Use case
We read every review, survey and comment from your customers, classify them by topic and sentiment and alert you to what is changing. Knowing what to improve no longer depends on reading everything.
Sources
Customer opinion is spread across many channels. We bring them together and analyse them as a whole.
Examples
Google review (3 stars)
“The order arrived two days late and nobody let me know, but when I called they sorted it out straight away and were very friendly.”
Analysis
Suggested reply: thank them, apologise for the delay and explain the automatic notice that is being switched on.
Reply ready to review
Satisfaction survey
“Good product, but the assembly instructions are a mess. It took me an hour to understand step 4.”
Analysis
Improvement proposal sent to product
412 opinions from October
“Reviews, surveys and customer emails from every channel over the last month.”
Monthly summary
Report sent to leadership
How it works
Connection to the platforms or regular exports.
4 sources · every night
Topics, sentiment per topic, language and urgency.
Delivery · negative
Comparison with previous weeks and alerts.
Delivery complaints ×2
Human review
Reviews suggested replies and decides on improvements.
12 replies approved
Before and after
Today
With AI
Visual guide · Customer feedback analysis
What your
customers say
on one map
Hundreds of comments spread across many channels. Grouped by topic, you can see at a glance what annoys, what pleases and what is starting to grow.
01 · A month of feedback
Size: number of mentions. Colour: sentiment.
02 · One review, taken apart
3 out of 5 stars
The order arrived two days late and nobody told me, but when I called they sorted it straight away and were very kind.
Suggested reply
Thank you for letting us know. We are sorry about the delay and that we did not tell you: we are switching on an automatic notice when an order is late. We are glad the team sorted it quickly.
A person checks it before it is posted
03 · Alerts
Each week is compared with the previous ones. A problem shows up when it starts, not when complaints have piled up.
04 · With judgement
Nothing is posted
unchecked
Replies
As well as counting topics, AI can suggest a reply to each review. A member of the team checks it and posts it.
Method
We bring together reviews, surveys and comments from recent months to get a first picture.
Initial report on topics and sentiment
We define with you the topics that matter (delivery, product, service, price…) and validate the classification.
Classification validated by the team
We schedule the regular analysis, alerts and suggested replies in your tools.
Dashboard, alerts and suggested replies
We add AI to the tools your business already uses to automate tasks, search information and connect data without having to change everything.
Reply sooner and better, without losing the human touch.
Draw conclusions from your data with AI, even if you are not a data scientist.
Tell us where you receive opinions and how many a month. With a sample we can show you which topics come up.
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