Strawberry can collect authorised feedback threads, survey responses, call notes, and review pages into a weekly summary with links back to the original words. The point is not to declare a roadmap from a few loud messages; it is to show the pattern, the exceptions, and the decision each one may require.
01
Bring feedback sources together before you count themes.
A support ticket, an onboarding call, a churn note, and a survey answer may describe the same obstacle in different language. Collect the approved sources into one review period before deciding whether a pattern exists.
02
Group meaning carefully enough that a theme remains checkable.
“Users hate onboarding” is not a theme.
A checkable theme names the moment, the obstacle, and the observed consequence, such as “new admins cannot find the invitation setting during setup.”
Strawberry can propose groups and show the excerpts within each group, leaving unclear items outside rather than forcing them into a convenient label.
03
Separate the evidence from the product decision.
Repeated requests may indicate a usability problem, a documentation gap, a missing capability, or a sales-expectation issue. The report should describe the evidence and propose an investigation, not claim it already knows the fix.
04
Give the weekly ritual a stable evidence standard.
Save the accepted source scope, theme format, and escalation thresholds as a voice-of-customer skill. A weekly routine can assemble the report before the product review, while owners decide whether a theme requires research, a fix, documentation, or no action.
The same routine should report source gaps, because a quiet channel is not evidence of customer satisfaction.
AI can compile authorised feedback sources, group similar evidence, and prepare a linked weekly summary for team review.
Group by the customer task, the obstacle encountered, and the consequence observed, then retain the original excerpts within each theme.
No. Prioritisation also depends on customer impact, affected segment, strategic importance, severity, and whether the evidence identifies the underlying problem.
It can identify proposed themes across approved ticket evidence, while product and support owners validate the grouping and priority.
Include sources reviewed, linked themes, key excerpts, affected customer task, severity signals, open questions, owners, and any source gaps.