Analytics & Data Visualization
The answers are already in your business data. The problem is that no one has made them visible yet.
What's Already in Your Data
You're making decisions based on feel. Your data knows the answer.
Most businesses are sitting on more useful information than they realise — in their accounting software, their CRM, their spreadsheets, their website, their point-of-sale system. The patterns are there. Which customers come back. Which products actually make money. Which months are predictably slow.
The work is taking that raw data — wherever it lives — and turning it into something visual and readable. A chart that makes a trend obvious. A dashboard that answers the question before you have to ask it. A one-page report you can actually use in a weekly meeting.
No data warehouse required. Most of what businesses need can be built from data they already have — exports, spreadsheets, and existing software. No data team needed to get started.
Visual dashboards
A single screen that shows what's happening in your business right now — sales, costs, customers, whatever matters most to you
Pattern & trend analysis
Surface the trends buried in your data — seasonality, customer behaviour, product performance — that aren't obvious from a spreadsheet
Automated reports
Replace the spreadsheet someone puts together manually every week with a report that runs itself and lands in your inbox
Data from your existing tools
Pull together numbers from QuickBooks, Shopify, your CRM, or wherever your data lives — no new software required
Make Sense of the Data
Four things businesses ask for most
Most of what businesses need falls into one of these four categories. Non-standard sources get scoped individually.
Business Dashboard
A live view of the numbers that run your business — revenue, margin, customer activity, whatever you currently have to dig for. Updated automatically, visible to the right people, no spreadsheet required.
Sales & Customer Analysis
Who your best customers are, what they buy, when they come back, and what predicts churn. Built from the transaction data you already have — turned into something you can act on.
Automated Weekly Reports
The report your team puts together manually every Monday — automated. Same numbers, same format, zero manual work. Delivered by email before the meeting starts.
One-time Data Analysis
A specific question you need answered from your historical data — pricing analysis, product mix, seasonal patterns, cost breakdown. A structured analysis with clear findings, not a raw export.
How It Works
Start with the question, not the data
The starting point is always the same: what do you wish you knew about your business that you currently have to guess at? Everything else — what data to use, how to visualise it — follows from that.
Start with the question, not the data
Start with the decision you're trying to make or the thing you currently can't see clearly. That defines everything.
What data do you already have?
Available data sources identified — exports, reports, spreadsheets, software — enough to answer the question or not.
Build and review together
A first version built quickly, walked through together, and refined until it's actually useful — not just technically correct.
Hand off something you'll use
You get a dashboard, report, or analysis that your team can use without needing anyone to explain it — and that updates on its own where possible.
How long does it take? A focused analysis or simple dashboard typically takes 1–2 weeks. A more complete business dashboard with multiple data sources runs 3–4 weeks. Scoped before start — no surprises.
Works with what you have
QuickBooks, Xero, Shopify, spreadsheets, your CRM — no new software needed to get started
Plain visuals, clear takeaways
Charts and dashboards built to be read by your whole team — not just someone who knows data tools
Related: AI & Automations
Once you know where the patterns are, automation can act on them — closing the loop between insight and action
What do you wish you could see in your business right now?
Tell us the question. An answer to whether existing data is enough — before any build begins.