How an International SaaS Platform Scaled Critical User Research in Weeks—Not Months

The Leadership Challenge

A global SaaS platform with tens of millions of monthly users faced a familiar but urgent problem:

They needed to make high-stakes product and experience decisions—but lacked a clear understanding of how their most engaged users deepen their engagement over time.

Leadership needed answers to questions like:

  • What drives users to become highly engaged?
  • Where do they get stuck or experience churn?
  • What capabilities or experiences accelerate deeper adoption?

These insights were critical to:

  • Informing product roadmap priorities
  • Improving user retention and engagement
  • Identifying opportunities to scale high-value behaviors

The team had already conducted an initial round of qualitative research. But there was a problem.

The insights were deep—but narrow.

The sample skewed heavily toward English-speaking users, and leadership lacked confidence that findings would generalize globally. Expanding the study using traditional methods would require:

  • Multilingual researchers
  • Translation and transcription workflows
  • Complex scheduling across time zones
  • Significant additional budget and time

Under mounting decision pressure, the organization needed a way to scale insight quickly—without sacrificing quality.

The Approach

The team partnered with a flexible research staffing model (via the UXr Guild) to extend their existing work—without restarting from scratch.

Rather than replacing traditional research, the approach layered methods strategically:

1. Establish a Deep Qualitative Foundation

  • 24 in-depth remote interviews
  • 6 in-person ethnographic sessions

This phase focused on understanding:

  • User journeys over time
  • Behavioral shifts and skill development
  • Emotional and identity-driven motivations
  • Barriers to continued engagement

This created a strong, story-rich baseline—but still lacked global coverage and nuance.

2. Extend Reach Globally with AI-Moderated Interviews

To scale quickly, the team leveraged Outset.ai to deploy AI-moderated interviews across:

  • 15 countries
  • 7 languages (including Spanish, Portuguese, French, Japanese, Korean, and Tagalog)

In just one week, they conducted 43 additional interviews—something that would have taken months using traditional methods.

This allowed the team to:

  • Reach underrepresented audiences
  • Avoid heavy translation overhead
  • Maintain consistency in interview structure
  • Gather rich, qualitative input at scale

Participants responded positively to the experience, with the majority describing it as:

  • Engaging
  • Clear and structured
  • Thoughtful and meaningful

Even without a live interviewer, participants shared detailed experiences and perspectives, validating the approach as a viable extension of traditional research methods.

3. Validate and Quantify with Survey Data

To complement qualitative insights, the team also deployed a large-scale survey to this highly invested user segment.

This helped:

  • Measure the prevalence of key behaviors and pain points
  • Validate patterns observed in interviews
  • Identify which opportunities would have the greatest impact

The combination of qualitative depth + quantitative validation gave leadership both:

  • Confidence in what was happening
  • Clarity on how widespread it was

The Outcomes

1. Broader, More Representative Insight

The organization moved from a narrow, English-heavy sample to a globally diverse dataset, capturing perspectives across regions, languages, and experience levels.

This reduced the risk of making decisions based on incomplete or biased input.

2. Faster Time to Insight

  • 43 international interviews completed in 1 week
  • Avoided an estimated 6–8 weeks of additional fieldwork

Leadership was able to move forward with confidence—without delaying key decisions.

3. Lower Operational Burden

By avoiding a traditional global research rollout, the team significantly reduced:

  • Coordination complexity
  • Translation overhead
  • Recruiting friction

This enabled the team to scale research efficiently—without a proportional increase in cost.

4. Strong Validation of Core Insights

The expanded dataset confirmed several critical patterns:

  • High engagement is driven by identity, meaning, and personal relevance
  • Advanced users follow a repeatable loop of discovery, evaluation, and validation
  • Data quality and trust remain persistent friction points
  • Organization and workflow management are key unmet needs

Importantly, the global sample also revealed region-specific constraints, helping teams identify where localization or infrastructure improvements were needed.

5. Increased Leadership Confidence

Perhaps most importantly, leadership gained confidence that:

  • The insights were not isolated to a single audience
  • The patterns held across cultures and regions
  • The resulting decisions would scale globally

Key Takeaway

For this organization, the goal wasn’t just to do more research—it was to reduce risk in critical decisions under time pressure.

By combining:

  • Deep qualitative research
  • Scalable AI-moderated interviews
  • Targeted survey validation

They were able to move from partial insight to confident direction—quickly and efficiently.

This hybrid approach demonstrates how leadership teams can leverage flexible research partners like the UX Research Guild to arrive at clear, confident decisions when the stakes are highest.