Proudly based in Saint John, New Brunswick, Canada
Your Strategic Business Data & Analytics Partner
What We Do
Save Time on Reporting
Track Business Performance
Forecast & Plan Ahead
Understand Your Customers
Fix Messy, Unreliable Data
Integrate & Automate Everything
How We Do It
The Data Seed Lifecycle
1. Discovery → Define the Problem & Goals
What are we trying to solve?
Every great solution starts with the right question. In this phase, we:
- Define success metrics and expected outcomes.
- Identify key business challenges and opportunities.
- Understand what decisions need to be made and by whom.
2. Collection → Gather & Organize the Right Data
What information do we need to answer this question?
Now that we’ve defined the problem, we need the right data. In this phase, we:
- Ensure data quality and completeness.
- Identify data sources (existing databases, CRM, web analytics, surveys, etc.).
- Set up data pipelines to collect and store clean, structured data.
3. Analysis → Find Patterns, Insights & Opportunities
What story does the data tell us?
Once we have the right data, we uncover actionable insights. In this phase, we:
- Use statistical and AI-driven methods to validate hypotheses.
- Explore trends, anomalies, and relationships in the data.
- Segment and filter data for deeper insights.
4. Execution → Build Solutions & Automate Processes
How do we turn insights into action?
Insights mean nothing without execution. In this phase, we:
- Automate repetitive tasks and reporting to save time.
- Design solutions (automated dashboards, reports, predictive models).
- Build scalable workflows to integrate insights into daily operations.
5. Delivery → Enable Decision-Makers with Actionable Data
How do we make data accessible and useful?
Now it’s time to empower the right people with the right information. In this phase, we:
- Train teams to use and understand the insights effectively.
- Deliver insights via dashboards, scheduled reports, or alerts.
- Ensure the data is accessible in a format that matches team workflows (Google Sheets, PDFs, Slack alerts, etc.)
6. Evolution → Iterate & Scale for Long-Term Growth
How do we continuously improve?
No data solution is static—businesses evolve, and so should their data strategies. In this phase, we:
- Transition ownership to internal teams over time (self-service analytics).
- Monitor performance and refine models and dashboards.
- Add new data sources and automation as the business scales.
Data Seed 