Data-Driven Persona Development
Applying Quantitative Research and Sociological Methods to Define Core Partner Profiles
Insider 2025
Project Context
Goal
Understand Onsite partners—their behaviors, needs, and key interaction points—to optimize onboarding, self-service tools, and support.
Challenge
Integrate statistical data and sociological methods to create representative partner profiles that would directly inform product decisions.
Meet the Research Team
Quantitative Research by Julia (me)
Designing and executing the quantitative research plan.
Segmenting partners by region, company level, and engagement lifecycle.
Identifying key behavioral patterns and product usage trends.
Synthesizing findings into actionable insights to inform persona development.
This phase laid the empirical foundation for further qualitative exploration and validated the statistical representativeness of our personas.
Qualitative Validation by Sıla
After the quantitative framework was established, Researcher Sıla led the qualitative research phase.
Her responsibilities included:
Conducting in-depth interviews with partners to explore motivations, behaviors, and contextual needs.
Identifying patterns and insights that complemented the quantitative findings.
Translating interview data into actionable insights for refining proto-personas.
This mixed-methods collaboration ensured that our personas were both statistically grounded and human-centered, bridging sociological research with product design strategy.
Quantitative Research Steps
Step 1: Data Collection via Power BI
Ensured data validity and representativeness by applying sociological sampling principles.
Standardized raw datasets to enable cross-segment comparison and trend visualization.
Prepared dashboards in Power BI to support exploratory data analysis and insights mapping.
Step 2: Partner Segmentation
By company level: Enterprise / Semi-Enterprise / Long-tail
By status: Retained / Onboarding / Churn
By partnership duration: <1 year / 1–2 years / >3 years
Step 3: Identification of Key Products
Region: Geographic distribution of product adoption.
Sector: Industries most engaged with Onsite tools.
Partner Status: Variation in activity among Retained, Onboarding, and Churned partners.
Company Level: Comparative product engagement across Enterprise, Semi-Enterprise, and Long-tail.
Step 4: Statistical Interpretation
Defined the core partner base as the foundation for proto-persona creation.
Combined quantitative clusters with emerging qualitative themes to build pre-personas.
Validated personas through stakeholder reviews and iterative feedback loops.
Planning and Analysis
This project focuses on building a clear plan for collaborating with onsite partners. We'll outline what needs to be done, who is responsible, and when key tasks should be completed.
Project duration: 2 sprints
Distribution of Partners by Key Metrics
From Data to Decisions — Bringing Our Customers to Life
It began with numbers. Thousands of data points flowing from Power BI — regions, sectors, partnership statuses, durations — all painting a broad, statistical picture. But behind every chart and percentage, there was something more: real people, real stories, and real relationships.
Through a structured, quantitative approach, we segmented partners by company level, status, and lifecycle. Then, by combining statistical analysis with the human perspective of our Customer Success Managers, patterns began to form.
The data started to speak.
These personas are more than profiles — they are a shared language across teams.
They guide how we design communication, structure support, and prioritize innovation.
They help us empathize with data and make strategic decisions with purpose.
As we move forward, these personas will continue to evolve — informed by new insights, real feedback, and the changing dynamics of our global network.
Because every dataset hides a story, and every story brings us closer to understanding the people behind the numbers.
