Customer success the Simply way: How we reduced ticket response time by 98%
The short answer: Data.
I joined Simply’ Customer Success efforts at a time when it became clear that we need to make a radical change in the way we do support. At Simply we work in small multidisciplinary teams called pods, each dedicated to a different business objective, for example user acquisition, retention, monetization, etc. Each pod is comprised of different disciplines (designers, devs, product) according to its specific needs. At the time I joined we spread our customer success (CS) owners across different pods, allowing them to specialize in different areas of our learners’ journey.
(Here’s our CEO Yuval Kaminka explaining just how it works in the Reversim Summit).
The intention to have CS in several different pods was to allow CS owners to become experts in specific use cases so that the support they offer to our learners would be super specific. The rapid growth that Simply has experienced over the last year demanded that we reassess our priorities.
While our goal to offer superior support was reached, it ended up hurting our velocity. In fact, at one point, people learning how to play piano or guitar with our apps Simply Piano and Simply Guitar were waiting up to 10 hours to hear back from the CS representative who specialized in the area they needed help with. Understanding that our learners often reach out to us while they’re learning how to play the piano or the guitar was critical to help us make the decision to make reducing our response time our main focus, without harming the quality of our support efforts.
Within a month, the wait time was down from 10 hours to under 10 minutes, and four months later down to 1.5 minutes! This text will share how we pulled it off, and how it connects to our approach to data and the idea of impact velocity at the core of our company culture.
The game-changing move
Our raison d’etre at Simply is to enable anyone and everyone to learn a musical instrument. Our most popular apps, Simply Piano and Simply Guitar, teach millions of people without any prior knowledge how to play from the comfort of their home. As such, all of our resources are dedicated to creating the best possible learning experience. Now imagine learning to play the piano with our app Simply Piano and suddenly encountering a bug that halts your progress, for example.
We are a data-driven company, meaning we are heavily invested in data analysis to direct us to areas of potential impact. So naturally, we turned to our data to launch a thorough re-mapping of our learners’ needs, analyzing historical data of the average daily and hourly queries we received to understand our learners’ behavior. It looked like this:
As you can see, there is not a single time of day without support tickets (the numbers are a snapshot that reflects the distribution over time, not the actual volume). Adding to the complexity, due to the nature of a highly technological app, learners’ queries are spread out over various types of speciality.
This led us to the understanding that the way our support team was structured, with two separate areas of speciality, was creating extensive lag times and long queues due to the split between those specialties. Historically, we divided the support team into two, each focusing on a different part of the learner journey — monetization and retention. We believed this would serve both our learners and our CS owners as the former would get specialized service and the latter would only need to learn one part of the funnel and form a deep understanding of the issues. Win-win. However, this specialization turned out to make us slow. Having two different disciplines meant we needed to maintain significant manpower redundancies and also create two different on-boarding processes for new teammates. Lose-lose.
So what’s the opposite of a specialist? Through analyzing support tickets issues across times of day and subject, we realized we need to build a team of generalists because our learners’ issues were not fragmented. The problems they encountered impacted their experience throughout the journey, not just in the beginning or the middle of it. ie. It made sense that we all had a holistic picture of the issues to better understand and serve them.
With this new understanding, we took on the massive task of uniting the two teams and standardizing our knowledge, training everyone on the team to know all there is to know about our products so that we can best support them.
This might sound like a nightmare to some (double the knowledge, double the work) and a dream to others (the more context available, the richer the work experience). The most important thing that we realized was that specialization was not as important as we previously thought, and we were able to chuck that out the window to reexamine what actually is important — being more responsive — and to act on it.
Challenges lead to resilience
Thankfully, most of our teammates saw this desired transition as an opportunity for personal growth and we were able to involve them in our research and planning. This was fundamentally a team effort and could only work with high levels of trust and cooperation. As our CS representatives are on the frontline, so to speak, directly interacting with our learners, they had boundless knowledge that we now needed to gather, tag and share before populating our new SaaS platform with all of it, sorting out all possible areas of support and mapping out the relevant answers.
We also opened a dedicated Slack channel for this, and encouraged team members to be open about knowledge gaps they may be experiencing so that they could help each other and help spread the knowledge. When the circumstances are right, knowledge spreads like wildfire.
The Results
It turned out that getting rid of areas of speciality and sharing all the knowledge with all teammates allowed us to get dramatically better results with the exact same resources. Not only were our learners more satisfied, but our teammates felt like they were growing their own skills and their own understanding of the whole funnel. This, in turn, ignited their passion to do even better, without any external triggers or KPIs.
Within a month of implementing this change we were able to reduce learners’ wait time to less than 8 minutes- That’s a 98.7% improvement, without increasing our resources at all.
And to validate that this really had a significant impact on our learners, our CSAT scores, which gauge satisfaction rates with our support team, rose from 83.1% to 88.5% within the first month after this transition.
Hopefully, this indicates better customer experience within the app and will lead to improved user retention down the line.
Our next big move
To summarize what happened, this is what our responsiveness metrics looked like when we made the decision to transform our CS owners & representatives to generalists (>10 Hours response time):
Today, five months after we first made the change, we are now down to an even dreamier response time than our initial goal:
And our CSAT score has improved accordingly:
Our success helped us realize that there are quite likely more areas for impact and we are currently doing a holistic rethink of how we actively listen to our learners. After tackling response time, we’re now rolling up our sleeves to make us not only faster, but also smarter, by introducing key changes to the way we collect and organize data so that we can have better insights and perhaps preempt our learners’ need to reach out to our support in the first place.
