Show HN: Assembled – Scale great customer support
assembled.com
assembled.com
The technical solution to modeling this out and providing more advanced forecasting is super interesting, and the product itself looks delightful to use (more than the spreadsheets our early support team used to be buried in navigating, at least :)
I'm John, one of the co-founders of Assembled. Our mission is to transform and elevate customer support.
Today we’re launching a product that solves workforce management and helps support teams get staffing right. For the past two years, we’ve been building it alongside some of the most innovative support teams in the world like Slack, Stripe, and Harry’s.
Sam Altman’s startup playbook says: “great startups always have great customer service in the early days” [0], but he doesn’t talk about the later days. It turns out to be really hard to scale great support with spreadsheets and internal tools. We’ve built Assembled after talking to hundreds of different organizations that have been trying to solve this problem.
Our product tackles three core operational challenges:
- Forecasting: We automatically forecast support volume and translate it into the right staffing plan.
- Scheduling: We provide an intuitive team calendar that works across time zones and/or multiple specializations.
- Unified metrics: We make support schedules and metrics, like response times, visible across all levels.
Assembled is available today and you can request a demo here. We’ll be around all day answering questions, so feel free to comment here or email me directly at john@assembled.com.
If I hire Assembled to help with support, what can they provide?
Obviously, they will have zero knowledge of the product. What can Assembled help with here?
Is this about fending the first-line questions, like "please reboot your computer"?
BTW there is like thousands of companies that do that. Not clear what is special here.
> Obviously, they will have zero knowledge of the product. What can Assembled help with here?
These are very good questions and they raise a very valid point: Assembled will not have deep knowledge of your product (at least not as deep of a knowledge as your own support agents). However, we do have deep knowledge about how support teams are run in general. We've talked to hundreds of support teams, large and small, and are knee deep in the customer service industry.
Our product doesn't answer front line support questions, but rather helps you manage agent schedules and determine the best times to staff your agents. To do this, we forecast support volume, and correspondingly, how many agents are required to handle that volume. This is important because a large part of great customer support is how quickly you're able to respond.
This is a much different way to improve support than by just answering questions. We try to make your team more efficient without the need to hire more people. The cool thing here is that you can still layer on deflection systems (to reduce ticket volume) and enhance agent performance (via QA systems) in addition to what we do.
Most smaller teams can get away with 9am-5pm weekday support for quite a while. However, once you have enough volume where you need to start staffing weekends or staffing earlier/later in the day, it becomes a lot harder to manage your team and that's where Assembled comes in.
In addition, just communicating with everyone about shifts and managing the people-side was also a challenge, and there never felt to be super-specialized tools for this.
Accurate staffing seems like precisely the kind of problem that good data and modeling could solve. Good communication is something that good UI design could solve too. I'm excited to see how this works!
It's actually very hard to have both fast response times and high occupancy (the percentage of your team's time actually spent answering tickets). Often a company wants both, but it's hard to convince people that you can't have both. We've helped our early customers show this by actually planning different scenarios out.
Neither of those removes the workforce at scale in my opinion.
Also, AI is real far away from replacing more advanced support teams doing "tier 2" and "tier 3" support which require a lot more work outside of the email/chat thread.
Also to be fair to our team, we do have a bunch of problems that we no longer think of as AI, but are still super algorithm-intensive: forecasting, modeling of queues, and schedule optimization.