So what does all this mean for SaaS providers?
Well, in short, it means scaling Customer Success, without the struggle. Check out our ultimate guide to Customer Success here for more information on how to scale effectively and efficiently, retain your customers and grow your bottom line!
Self-service adds value because it respects users’ time and provides high-quality answers, quickly. All vital elements for SaaS companies that need to service hundreds or thousands of freemium users on minimal budgets.
Interested to find out more about how to create a scalable self-service help center for your B2B SaaS solution? We’ve created an eBook detailing 5 help center features that will bring you the most bang for your buck — so don’t miss this resource if your customer service team is ready to do more with less. Download your free copy here.
This blog post was originally published by Ben Foster on November 23, 2017. It was updated by Danielle Juson on March 14, 2019.
