Fractional BI is an ongoing business intelligence function, scaled to your needs. We connect your data, define the numbers, and keep the answers coming.
Your CRM knows the pipeline. Your core operations know the work. Finance knows the margin. But no single system tells the whole story.
We build repeatable connections into a shared data foundation. A warehouse layer or read-replica can retain source data; cleaning, validation, and modeling make it useful for reporting.
We turn connected data into agreed KPIs, dependable dashboards, and answers to new questions. Then we maintain the pipelines and evolve reporting as your business changes.
Documented pipelines and consistent definitions, with architecture suited to your security and hosting needs.
Repeatable refreshes and useful dashboards that reduce the recurring work of assembling reports.
A partner to investigate changes, prioritize new questions, and keep your BI environment useful.
Most companies track business revenue in one place and app events in another. We instrument PostHog alongside your warehouse so you see the complete story.
Pinpoint the exact step in sign-up, BVN/KYC verification, or payment checkout where prospective users abandon. Filter conversion funnels by device type, traffic acquisition channel, or user tier to fix real conversion leaks.
See exactly what happened before a user dropped off or submitted a support ticket. Diagnose rage clicks, broken form validations, and confusing mobile web states with privacy-conscious session recordings.
Product telemetry shouldn't live trapped in a silo. We configure automated event exports into your PostgreSQL or central warehouse, letting you query user events directly against financial accounts and operational records in Metabase.
Track true day-1, day-7, and day-30 retention curves. Roll out changes incrementally with targeted feature flags to safely test new pricing structures, checkout designs, or features on select customer segments.
Read our practical guide on instrumenting PostHog, finding onboarding drop-offs, and joining event streams with your warehouse.
The right engagement depends on how often you need help and who will own the reporting after it is built. Fractional BI provides recurring capacity; a dashboard project focuses on a defined deliverable; an internal role puts day-to-day ownership inside your team.
| Option | When it can fit | Plan for |
|---|---|---|
| Dashboard project | You have a defined reporting question, known sources, and a clear deliverable. | Who maintains connections, updates definitions, and handles new requests after handover. |
| Fractional BI partner | You need ongoing reporting and analytics help at an agreed scope without filling a full-time role. | Priorities, available capacity, response expectations, documentation, and review cadence. |
| Internal BI hire | You have sustained work and want dedicated day-to-day ownership within the organization. | Recruiting, management, specialist support, and coverage when the role is unavailable. |
Suppose a monthly report shows ₦100,000,000 in recognized revenue and ₦65,000,000 in agreed direct costs. Gross profit is ₦35,000,000, and gross margin is 35%: gross profit divided by revenue. These are sample figures, not client results.
A chart alone cannot explain whether the two inputs cover the same period, jobs, and cost categories. Before building the dashboard, define what belongs in the measure and how someone can investigate a change.
Document which revenue and direct-cost records are included, the reporting period, and how credits or adjustments are handled. Keep gross margin distinct from net profit.
Match the relevant jobs or accounts, check missing and duplicate records, and compare totals with the agreed source reports. Flag incomplete data before interpreting the result.
Show the trend and the contributing jobs or categories. Include the last refresh time and an owner for questions so a change in margin can lead to a useful investigation.
This is the connection between data integration, KPI design, and decision support: define the question, make the inputs comparable, then present the result with enough context to act.
Start with one important report or decision. The number of systems, data quality, access requirements, refresh frequency, and level of ongoing support determine the work. Your existing database may be enough; a new data lake is not a prerequisite.
Tell us which decision your current reports cannot support.
Book a Scoping Call