Most startups have data. Very few have answers.
Your dashboard shows you what happened last week. But when a Series A investor asks about your 6-month net revenue retention, payback period by acquisition channel, or your leading indicators of churn, the answer is a spreadsheet, a gut feel, or silence.
That gap doesn't just cost you in fundraising. It costs you in every decision you make while building. We fix the infrastructure that produces real answers, not just charts.
What we offer.
We work across the full data stack — from raw pipeline consolidation to statistical modelling to investor-ready narrative. Every engagement produces infrastructure your team can own.
We consolidate fragmented data sources into a single source of truth. We build scalable dbt pipelines that enforce data integrity across every dataset, eliminating manual correction cycles and reducing time-to-insight by up to 40%.
We architect LookML-based metrics layers that standardise KPI definitions across your stack, eliminate metric sprawl, and enable self-serve analytics for product and commercial teams — without creating an engineering bottleneck every time someone has a new question.
K-means segmentation, Z-score models, regression analysis, pricing models, NPS modelling — we build the analytical layer that surfaces the signals your dashboards miss. We've used this to identify upgrade drivers that boosted conversion by 75% and to unlock $6M in incremental revenue from untapped customer datasets.
Cohort retention curves, net revenue retention, LTV/CAC, payback period by acquisition channel — structured for the questions investors ask in Series A diligence. We've directly enabled fundraises through the analytical layer of data rooms, most recently contributing to a £750K raise.
SQL-driven customer dataset mining combined with qualitative research — surveys, interviews, NPS analysis — translated into prioritised recommendations for C-suite. We've run studies at 800+ survey scale that produced investor-ready insights reports and drove measurable NPS improvement of 7+ points.
We distil data signals into prioritised KPIs for weekly executive reporting. Real-time dashboards adopted by senior leadership across multi-market operations — reducing cross-functional reporting overhead by 30%+ and cutting leadership decision cycles. Your data stack should inform decisions, not generate more meetings.