Retail · multi-site networks · hospitality
Customer reviews handled the same day, in your voice
Reviews land continuously, across several platforms and several sites. You reply when you remember, often too late, sometimes too curtly. And the one-star review that actually needed handling went unnoticed.
- Today
- 21 min / review
- Time to production
- 3 to 5 weeks
- What stays human
- You keep control of every publication. The goal is not to reply automatically: it is to never again leave a review unanswered for lack of time.
Before / after
The same process, run twice
On the left, what it costs today. On the right, the pipeline played step by step, with the data that actually moves from one step to the next.
Today · by hand
21 minutes per review
- Do the rounds of the platforms3 min
- Find the visit or the order3 min
- Write a measured, fair reply10 min
- Publish on the right listing2 min
- Tell the site manager3 min
A working assumption, not a measurement taken at your company. You’ll adjust these figures below.
The review is detected
< 5 min after postingEvery platform, every location, continuously.
New review · Geneva-Cornavin
★★☆☆☆ · 4 minutes ago · Sofia M. “Staff were fine but 35 minutes of waiting on a Tuesday lunchtime with the room half empty. Shame, because the food is genuinely good.”
It gets analysed
1.1 sRating, real theme, severity, and whether a gesture is warranted.
Analysis
rating : 2/5 theme : "waiting time" (6× this month) positive : "food quality" — worth echoing in the reply severity : medium · customer recoverable gesture : suggested (second visit)
The reply is written
2.2 sIn your brand voice, no copy-paste formula, no promise you can’t keep.
Draft reply
“Hello Sofia, thank you for taking the time — and glad the food landed well. 35 minutes on a Tuesday lunchtime is not our standard: we reworked the lunch service this week. Say hello next time you’re in and we’ll look after you.”
You approve in one gesture
15 s of your timePublish, edit, or decline. Nothing goes out without a human.
Published · reply time: 11 min
Reply published on the correct location listing Customer history updated Location response rate: 100 %
The signal comes up
—One review is an anecdote. Six on the same theme is an operations problem.
Trend alert · Geneva-Cornavin
“Waiting time”: 6 mentions in 30 days (+200 %) Concentrated on Tuesday lunch service Location average: 4.1 → 3.8 Alert sent to the site manager
You keep control of every publication. The goal is not to reply automatically: it is to never again leave a review unanswered for lack of time.
Your numbers
What this weighs at your company
Run the numbers on your own figures
Move the sliders: everything recalculates live, from your own volumes.
0h/month
Time handed back to your team, every month
0€/year
Value of the time recovered over twelve months
0FTE
Full-time equivalent freed from work that creates no value
0€
What doing nothing costs over three years
How we build it
Nothing magic — assembled building blocks
Every block is replaceable and documented. You own the code, the data and the access — that is a condition, not an option.
See the offering AI automation & agents- Multi-platform connectors
- Sentiment and theme analysis
- Drafting in your brand voice
- Mandatory human approval
- Trend alerts per location
Proof
Respark is our own product on this pipeline: review collection, generated reply, approval, publication.
Visit ResparkThe other scenarios
Often, the real subject is somewhere else
- Trades · construction · quote-driven servicesFrom a voice note to a signed quote, in 90 secondsThe quote goes out the same day — not next Tuesday.
- B2B services · e-commerce · agenciesEvery inbound request sorted, qualified and answeredThe shared inbox stops being a pile. It becomes a queue of cases.
- Professional firms · industry · document-heavy organisationsAsk 12,000 pages a question — and get the sourceThe answer comes with the page number. Verifiable in five seconds.
One concrete problem is enough to start
Shall we test these assumptions on your case?
Twenty minutes is enough to know whether this scenario holds at your company, what it assumes about your data, and where to start.