“What surprised me most was how quickly the whole experience started to click. With Milo, we could move in real time, work through exceptions as they came up, and keep making progress without losing momentum. That really changed what I expected an implementation could feel like.”
–Denise Schnier, Senior Director, Finance Systems & Integrations, Fullsteam
About
Fullsteam is a payments and vertical software platform company with more than 80 business units. It acquires and operates SaaS businesses across many industries, giving each shared services, payments infrastructure, and operational support while letting them keep their own brand.
Industry:
Software and technology
01
The Challenge
Fullsteam grows through acquisition, so bringing on new business units is an ongoing process. As the company modernized billing and revenue on Zuora, moving off NetSuite and connecting Salesforce and Zuora CPQ, data migration was a challenge to scale. Every acquired business unit arrives with its own source systems, which used to mean reshaping raw data into rigid templates and manual corrections. Each exception meant more time and resources.
02
The Solution
Fullsteam uses Milo, Zuora’s implementation agent, to change how its team approaches migration and onboarding. Milo lets the team work from source data in its existing form, removing manual transformation. When issues surface, the team resolves them in the flow of implementation instead of waiting, while keeping teams in the loop to check accuracy.
03
The Benefits
- 80% headcount reduction across the workflow, with fewer employees necessary to onboard new business units and complete the data migration process
- Increased efficiency with fewer team members: Fullsteam now onboards 5-6 business units every other month with one full-time employee. Previously, each business unit needed a dedicated, full-time employee.
- More team time redirected to higher-value work
- Human review and validation built into every step
“What gave us confidence was that we still had the validation piece. We could move faster, see what was happening, and confirm the data was accurate while spending far less time on the manual work.”
At Fullsteam, implementation is a constant, ongoing process: growth by acquisition means new business units and new data keep arriving. That reality shaped the real question behind Fullsteam’s Zuora work: could onboarding get easier with each new business?
Before Milo, the heaviest lift happened before a record ever loaded, reshaping raw data into rigid templates and repeating the upload-check-correct cycle by hand. Because Fullsteam’s acquisitions don’t arrive with standardized systems, that burden compounded with every new business unit.
“As we onboard new businesses, the data is not always standard,” Schnier said. “What stood out with Zuora was the ability to work from different source data formats without forcing everything into the same manual template process first.”
With Milo, the team works from data in its existing form rather than reshaping everything up front, and addresses issues in the flow of implementation instead of offline, one failed load at a time. Problems that once cost days now get worked through in real time.
None of this came at the expense of oversight. Validating what Milo produced and confirming accuracy along the way let AI take on the repetitive work while people stayed focused on judgment and cleanup. For a finance team accountable for a shared system of record, that balance made the shift worth trusting.
That mix now shapes how Fullsteam staffs onboarding, letting the team manage far more business units with far fewer people, and letting implementation keep pace with growth instead of holding it back.
For a company managing onboarding across dozens of business units at once, Milo’s impact goes well beyond any single go-live. Each new acquisition no longer means rebuilding the same process from scratch, and a small team can carry a growing pipeline of work while keeping the control an enterprise finance function needs.
“Before Milo, data migration for implementation meant too much manual transformation, too much waiting, and too many repetitive steps. With Zuora, we work through issues faster, spend less time loading data, and focus more effort on getting the data right.”
