Nobody planned for this to be the process.
At some point, someone decided that survey comments should be reviewed before the weekly report. Then the volume grew. Then it became a task squeezed in by whoever happened to have five minutes. Then it stopped happening consistently.
Sound familiar?
Manual survey review starts with good intentions - it's just an approach that doesn't scale. And for most service desks, the gap between the feedback that's collected and the feedback that's actually read is bigger than anyone wants to admit.
The volume problem
Busy service desks can generate hundreds or thousands of tickets each month. A lot of tickets means a lot of surveys being sent. Even with a modest response rate, that can create a significant volume of feedback to review.
Even at moderate volumes, reviewing every comment individually takes time most teams don't have. At higher volumes, it's simply not realistic. So a process emerges that looks like analysis but isn't really: scan the low scores, skim the comments that seem angry, ignore the rest.
The problem with that approach is the same problem you'd have skimming a spreadsheet - you see what stands out, but you miss the patterns.
A single complaint about unclear communication may be an isolated issue. Ten similar comments across two weeks indicate a pattern. The same might apply to feedback about ticket ownership, slow handovers between teams, poor major incident updates or issues being closed before the user feels they have been resolved. If you're only reading the loudest responses, you may miss the quieter comments pointing to the same recurring problem.
The consistency problem
Even when survey review does happen, it rarely happens the same way twice.
One person reads comments looking for praise or complaints. Another filters for anything below three stars. A third reads everything but only escalates what seems urgent today. None of these approaches is necessarily wrong, but they are not comparable - and inconsistent analysis leads to inconsistent action.
If your insight changes depending on who reviewed the surveys that week, it's not really insight. It's interpretation, which is useful but unreliable at scale.
The timing problem
Post-resolution surveys naturally arrive after a ticket has been closed. The problem is not that the ticket is closed - it is the delay between receiving the feedback and reviewing it. By that point, the analyst may have moved on, and the same issue may already have affected several other users.
Feedback becomes less actionable over time. Spotting that a cluster of users felt poorly informed during a major incident response is useful on day two, when communications can still be improved. By day fourteen, the feedback may still inform continual improvement, but the immediate opportunity to act has passed.
Manual review, even when it happens, tends to be retrospective. The insight arrives after the window to act on it has passed.
What actually needs to happen
Survey responses need to be analysed consistently, comprehensively and close to the moment they're received - not when someone gets around to it.
That means every response, not just the low-scoring ones. Every comment, not just the ones that sound urgent. Feedback analysed as it arrives, not just when the quarterly review is coming up.
That level of consistency isn't achievable manually at scale, which is why it needs to happen automatically.
Automation does not replace the judgement or experience of the service desk team. It provides a complete and consistent view of the feedback, helping managers identify where attention is needed and decide what action to take.
Survey Sentiment, powered by Solvyr®, analyses 100% of survey responses as they come in - identifying the sentiment expressed in each reply, flagging unusual or strongly negative feedback that may require follow-up, and tracking how user sentiment changes over time. In the time it takes to manually review a handful of comments, it's already processed them all.
Every response considered. A consistent approach. No backlog of feedback you never quite got around to reviewing.
See Survey Sentiment in action →