Voltera Turned Closed Deals Into a Clear View of Profit, Cost, and Agent Performance

At a glance

• Sales, operations, marketing, finance, and recruiting data from 5 systems unified into BigQuery
• A full funnel model connecting Meta ad spend to closed installations and true cost per deal
• Per agent performance and cancellation rates now visible before they become a pattern

Voltera runs a full sales operation across the Netherlands, from Meta ad to signed quote to physical installation. Every deal that closes earns a commission, costs procurement and back office time, and either becomes profitable or quietly doesn't. The team could see the deal closing. They could not see what it actually earned.

Their individual systems worked well. The CRM tracked quotes and closes. The ERP handled installation and procurement. Meta Ads ran the campaigns. But margin lives in the gap between systems, and that gap was where Voltera's real numbers were hiding.

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The Problem With Margin Spread Across 5 Systems

As deal volume grew, so did the difficulty of answering one question: which deals actually made money. The team needed to trace ad spend to closed installations, attribute commission and procurement cost per deal, and see which closers were driving revenue versus which were driving cancellations.

These are not exotic questions. They are standard questions for any sales operation managing margin at scale, but five disconnected systems could not answer them without a manual pull every time.

Every system Voltera relied on, connected into one warehouse:

The data existed. The problem was connection. Without a warehouse underneath, every margin calculation meant pulling five exports by hand, so it almost never happened.

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Why the Standard Answer Did Not Fit

The instinctive response is to hire a data engineer, connect the CRM and ERP, and build a margin report in house. That works for some teams, but a hire takes months to ramp up and still only owns one layer of a five system funnel.

Voltera did not need a headcount. They needed a foundation, built fast, deployed on their own infrastructure, by a team that had built this exact funnel model before.

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What Vero Built?

The architecture we deployed runs on one constraint: every system in the deal journey feeds one warehouse automatically, with true margin calculated once and trusted everywhere.

• dlt connects all 5 sources, CRM, ERP, Meta Ads, Moneybird, Manatal, and handles schema evolution so new fields never break a downstream report
• BigQuery is the single warehouse where sales, operations, and marketing data live side by side
• dbt staging models clean each source, intermediate models join quotes and closes to installation, procurement, and ad spend, mart models surface true margin per deal and funnel conversion
• Dagster on GKE runs every pipeline on schedule with sensors and Slack alerts on failure
• Hex powers two live dashboards, a KPIs Dashboard for management and an Agent Sales Dashboard for each closer

Every deal now carries one true margin number, planner and closer commission, installation, procurement, and back office cost all attributed in a single model.

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How the Rollout Happened?

The engagement moved in three stages

1. Discovery: mapped all 5 systems, understood how leads moved from Meta ad through quote, close, and installation, and defined the margin components that mattered
2. Warehouse setup: ingestion stood up and validated, the CRM refreshing every 15 minutes, accuracy checked against each source system
3. Dashboards live: dbt models built incrementally, starting with the funnel and true margin, then expanding into per agent performance and cancellation tracking

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 knew a deal had closed but not what it earned. Real margin meant pulling the CRM, the ERP, and Moneybird by hand, and by the time the number surfaced, the quarter was already over.

• Ad spend now traces directly to closed installations, not just leads
• True margin per deal is visible the day it closes, not at month end reconciliation
• Top closers by revenue are ranked in the KPIs Dashboard, not guessed at
• Cancellation rate is tracked per agent before it becomes a pattern

Nobody on the team manages infrastructure. The stack runs on their own cluster, fully owned, with monitoring and alerts built in.