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Driving Customer Success Through Data-Driven Insights: Lessons from Dylan Sewell at Workyard

Last week, I had the opportunity to speak with Dylan Sewell, Head of Customer Success at Workyard, a company specializing in time tracking and location tracking for construction companies. Dylan's insights into building a customer success function from the ground up and leveraging data to drive retention offer valuable lessons for customer success leaders across industries. Here's what we discussed:

Driving Customer Success Through Data-Driven Insights: Lessons from Dylan Sewell at Workyard

Last week, I had the opportunity to speak with Dylan Sewell, Head of Customer Success at Workyard, a company specializing in time tracking and location tracking for construction companies. Dylan's insights into building a customer success function from the ground up and leveraging data to drive retention offer valuable lessons for customer success leaders across industries. Here's what we discussed:

Can you tell us about your role at Workyard and what challenges you're facing?

"I joined Workyard in April as the Head of Customer Success. My role is to set up the customer success function because it didn't exist before. Workyard had typical Series A problems - they had a lot of customers but not enough people and processes to support what they were doing. They’re growing at breakneck speed, which is how you want to grow as a Series A company.

My number one job was to tackling churn - Workyard is a great product, but you always have to try to understand where your bucket is leaking - the plus is solving that problem is also just a good, quick win. We're trying to look at churn in a few different ways, with adoption and education being the primary focus. Now that we've set up an implementation team, I'm getting into the cross-sell and upsell part of it."

How did you approach understanding the problems and getting up to speed in your new role?

"I became an implementation manager. I worked support. I did the job. There are tons of CS leaders out there that want to move from leader job to leader job, but this is about getting your hands dirty. You said it already - call your customers. It drives me nuts when I ask somebody to call a customer and they email them instead.

Especially in my career, which has been over ten years now in SaaS, mostly focused on industrial applications like oil and gas, construction, and logistics - our customers don't sit down and write emails explaining their problems. But they will answer the phone and talk to you, and this is how you want to be communicated to. It’s how you get the answers you need to solve their problems because this is how they communicate and do business with their other vendors.

You have to be part of their community and work on the level that they work at. That's how I learn - use the tools, get in with the customers, feel stupid for a little while because they're telling you things and you don't know the answers to them, but you then go find out."

How do you gather and analyze customer data to drive improvements?

"When I joined, a lot of the data gathering was manual. I had to write numbers down in Salesforce because that was the only way we captured data at the time. It's much better today - we have lots of our application data and billing data integrated now.

We're focused on two main goals: reducing churn and driving upgrades. For churn, we're looking at our smaller companies at the 90-day level, which is the riskiest point in the customer lifecycle for any b2b SaaS platform. For upgrades, we recently released a third subscription tier, so we're looking at how to identify customers who are ripe for an upgrade.

We've developed what we call 'upgrade indicators' and 'churn indicators'. For now, I’ve got a Homer Simpson-esque dashboard of blinking lights. I just want the blinking lights to blink at me and tell me what’s broken, and then I respond to them. It's not the best model long-term, but for managing 2000 customers with one person, I need these lights to optimize my time and manage by exception.

For example, one of our upgrade indicators is based on a feature that automates job site logging. We can detect which workers are visiting multiple job sites a day, which indicates they might benefit from an upgrade to reduce data entry.

For churn indicators, we look at trends in usage. It's important to note that usage itself is not a leading indicator - by the time they stop using it, it's often too late. So we look at trends in how they're using specific features, exporting data, etc."

How do you prioritize issues and communicate them to other teams, like product?

"Product is the whole reason we exist, so we have to treat them with that respect. Sales keeps the lights on, but the building is built by the product team. My approach is to bucketize customers based on the products they use and build customer sentiment by features.

For each major feature or aspect of our product, we gather feedback from customers who use it heavily. This gives product managers a clear picture of sentiment across different features. We might find that sentiment is overall negative for our mobile experience but positive for our import functionality. This helps the product team prioritize where to focus improvements.

Of course, we also factor in the financial impact. We might say, 'By the way, this company's got 600 users and they're worth a million bucks.' This helps stack rank the priorities.

It's also crucial to have a great relationship with the sales team. If you can get them to share key pain points from the sales discovery process, you can better measure outcomes for customers and know when to escalate issues."

What advice do you have for other customer success leaders looking to improve their data-driven approach?

"First, understand that not everything you put into place on day one is going to work perfectly. You'll learn over time what metrics weigh more than others. Sometimes a 30% drop in one metric isn't a big deal, while other times it's critical. That's where the manual labor comes in - you have to take these drivers, learn from them, and refine your approach.

Second, focus on the features and aspects of your product that customers actually care about. They don't call you to talk about their business strategy - they call about specific features or issues. Measure your customers by the way they measure themselves and their success on your app. That's how you stay in lockstep with customer value.

Finally, be prepared to get your hands dirty. The best way to understand your customers and your product is to do the job yourself - become an implementation manager, work support, use the tools. That's how you truly learn what your customers need and how to serve them better."

So what did we learn?

Dylan's insights highlight several key principles for building a data-driven customer success function:

  1. Get hands-on experience: Don't be afraid to do the job yourself to truly understand customer needs and pain points.
  2. Develop clear indicators: Create 'upgrade indicators' and 'churn indicators' to help prioritize your focus and actions.
  3. Look beyond usage data: Usage alone isn't a leading indicator of churn. Look at trends in how customers use specific features and other behavioral signals.
  4. Segment by product and feature: Organize customer sentiment and feedback around specific products and features to help prioritize improvements.
  5. Build strong cross-functional relationships: Work closely with sales and product teams to ensure alignment on customer needs and priorities.
  6. Be prepared to iterate: Your initial data models and processes won't be perfect. Be ready to learn and refine your approach over time.
  7. Focus on customer-centric metrics: Measure your customers by the metrics that matter to them and their success with your product.
  8. Balance automation with personal touch: While data and automation are crucial, especially at scale, don't underestimate the value of direct customer communication.

By applying these principles, customer success leaders can create a more data-driven, customer-centric approach to retention and growth. As Dylan put it, "It's about tweaking things. You'll learn over time what weighs more than other things." This focus on continuous learning and refinement, grounded in direct customer insights and data, is key to building a successful customer success function.