This is fantastic. I started Stripe's support team, built out our version of an internal tools team, and have since advised a bunch of mid-range startups on how to scale operations. Every company I've talked to is trying to figure out how to improve response times, but really lacks visibility into when load is coming in -- and especially any visibility into when it will come in.
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 :)
Thanks for the kind words! We've definitely seen a ton of small companies that started out with spreadsheets and internal tools. That's why we wanted to mimic the ease of use of Google Sheets while providing out-of-the box features that support teams usually ask for, like forecasting.
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.
I have a startup, we have a nice new product -- and obviously, there are some product specifics ,so we have our own support team, that we train to learn the product, and be able to answer customer questions, and so on.
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.
> 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?
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.
Congrats on the launch! What's the minimum number of support agents do companies need to have before you're a good fit for them? Or how do you think about what a qualified customer looks like?
Thanks, and that's a great question! We're targeting companies with 10 or more support agents. More generally, we're best for companies who are starting to see some amount of complexity in their customer support. Some examples include: if you're launching phone/chat/realtime support, if you have multiple specializations in your support team, if you're extending hours to the weekends.
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.
This is really cool! I'm working with a customer support team and getting the right amount of staffing was always a challenge. To really reliably have good support with low wait times for 95% of the time, you'd end up being overstaffed by quite a bit for >50% of the time.
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!
These are definitely the kinds of problems we're trying to solve. We've been working with our launch customers to get their whole company to understand the tradeoffs involved in customer support.
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.
For now, AI is working as a good deflection in front of the workforce. I think that will continue and get a lot better over time, but will likely still just be a combination of deflection in the front, as well as enablement for agents by giving some good summary resources that may make responding faster.
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.
+1, very much agree with this. AI-driven chatbots are a piece of the puzzle for many of our users -- they cover commonly asked questions and can deflect a lot of questions. But it’s still just a portion of the work (even if a majority of volume). For example, a lot of “hard” support questions involve jumping between systems and following complicated (often nonexistent) procedures, even aside from models that understand intent.
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.
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 :)