Optimizing the experience of thousands of new ERP users so they reach the product's real value

Role

As a Growth Designer I had a specific initial problem to solve: new users weren’t reaching the product’s value. In practice, it became strategy, research and execution work at the same time, always tied to data and to what people actually did inside the product. There were 31 initiatives over two years, with impact measured in activation, revenue, tax document issuance and feature discovery.

Strategy

What the business called “activation” was, in practice, four overlapping layers:

• Measurement: each team measured something different, with no shared definition.
• Organization: CS as a scaling bottleneck, human dependency that didn’t grow with the user base.
• Product: invisible paths, empty states with no guidance, an unstructured first experience.
• Data: no structured understanding of why users churned.

Tackling one layer at a time would barely move the needle. I stopped treating activation as a feature queue and started treating it as a system. That’s what let the impact accumulate instead of dilute.

Process

I don’t propose a solution before understanding the context. Here that meant three things: talking to customers to find the real pain points, mapping the product to understand the business from the inside, and listening to operations teams, who saw friction no dashboard showed.

I use AI in discovery and execution to gain speed, mainly in data analysis and research synthesis. Every initiative starts with a clear hypothesis and a defined success metric before designing any screen.

• Hypothesis-Driven
• Mixed-Methods
• Metrics-Driven
• AI-Augmented

Diagnosis

Every design decision here was grounded in real evidence, tied to the business, its goals, and its experience and operational problems. Each one came from a diagnosis phase. The sequence below is in the actual order it happened, and each step fed the next.

1. 01Stakeholder interviews↓
2. 02Redefining activation↓
3. 03AI-assisted secondary research↓
4. 04Market reference analysis↓
5. 05CS observation & interviews↓
6. 06Support ticket analysis↓
7. 07Current-flow mapping↓
8. 08Service blueprint↓
9. 09Native onboarding mapping↓

Solution

Eight initiatives, grouped by impact area. Each one attacks a specific failure point exposed by the diagnosis.

Onboarding at scale+40% sales created↓

Contextual banners+109% CTA clicks↓

Empty states & +New+18% sales · 1,392 entries↓

Tax document issuance+189% NFS-e created↓

Search & navigation+600% Pix access↓

Trial gamification+500% trial conversion↓

AI-assisted import+44% interest↓

Training scheduling↓

Impact

Per-initiative metrics are in the previous section. Here: what changed in the organization.

• Activation went from 30% to 51.6%

  This is the number that ties the 31 initiatives together. The 30-day activation rate hovered between 28.8% and 36.2% when I started, and the team’s target was 60%. Over the period it climbed consistently and reached 51.6% in October 2025, hitting between 100% and 117% of the monthly target. No single initiative explains that movement — it comes from the set, which is precisely the argument of this case.

• New team created

  The diagnosis made visible problems that had always been there, but that no team claimed as their own. The 200+ opportunities I mapped became the foundation of a new team dedicated to experience quality. That team inherited the entire backlog that came out of the project’s artifacts and started owning parts of the product that previously had no owner.

• CS freed from onboarding

  Standard onboarding stopped depending 100% on human support and started working on its own, without needing to grow the team. That let CS focus where it really makes a difference: complex accounts, at-risk customers, and specialized support.

• AI-assisted discovery spread

  I documented the way of researching and synthesizing with AI, and other designers on the team started adapting it into their own work. The method ended up paying off well beyond this project.

Reflection