GovPlus unifies 9 disconnected systems into one warehouse and finds the exact products driving a refund crisis

At a glance

• Customer support, payment, and reputation data from 9 systems unified into a single BigQuery warehouse
• Cross domain dbt models that joined refund transactions to complaint data and named the root cause
• Refund rate cut in half and CSAT up across every support channel within weeks

GovPlus is a SaaS company built around government services, where trust is the product. Every refund, complaint, and review either confirms that trust or chips away at it. The team tracked all of it, but the visibility ended where the data lived.

Their individual tools worked well. Intercom captured conversations. Chargebee processed payments. Reviews landed on Google, Trustpilot, and BBB. But nothing connected them, and the gap between the systems had started hiding the real story, the kind that only shows up once you can see everything at once.

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The Problem With Fragmented Data at Scale

As complaint volume climbed, so did the difficulty of answering one question: why. The team needed to know which products were driving refunds, whether CSAT was actually dropping, and if review sentiment matched what support tickets were already saying.

These are not exotic questions. They are standard questions for any company managing trust at scale, but nine disconnected exports could not answer them. Every analysis turned into a side project before it could turn into an answer.

Every system GovPlus relied on, connected into one warehouse:

The data existed. The problem was connection. Without a warehouse underneath, every team was reading half the picture, and half a picture hides what matters most.

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Why the Standard Answer Did Not Fit

The instinctive response is to hire a data engineer, spin up a warehouse, write the connectors, build the dashboards in house. That works for some companies, but a hire takes months to find and ramp up, costs well into six figures a year, and still only covers one layer of the stack.

GovPlus did not need a headcount. They needed a foundation, built fast, owned on their own cloud, by a team that had already built this exact architecture before.

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What Vero Built?

The architecture we deployed runs on one constraint: every source feeds one warehouse automatically, with no manual exports standing between the data and the answer.

• dlt connects all 9 sources, Intercom, CloudTalk, Chargebee, Paycom, Google, Trustpilot, BBB, and loads them into BigQuery on a schedule
• BigQuery is the single warehouse where support, revenue, and reputation data live side by side
• dbt staging models clean each source, intermediate models join refunds to complaints to reviews, mart models surface CSAT, refund rate, and complaint to refund ratio
• Dagster Cloud keeps every pipeline running on schedule with monitoring built in
• Hex powers three live dashboards, Operations, Sales, and Product Evaluation, with AI threads so anyone can query trusted data directly

Every metric now has one definition the whole company trusts. No more reconciling numbers before a meeting can even start.

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How the Rollout Happened?

The engagement moved in three stages.

1. Discovery: mapped all 9 systems, understood how support, revenue, and reputation data related to each other, and defined the KPIs the team needed to trust
2. Warehouse setup: ingestion stood up and validated, all 9 sources began flowing into BigQuery, accuracy checked against each source system
3. Dashboards live: dbt models built incrementally, starting with CSAT and refund rate, then expanding into the cross domain models that connected refunds to complaints by product

The full stack was live and in daily use within the week.

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What Changed for the Team?

The difference was not subtle.

Before, the team could see complaints rising and refunds climbing, but not why. Every theory required manually cross referencing spreadsheets from three different systems, and by the time an answer surfaced, the problem had already grown.

• Refund rate halved after cross domain data named the exact products driving it
• CSAT climbed across every support channel once performance was visible in one place
• Leadership syncs start with decisions instead of twenty minutes of reconciliation
• New questions get answered directly in Hex, without waiting on an analyst or an export

Nobody on the team manages infrastructure. The stack is intentionally simple, and that simplicity is what took GovPlus from nine disconnected systems to a root cause in weeks, not quarters.