Analytics products that turn dense data into weekly decisions.
We craft data experiences that balance clarity for new users with power for analysts—grounded in research, design, and engineering.
+31%
Weekly active users
Data intelligence platform increased retention post redesign.
5 min
Time to insight
Guided stories reduced executive prep work from 30 minutes.
-40%
Data quality incidents
Instrumentation and monitoring caught issues before release.
Noise over signal
Dashboards expose every metric without storytelling or prioritisation.
Impact: Guided narratives highlight what changed and why it matters.
Onboarding gaps
Users lack education on data lineage, definitions, and key workflows.
Impact: Contextual onboarding increases activation and confidence.
Power-user divergence
Analysts need control without overwhelming casual stakeholders.
Impact: Configurable workbenches keep advanced use cases within guardrails.
Capabilities for analytics and intelligence teams
Designers, engineers, and strategists who understand data platforms end-to-end.
Experience design
Tell clear data stories while keeping advanced workflows within reach.
- Progressive disclosure that guides users from overview to drill-down.
- Notebook, dashboard, and alert surfaces with a shared design language.
- Education layers explaining metric lineage, filters, and caveats.
Product engineering
Pair with your team to align semantic layers, performance, and observability.
- Composable data visualisation components with accessibility baked in.
- Query performance tuning, caching, and pre-computation strategies.
- Event tracking plans, instrumentation, and monitoring dashboards.
Venture advisory
Align stakeholders on the questions, KPIs, and feedback loops that matter.
- Metric taxonomy and governance workshops with business owners.
- Adoption and behaviour analytics with experiment readouts.
- Change management plans to embed analytics into weekly rituals.
Analytics product engagement cadence
Six-week partnership from discovery to adoption mechanics.
Phase 1
Insight discovery
Map decision moments and data sources across personas.
Key outputs
- Stakeholder interviews with executives, analysts, and operators.
- Decision and workflow mapping with north-star success metrics.
- Data quality and instrumentation audit.
Phase 2
Experience narratives
Design dashboards, notebooks, and alert flows with prototypes.
Key outputs
- Narrative dashboard prototypes tested with each persona.
- Content strategy for annotations, tooltips, and explanations.
- Usage research synthesis with prioritised opportunities.
Phase 3
Build & instrumentation
Engineer visualisations, interactions, and observability.
Key outputs
- Component library for charts, tables, and filters.
- Instrumentation plan aligned with analytics tooling.
- QA checklist covering performance, accuracy, and accessibility.
Phase 4
Launch & adoption loop
Enable stakeholders and set up continuous measurement.
Key outputs
- Adoption playbook with training materials and office-hour plans.
- Executive briefings and read-out templates.
- Experiment backlog for iterative improvements.
Analytics accelerators
Templates, systems, and rituals that keep insights flowing.
Metric taxonomy
Shared definitions with ownership and calculation notes.
Dashboard design kit
Figma + code components mapped to states and accessibility rules.
Data storytelling templates
Narrative structures for executive and team readouts.
Usage instrumentation plan
Tracking schemes aligned with Amplitude, Mixpanel, or Segment.
Experiment readout pack
Templates for hypothesis, results, and next steps.
Related analytics launches
See how we increased adoption and trust.
Make your data product indispensable.
Partner with strategists, designers, and engineers who ship clarity and adoption.