Fintech / Investment Foundation Build CFO partnership

From spreadsheets to BI

Whisky and wine investment platform with no centralised analytics. Built the foundations from zero, worked daily with the CEO, CFO, and CPO.

150h+

saved monthly across 6 stakeholders

40%

cut on monthly marketing spend

11%

increase in lead generation

100%

of manual reports eliminated

The client

A whisky and wine investment platform offering individuals the opportunity to diversify their portfolios through rare and premium products. The platform combines fintech, alternative asset investing, and client advisory. It operates across multiple markets with high-volume lead generation, investor relations, and financial operations.

The problem

No centralised analytics infrastructure. Reporting was entirely manual, scattered across spreadsheets, with data living in disconnected tools - Hubspot, several ad platforms, Calendly, Xero. No dashboards, no warehouse. Key business metrics from marketing performance to financial reporting were calculated by hand. Decisions were slow and error-prone.

Architecture

flowchart LR A["21 source systems
Hubspot, Google Ads,
Meta Ads, Calendly, Xero, etc."] -->|Fivetran + Python| B[("BigQuery
warehouse")] B -->|SQL data layer| C["Looker Studio
dashboards"] C --> D["Sales"] C --> E["Marketing"] C --> F["Finance / CFO"] C --> G["Product"] style A fill:#f0e8db,stroke:#1a1a2e style B fill:#d8c8ed,stroke:#1a1a2e style C fill:#b6e0c2,stroke:#1a1a2e style D fill:#f4c8a8,stroke:#1a1a2e style E fill:#f4c8a8,stroke:#1a1a2e style F fill:#f4c8a8,stroke:#1a1a2e style G fill:#f4c8a8,stroke:#1a1a2e

What I did

01.Built a centralised data warehouse in Google BigQuery, integrating 21 source systems (Hubspot, Google Ads, Meta Ads, Calendly, Xero, etc.).
02.Built data pipelines across 21 connectors using Fivetran for supported sources and custom Python API connectors deployed via Google Cloud Functions for the rest.
03.Created a pipeline to store historical data for stock levels and inventory, which were previously only available as point-in-time snapshots.
04.Eliminated 10+ manual spreadsheets used for financial metrics, marketing performance, and lead tracking.
05.Designed and implemented a suite of automated dashboards in Looker Studio for Sales, Marketing, Finance, and Product.
06.Created an Analytics Landing Page to organise all reports and ensure team-wide access.
07.Worked directly with the CEO, CFO, and CPO on a daily basis, aligning data strategy with business goals and key decisions.
08.With the CFO: defined and created user segments; calculated previously unavailable metrics including sales velocity, Gini coefficient, Rule of 40%, and LTV per segment; built an automated Portfolio Overview downloadable as PDF for investors; built the CFO's daily-use dashboard.
09.With the CPO and Growth team: identified high-value user segments enabling targeted marketing strategy, calculated referral attribution and other previously unavailable growth metrics, and unified data across systems that could not be joined before to automate Agent performance metrics.

What it actually looks like

The Analytics Landing Page I built for the team

Looker Studio

Analytics landing page organising marketing, finance, product, agent and stock reports

Headline outcomes

Each metric, against the baseline it replaced

12 months post-implementation

Tools used

BigQuery Fivetran Looker Studio Python Google Cloud Functions Hubspot Google Ads Meta Ads Calendly Xero

"From day one she delivered impact that exceeded expectations. Bernadette led the end-to-end design of our new cloud data warehouse, building robust, well-documented pipelines that unify marketing, sales, and finance data in near real-time. She then crafted a suite of intuitive dashboards that put the right metrics in front of every decision-maker, from C-suite to front-line managers."

Vedat Mizrahi

CFO, Decant Group

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