I will analyze saas onboarding feedback and prioritize improvement tests
Japan Market Research and Localization Specialist
About this Gig
Deciding what to improve in your SaaS onboarding? Turn scattered customer comments into a clear next-test plan.
I analyze one buyer-supplied English feedback dataset for one SaaS product and one onboarding decision. Every package includes:
- A PDF decision brief and editable TXT evidence report
- Theme counts with clear denominators and comment IDs
- Supporting quotes, positive contrasts and unclear feedback
- Up to 3 prioritized improvement tests, with reasons and uncertainties
Choose up to 50, 150 or 300 comments, within 5,000, 15,000 or 30,000 source words. Both limits apply to the submitted dataset. Supply a redacted TXT file; no account access is needed.
This is AI-assisted qualitative analysis with separate QA. Counts describe your supplied comments, not your whole customer base. No scraping, interviews, integrations, causal churn analysis or guaranteed revenue impact is included. The sample is fictional, not client work.
Please message me before ordering to confirm data suitability, scope and timing.
Language:
English
Research method:
Qualitative
Other Market Research Services I Offer
FAQ
Who is this for?
SaaS founders, product managers and customer success teams deciding what to improve in onboarding. You already have English customer feedback and need a reviewed, one-off decision brief rather than a new analytics system.
What will I receive?
A PDF decision brief and an editable plain-text evidence report with a theme codebook, counts, comment IDs, quotes, positive contrasts, exclusions and up to three next-test recommendations. All packages use the same method; the data limits differ.
What data can I send?
Send one redacted UTF-8 TXT file with one feedback entry per block, separated by a blank line. Optional IDs, dates and source labels help, but I can assign IDs. One comment is one submitted feedback entry. Both the comment and source-word limits apply before exclusions.
What is outside the scope?
Feedback collection, scraping, account access, audio transcription, translation, interviews, dashboards, software implementation and statistical or causal churn analysis are excluded. One product, one dataset and one onboarding decision are included.
What if the evidence is weak or contradictory?
I retain relevant positive and contradictory feedback and explain uncertainty. Counts refer only to the supplied comments, not unique customers or population prevalence. If the evidence cannot support three tests, I recommend fewer and explain what is missing.
Do you use AI?
Yes. AI assists coding, synthesis and drafting; factual counts and quotes are checked against the supplied dataset, followed by a separate QA review of the English deliverables. Do not order if your policy prohibits AI-assisted processing.
How should I handle confidential information?
Only share data you are permitted to provide for this AI-assisted work. Remove names, emails, account identifiers, credentials and sensitive personal information before sharing. Do not send health, payment-card or other highly sensitive records.
What does a revision cover?
One consolidated clarification or correction round on the agreed dataset and decision; Premium includes two. New comments, products, languages or decision questions are scope changes. Our factual, counting or source-record errors are corrected without charge and do not use your revision allowance.
Is the sample client work?
No. TeamRelay and all sample comments are fictional. The sample demonstrates the analysis method and file quality; its counts and recommendations are illustrative, not customer results.
Why pay instead of using an AI summary tool?
This service delivers a finished brief for one decision, with reviewed comment-level coding, counterevidence and an explained priority order. A self-service tool may be a better fit if you prefer to do the analysis yourself or need a continuous feedback platform.

