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Case Study: Microsoft
Migrated 15,000+ users to a new platform with 65% retention — and rebuilt the entire research ops system in the process.
Enterprise  ·  Research Operations  ·  Platform Migration
65% Retention — while simultaneously removing inactive and unqualified users
30% Increase in recruitment efficiency post-migration
15K+ Users migrated to fully owned infrastructure

The Situation

Microsoft's research team relied on a third-party platform (Alida) to manage a 15,000+ participant panel. The organization needed to migrate to a new in-house system (GreenRoom) — but the risks were significant. Participant data loss, low retention, no standardized migration process, and fragmented researcher workflows all threatened the transition. On top of that, the existing panel was full of dormant and low-quality users, making a direct lift-and-shift migration inefficient from the start.

Most teams would have treated this as a data transfer problem. It wasn't. It was a systems and operations problem.


What I Did
  • 1 Migration strategy and project management. Designed and managed the full migration using Azure DevOps — breaking the project into structured workstreams, identifying cross-functional stakeholders across research, dev, and ops, and coordinating execution across every team involved.
  • 2 Platform implementation and team onboarding. Partnered directly with the developers building GreenRoom. Ensured every researcher had access, training, and full readiness before go-live.
  • 3 Opt-in migration system. Instead of force-migrating users and risking mass drop-off, I designed a permission-based opt-in campaign with incentives, updated screening questions, and re-qualification during migration — filtering out inactive and low-quality participants in the process.
  • 4 Database quality optimization. Removed dormant users with no engagement in the past year. Eliminated unqualified participants. Rebuilt the panel from the ground up with higher-quality, properly categorized users.
  • 5 Workflow and process design. Reworked researcher workflows end-to-end — creating new standardized processes for participant intake, study recruitment, and data management within the new tool.
  • 6 Centralized operations hub. Built a full documentation infrastructure in SharePoint — step-by-step playbooks, SOPs, KPI tracking systems, study tracking metrics, GDPR and compliance docs, vendor guidelines, and internal support resources. Everything in one place.
  • 7 Automation and enablement. Created reusable templates for study setup, built systems to reduce manual work, and implemented performance metric calculators so researchers could execute independently and report consistently.
  • 8 Research awareness and internal communications. Designed and distributed recurring research newsletters highlighting key findings and upcoming initiatives — increasing the visibility and organizational impact of the research function.

The Results
65% participant retention — achieved through opt-in campaign and incentive structure, retaining only high-quality engaged users
30% increase in recruitment efficiency — driven by improved tooling, workflows, and automation reducing manual effort
Transitioned from third-party dependency to fully owned infrastructure — more control, lower long-term cost
Improved participant quality and segmentation, standardized workflows, and a scalable foundation for future research operations
“Most migrations fail because they treat it as a data problem. This was solved as a systems and operations problem — and the difference showed in every metric.”
Case Study: Google
How a fragmented research process became a scalable system, and cut recruitment time in half.
Fortune 10  ·  Enterprise Research Operations  ·  2018–2023
45% Reduction in participant recruitment cycle time
1,000s Participants in centralized database
0 Manual rebuilds per study — down from every single one

The Situation

A high-performing research team at Google was operating on fragmented, entirely manual recruitment workflows. Every researcher ran their own process. Tools were inconsistent. Screening, scheduling, and tracking all lived in different places — or in someone's head. As research demand grew, the cracks widened. Slow recruitment cycles, inconsistent study execution, and redundant manual work were limiting the team's ability to scale.


What I Did
  • 1 Full operational audit. Conducted 1:1 interviews with every researcher. Mapped the end-to-end recruitment workflow and identified every bottleneck, redundancy, and gap.
  • 2 System redesign from the ground up. Rebuilt the entire recruitment process — standardized study planning, defined clear stages from intake through screening, scheduling, and payout, and consolidated fragmented tools into a single unified workflow.
  • 3 Automation and tooling. Built reusable study plan and screener templates. Created a plug-and-play screening system. Automated repeatable steps so researchers could run studies independently without starting from scratch every time.
  • 4 Participant database infrastructure. Built a centralized participant database in Qualtrics, scaled to thousands of participants, with structured intake and tagging systems for reuse across studies.
  • 5 Documentation and enablement. Wrote end-to-end SOPs for every stage of recruitment. Built playbooks, onboarding systems, and training materials so the system lived beyond any single person.
  • 6 Compliance and gratuity systems. Developed standardized gratuity frameworks by region, created payout processes, and partnered with legal and privacy teams to ensure full GDPR and PII compliance with quarterly audit systems in place.

