When I began working as Director of Support for Handshake, a career community that connects students and employers, I thought my role would focus largely on hiring, managing a team, and improving workflow—but I’ve come to find out that modeling data and automating processes is just as important. And with everything we do, we need to leave room to improvise.
At Handshake, we handle over 100,000 support tickets per year with a maximum response time of twenty-four hours—with a lean but dedicated customer support team o. It’s a lot of volume for a small team to handle, and our customer support needs are only growing as Handshake scales.
Here are the lessons I’ve learned about the strategies that help our support team delight our customers day after day.
Lesson 1 – Sweat the Details.
Invest in collecting data and use it to learn from the past and anticipate the future. Your team and your customers will thank you for it.
Don’t keep your support team in a silo. Partner with data and finance to gather insights on your company’s performance, and connect with communities and peers at other companies to learn best practices for building a strong support team, focusing on three levels—your team, your department, and your company.
When hiring and managing people, situate them strategically to leverage their strengths and skillsets, grouping them in ways that enable them to learn from and lean on one another. Paying close attention to each employee’s impact will help you visualize different scenarios and see the impact on the rest of the team.
By gathering insights from your finance and analytics teams, you can provide more accurate and proactive budgeting, forecasting, and staffing. Use modeling tools and build scenarios to understand your cost model, ROI of investments, and tradeoffs.
By building clear communication between departments and building a stronger strategy, you’ll be able to elevate the role of support within your company. This will help you strengthen partnerships with other departments like finance, data, success, sales, product, engineering, and People/HR.
Lesson 2 – Expect the Unexpected.
Data won’t tell you everything, though. You need to build a sustainable system that allows you to roll with the punches when things don’t go as planned.
For example, we used to have one employee staffed on tech support year-round. That worked—except when it didn’t. It tended to be a seasonal business—they’d get swamped in summer, and need to put out too many fires. It also made things tricky when our employee took paid leave, as we had no one knowledgeable to step in to support customers on technical issues. Although data told us the job could be filled by a single person, we found enough exceptions to prove that it made sense to add another support person as backup.
Rely on data, but listen to your team’s and customers’ feedback, too. If things aren’t going according to plan, don’t be afraid to shift your models.
Lesson 3 – Check yourself before you wreck yourself.
As Director of Support, I’m responsible for a lot of moving parts. I pay attention to metrics like handle time and tickets per agent per day. But even with all the models and forecasts I have available, things can get tricky when it comes to variables like seasonality, learning how to handle different types of customers and their communication needs, and taking into account unplanned work, technical incidents, or coverage for out-of-office employees.
This is where smart tools and ops come into play to help me simplify my workflow. We use a variety of tools, including Solvvy for help center search and self-service which has helped us scale immensely. We use a broad mix of solutions because it allows us to customize and incorporate unique elements of our business into our reporting and staffing model.
Finally, we do a monthly review of all our data against our forecasted models, and see how closely we match up. We pay attention to which metrics aren’t where we’d like them to be, and make plans to improve them, either through additional staffing or technology support. Once a quarter isn’t enough—a monthly review is crucial to make sure important details don’t slip through the cracks.
Lesson 4 – Share and pay it forward.
Finally, once you’ve found a system that works effectively, be transparent with your team and colleagues about your model and look for other opportunities to apply the same template or approach.
As you scale your support strategy across different initiatives, don’t be afraid to seek out experts or stakeholders for help. Start out with small tests to make sure your hypotheses are correct before leveling up from there.
Remember that not everything is an easy answer, and your models are a work in progress: For example, after bringing on contractors to help us with moderation, we needed a way to forecast volume, contractor needs, and costs. We’re building models now to evaluate the best approach and the tradeoffs of various scenarios now.
It’s also important to share your successes and models to help other teams at your company. For instance, at Handshake, our product team launched new community and messaging features based on our support model. Focus on collaboration across teams, be generous with your knowledge, and rely on the wisdom of others to help you meet your leadership goals.
I’ve discovered that data is critical for forecasting and planning a customer support strategy —but not everything that can be measured counts, and not everything that counts can be measured.
Never forget that’s a human in your sheet, not a number.
A model is just that, a model. We start with our models, and then learn, grow, and repeat.
Would love to hear your thoughts, feedback, and learnings on scaling support too! Feel free to hit me up here.