Case Study

The Challenge

Orbio World operates a portfolio of health, wellness, and consumer product brands. Each brand has its own media buying operation, its own subscription model, its own fulfilment pipeline, and its own unit economics. They sell across their own online checkout, Amazon, TikTok Shop, Walmart, Allegro, eBay, telemarketing, and cash-on-delivery networks in over 20 countries.

That creates an enormous surface area of data. Every brand manager needs to know their daily revenue, profitability, and ad performance. Every media buyer needs creative-level analysis and CPA benchmarks. The operations team needs to catch payment approval drops, chargeback spikes, and fraud patterns before they cause damage. Finance needs COD cash collection estimates and margin tracking at the brand and country level. Leadership needs all of it, every morning, without asking anyone.

The traditional approach was centralised BI: a small analytics team building and maintaining dashboards in tools like Tableau. That worked when the company was smaller. But with 12+ active brands, 20+ countries, and dozens of team members who each need slightly different views of the data, the queue for new reports grew faster than the team could deliver.

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The Solution

Orbio connected their central analytics data warehouse to Milo. Then something happened that does not typically happen with BI tools: the users started building for themselves.

Brand managers built their own daily performance dashboards. Not one generic dashboard, but brand-specific views with the exact metrics that matter for each product: subscription renewal rates for Kinzeno, upsell basket composition for Matsato, COD approval rates for Akusoli, creative angle performance for Ondrela. Each brand got exactly the analytics it needed because the person closest to the brand was the one building it.

Media buyers built Facebook Ads daily performance reviews, creative analysis dashboards, and a statistical model measuring the halo effect of Facebook spending on Amazon brand search revenue. That last one includes Granger causality testing, negative controls, and confidence intervals. It was built through conversation, not code.

Operations built a daily pulse dashboard covering payment approval health, refunds, chargebacks, COD logistics, and subscription trends. They layered on automated anomaly detection that runs twice a day (morning and midday) and alerts the team via email and Slack when something breaks pattern.

Finance built COD estimation models (daily and weekly) using historical approval rates and live lead data. They built GP4 profitability analyzers that break down revenue and cost components across every business line. They built a brand lifecycle risk monitor that flags products trending toward end-of-life based on order velocity thresholds.

Automated Reporting at Scale

This is where Orbio's usage is unlike any other customer. They have set up 166 automated reports. That includes:

• Daily performance reports for every major brand (sent every morning before the team starts work)

• Weekly and monthly brand summaries

• Morning and midday anomaly detection checks

• Revenue drop alerts (triggered when any brand falls more than 10% vs the prior day)

• Chargeback and fraud alerts (flagging suspicious patterns in real-time)

• COD lead trend alerts (flagging when daily lead volume shifts significantly)

• Refund monitoring (pending refunds, invalid refunds, unresolved chargebacks)

• Subscription dunning monitors and churn rate reports

• Affiliate refund tracking

• Shipping cost alerts

Most of these go to email. Many also go to Slack, where brand managers and ops leads get updates in their working channels without switching context.

The Scale

Within 10 months of joining, Orbio's usage looks like this:

• 48 active users across the company

• 91 live dashboards

• 166 automated reports

• 7 custom apps (including vendor assessment tools, max CPL calculators, and GP4 analyzers)

• 4,764 total conversation threads

• Usage grew from single digits in the first month to over 2,700 interactions per month

The team accesses Milo through three channels: web for building and exploring, email for receiving automated reports, and Slack for quick questions and alerts during the workday.

What Makes This Different

Most companies adopt an analytics tool and use it for a handful of KPI dashboards. Orbio adopted Milo and every department built their own analytics stack on top of it.

Media buyers are running statistical correlation analysis. Operations is catching payment anomalies before they hit the P&L. Brand managers are tracking subscription cohort lifetime value by billing cycle. Finance is estimating COD cash collection using historical approval rate models. All of this was built by the people who use it, not by a central BI team building reports for them.

The result is not just faster reporting. It is a fundamentally different relationship with data. When the person who needs the answer is the same person who builds the analysis, the right questions get asked and the right dashboards get built. Nobody waits in a queue. Nobody gets a report that almost answers their question but not quite.