Collect Meaningful Feedback with AI Voice Bots
- Detractors0–6 · 21%
- Passives7–8 · 26%
- Promoters9–10 · 52%
- Net Promoter Score
- +31
- Completed surveys
- 1,204
- Median call length
- 48s
- Verbatims captured
- 81%
promoters − detractors
last 30 days, voice
score + one follow-up
of completed calls
Collecting timely feedback through surveys and open conversations is crucial for businesses. These surveys paint an accurate picture of how customers perceive your brand. Recent studies even show that reaching out via voice is more effective than any other channel.
VocalLabs' customizable voice bots conduct natural, flowing conversations to gather vital product- or service-level feedback and broader business insights.
A score on its own is a number. A score with the sentence that explains it is a decision. The bot always asks both — the scale question, then the why — and hands you the verbatim alongside the digit.
01 — 05
- 01Automated survey campaigns
- 02Natural language processing for sentiment analysis
- 03Real-time feedback collection and analysis
- 04Multi-channel deployment (voice, chat, email)
- 05Integration with CRM and analytics platforms
The survey you never answer is the cheapest one to run.
One list of ten thousand contacts, four channels, one week. The gap is not in the questions — it is in whether anyone answers them, and whether they say anything beyond the number.
- Voice bot call31.4%3,14081% verbatim · Under 2 hours
- SMS with link6.2%62011% verbatim · 1–2 days
- Email survey4.1%4109% verbatim · 3–5 days
- In-app prompt8.9%89014% verbatim · Next session
Figures from a VocalLabs retail deployment, 10,000 contacts per channel, surveyed within 48 hours of delivery.
What the bot does between dial and disposition.
- 01
Trigger on the event, not the calendar
The survey fires off a real moment — order delivered, ticket closed, policy issued, discharge complete. VocalLabs listens to your webhook or CRM stage change and dials inside the window where memory is still fresh.
Webhook · CRM stage · Batch list
- 02
Ask the one question that counts
The bot introduces itself, states why it is calling and how long it will take, then asks the scale question. Spoken numbers, "a solid eight", "I would say nine out of ten" and "ten, definitely" all resolve to the same integer.
NPS · CSAT · CES
- 03
Follow the score with a why
The follow-up branches on the band. A detractor is asked what went wrong, a passive what would have made it a ten, a promoter what stood out. The respondent talks for as long as they like; the bot does not interrupt.
Branching follow-up
- 04
Transcribe, theme and score sentiment
The verbatim is transcribed, tagged against your theme taxonomy and given a sentiment score. Free text that does not match an existing theme is clustered and surfaced for review rather than dropped.
NLP · Theme tagging
- 05
Close the loop before the day ends
Detractors raise an alert on the owning team the moment the call ends, with the score, the transcript and the recording attached. Promoters can be routed straight to a review request or a referral ask.
Alert · Callback · Review ask
A score, then the sentence behind it.
- BOT
Hi, is that Meera? This is Asha calling from Northline. Your order arrived yesterday — do you have forty seconds for two quick questions?
- CUSTOMER
Sure, go ahead.
- BOT
Thank you. On a scale of zero to ten, how likely are you to recommend Northline to a friend or colleague?
NPS question
- CUSTOMER
Umm… I would say a nine.
- BOT
A nine, noted. What made it a nine rather than a ten?
Score 9 · promoter · follow-up branched
- CUSTOMER
Honestly the product is great and it came a day early. The only thing was the packaging — the outer box was pretty beaten up, and there was a lot of plastic inside. Felt wasteful.
- BOT
That is useful, thank you — the box arrived damaged and there was more plastic than you expected. Have I got that right?
Verbatim captured · 2 themes tagged
- CUSTOMER
Yes, exactly.
- BOT
I have logged it for the packaging team. That is everything — thanks for your time, Meera. Have a good evening.
What the call wrote back
- nps_score
- 9
- band
- promoter
- verbatim_themes
- packaging.damage, packaging.excess_plastic
- sentiment
- +0.62 (positive, with a specific complaint)
- routed_to
- Packaging QA — weekly digest
- call_duration
- 41s
A nine is a good score that still contained a defect report. Without the follow-up question, the packaging problem never reaches anyone.
Six instruments, one voice.
Each instrument has its own scale, its own wording and its own trigger. The bot knows which scale it is on, so a five is read as the middle of a CSAT and the bottom of an NPS without you scripting the difference.
- NPS0 – 10“How likely are you to recommend us to a friend or colleague?”Quarterly, or 7 days after onboarding
- CSAT1 – 5“How satisfied were you with the support you received today?”Within an hour of ticket closure
- CES1 – 7“How much effort did you personally have to put in to get that resolved?”After a self-service or IVR journey
- Post-deliveryYes / No + 0 – 10“Did the order arrive on time and in the condition you expected?”Same day as the delivery scan
- Post-visit0 – 10“How would you rate the care you received during your visit?”24 hours after discharge
- Churn exitOpen-ended“What made you decide to cancel? Anything we could have done?”On cancellation confirmation
Open answers, counted.
Every verbatim is tagged against your taxonomy and counted. What you read is not a word cloud — it is a list of recurring, nameable problems and compliments, each one traceable back to the calls that produced it.
- Delivery arrived early312
- Packaging damaged in transit168
- Support answered on first try144
- Excess plastic in the box97
- Refund took longer than promised88
- Could not reach a human61
A detractor is an alert, not a row in a report.
- T+0s01
Score captured
The respondent says "four". The bot recognises the band before the sentence is finished and switches to the recovery follow-up.
- T+35s02
Reason recorded
The open-ended answer is transcribed in full and tagged. Nothing is summarised away — the account owner reads what was actually said.
- T+40s03
Alert raised
A ticket opens on the owning team with the score, the transcript, the recording and the customer record already attached.
- Under 4h04
Human callback
A person calls back inside your SLA. The bot never pretends to resolve the complaint; it makes sure somebody who can, hears about it in minutes.
- T+7d05
Re-survey
The same contact is re-surveyed after the fix. The movement between the two scores is the number that tells you recovery worked.
Where the survey runs, and where the answer lands.
- 01
Outbound telephony
Dial any landline or mobile on your own numbers, with local caller ID, retry windows and per-region calling-hour rules.
SIP · PSTN · Local CLI
- 02
Inbound IVR hand-off
End a support IVR journey with the survey instead of a beep, so the score is attached to the call that just happened.
Post-call IVR
- 03
WhatsApp & chat
The same script, same branching, same themes over text for contacts who will not pick up a call.
WhatsApp · Web chat
- 04
CRM write-back
Score, band, verbatim and theme tags land on the contact record, so the survey lives where the account owner already works.
Salesforce · HubSpot · Zoho
- 05
Analytics & warehouse
Stream every response row into your warehouse or BI tool for trend lines, cohorting and driver analysis.
Webhook · BigQuery · Snowflake
- 06
Language coverage
Run the same instrument in the language the respondent answers in, with themes normalised to one taxonomy.
English · Hindi · +10 Indic