The Results
45% reduction in participant recruitment cycle time — measured before and after system implementation
Researchers no longer rebuilt from scratch for every study — recruitment became repeatable and independently executable
Manual work significantly reduced through automation — time freed for actual research
Improved consistency across all studies — faster turnaround and increased research velocity across the entire team
“By turning a fragmented process into a structured system, recruitment became faster, scalable, and independently executable by any researcher on the team — regardless of their experience level.”
Case Study: CryoMode
Scaled revenue from $6K to $50K+/month by building the operational, marketing, and revenue infrastructure from scratch.
Startup  ·  Service Business  ·  End-to-End Operations Build
$6K → $50K+ Monthly revenue scaled in under 2.5 years
8x Revenue growth driven entirely by systems, not headcount
0 → 1 First hire to full operational team — built, trained, and running independently

The Situation

CryoMode had real demand and a strong service — but no operational infrastructure to support growth. Leads lived in spreadsheets. There was no CRM, no sales pipeline, no marketing attribution, and no documented processes. Customer communication and scheduling were entirely manual. The owner was the bottleneck for everything.

The business wasn't being held back by the market. It was being held back by the absence of systems. I joined as the first employee and built everything from the ground up.


What I Did
  • 1 CRM and revenue system implementation. Implemented HubSpot as the central CRM. Designed a full deal pipeline with custom stages, migrated all existing customer data, and built revenue tracking and forecasting systems so the owner had real visibility for the first time.
  • 2 Lead capture and automation infrastructure. Built automated workflows using Zapier connecting the website, landing pages, and ad campaigns directly into the CRM — so every inbound inquiry became a qualified deal automatically, with no manual data entry.
  • 3 Marketing engine and attribution. Managed and scaled Google Ads and Meta Ads across five service lines: automotive, industrial, food processing, fire remediation, and laser cleaning. Implemented full UTM tracking with attribution down to the individual ad level so every dollar spent was accountable.
  • 4 Landing pages and conversion optimization. Designed and launched high-converting landing pages aligned to each campaign and service line, improving conversion rates through targeted messaging and continuous testing.
  • 5 Call tracking and customer intake. Implemented CallRail for call attribution, tracking whether leads came from paid ads or organic search. Integrated a phone system across the team so no lead fell through the cracks.
  • 6 End-to-end customer journey systems. Built complete workflows for inquiry handling, scheduling, project updates, payments, and review collection. Automated email sequences and appointment reminders. Centralized all customer data including UTM source, project scope, and full communication history.
  • 7 Reporting and continuous optimization. Created monthly reporting systems tracking cost per conversion, CPC, CTR, impressions, and conversion rates. Used the data to continuously optimize campaigns and cut wasted spend.
  • 8 Operations and process infrastructure. Documented all internal processes and built SOPs for shop operations, mobile job execution, inventory and vendor management, and payment processing through QuickBooks.
  • 9 Hiring and team enablement. Hired and onboarded three employees. Built training systems and documentation so team members could operate independently at a high level without the owner involved in every task.
  • 10 Financial operations. Worked directly with the owner on revenue tracking, forecasting, budgeting, and cost optimization — building the financial visibility that informed every growth decision.

The Results
Revenue scaled from $6K–$8K/month to $50K+/month — 8x growth driven by systems, not just effort
Built a fully functional CRM and sales pipeline where none existed — complete visibility into every deal and lead
Created a predictable, trackable lead generation engine with attribution down to the individual ad level
Eliminated manual bottlenecks through automation — the business now scales without the owner being the single point of failure
Hired, trained, and enabled a team that operates independently — growth no longer dependent on any one person
Established a system that continues to support growth — the infrastructure built here is still running today
“Growth didn’t come from more effort. It came from building the systems that allowed the business to scale efficiently. The same operational thinking I applied at Google and Microsoft — applied to a two-person startup with no safety net.”