Reads the whole comment
One review can praise the food and complain about the wait. Each comment can carry several themes, each with its own sentiment, instead of one blended score.
Group
Themes formed from what customers mean, not the words they happen to use.
"Still waiting for my money", "refund pending" and "paise wapas kab aayenge" are the same problem. Kingsclap reads each comment in full, groups it with comments that mean the same thing, and names the theme in plain language your team can act on.
ReviewRefund promised in 5-7 days. It is day 15.
TicketReturn picked up, money still not credited.
SurveyPaise wapas kab aayenge? Two weeks ho gaye. Hindi + English
Refund delay 38Money not credited 23Refund wait time 61
Merge Split Rename 61 comments
Theme Detection
What it covers
Mixed-language feedback
Hinglish and other code-mixed comments are read as written, without asking customers to pick a language.
Merge and split
Combine two themes that are really one, or split a broad theme like "delivery" into late, damaged and wrong address.
Rename in your words
Call it "Counter queue" instead of "Wait time" if that is what your floor managers say. Names stick across months.
Theme hierarchy
Keep broad parents for leadership views and specific children for the teams who fix things.
Every theme opens to its comments
Click any count and read the exact comments behind it, with source, date and location. If a theme looks wrong, you can see why in seconds and move comments out.
Workflow
How a theme is formed
- 01
Understand
Each comment is read by a language model that extracts the issues and praise it contains.
- 02
Cluster
Similar issues are grouped across sources, so a review and a ticket about the same problem land together.
- 03
Name
Each group gets a short, specific name and a one-line description of what belongs in it.
- 04
Learn from edits
When you merge, split, rename or move comments, new feedback follows your structure.
In detail
Honest limits
We would rather tell you where the model is weaker than have you find out from a wrong chart.
Language coverage
English, Hindi and Hinglish are strongest. Other Indian languages in native script work well for clear complaints and less well for slang. We confirm coverage on your data before you commit.
Sarcasm and one-word reviews
"Great, late again" is usually caught. A lone "ok" with three stars carries almost no signal and is counted, not themed.
Small volumes
Themes with fewer than a handful of comments are shown but marked low confidence, so one angry customer does not look like a trend.
Human review
New themes appear as suggestions until someone on your team accepts them.
FAQ
Questions teams ask
Do we have to set up keywords or rules?
No. Themes are found from the comments themselves. You can add rules later if you want certain terms always routed to a theme.
Will themes change every month?
No. Accepted themes stay stable so trends are comparable. New issues appear as new suggested themes instead of reshuffling old ones.
Can one comment belong to more than one theme?
Yes. A comment about late delivery and a damaged box is counted in both, with the right sentiment for each.
Is our data used to train shared models?
No. Your comments are used to analyse your account only.
Insight Engine
Works together with
Next step
Your fix-first list is already sitting in last month’s feedback.
Send us an export of reviews, survey answers or tickets. On the demo we sort it live and show you what we would fix first, with the comments behind every theme.