The score has no content
A 3-out-of-5 could mean slow support, a broken feature, or a bad price change. Score-only software treats all three identically, as the number 3.
Satisfaction surveys that explain the score.
A CSAT number tells you something changed. It never tells you what, or what to do about it. Diaform follows every rating with a real conversation, so satisfaction data arrives with the reason attached, not as a chart you argue about in retros.
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Where score-only CSAT tools stall
The textbox doesn't rescue it
Optional comment fields convert in single digits, skew toward the angriest customers, and produce one-liners that still need a human to interpret.
Drivers get debated, not measured
When the trend dips, teams theorize in meetings. The evidence that would settle it, hundreds of customers explaining their score, was never collected.
How Diaform measures satisfaction
01
Score first, then the why
Ask your CSAT question exactly as you always have. The AI then opens a short conversation about the reason, tailored to the score and the answer given.
02
Probing that adapts to each customer
"Support was slow" gets a different follow-up than "the app crashed". The AI chases each thread the way an analyst would, at every volume.
03
Sentiment alongside the score
A resigned 4 and an enthusiastic 4 are different customers. Sentiment on every transcript separates them, which the number alone never will.
04
Voice for the fuller story
Customers explaining satisfaction out loud give 2-3× more detail than typed comments, and can switch to text whenever they prefer.
05
Alerts on the scores that need a human
A low score from a key account pings Slack immediately, with the summarized reason attached, while an apology can still land.
06
Trends with reasons attached
Analytics aggregate sentiment and themes across responses, so "CSAT dropped 0.3" comes with "driven by the checkout change" in the same view.
How it works
- 01
Set your satisfaction question and context
Keep your existing CSAT scale for continuity. Add your business context so the AI's follow-ups are informed and on-topic.
- 02
Trigger at the moments you measure
After support interactions, purchases, renewals, or periodically. One link works in any email flow, product surface, or QR code.
- 03
Every rating becomes a short conversation
The AI asks why, probes the specifics, and closes politely, typically 2-4 minutes, by voice or text, in 30+ languages.
- 04
Read reasons, not just the trend line
Summaries and sentiment per response, driver themes in aggregate, Slack alerts on red flags, CSV export for deeper cuts.
Satisfaction moments worth more than a number
Post-support CSAT
Learn whether the low score was the agent, the policy, or the product, three very different fixes that one number conflates.
Post-purchase satisfaction
Capture the full first impression while it's fresh: what almost stopped them, what surprised them, what they'd warn a friend about.
Renewal-time check-ins
Before the renewal conversation, know what the account actually thinks, from the account, not from the CSM's optimism.
Periodic relationship surveys
Quarterly satisfaction pulses where every score arrives with its reasoning, so the QBR deck writes itself from evidence.
Product-area satisfaction
Measure satisfaction with a specific flow after using it, and hear which step dragged the score down.
Frontline experience feedback
For services and e-commerce: satisfaction with delivery, staff, or the visit, with the story behind every outlier rating.
Score-only CSAT software vs. Diaform
Score-only CSAT software
- Collects a number and an optional one-line comment
- Single-digit comment rates, skewed to the angriest
- Drivers of change are guessed at in meetings
- A resigned 4 and a delighted 4 look identical
- Low scores surface in the monthly report
Diaform
- Collects the score plus a probed conversation about why
- Conversational format lifts both completion and depth
- Driver themes measured across every response
- Sentiment separates tone behind identical scores
- Low scores from key accounts alert Slack instantly
Frequently asked questions.
The practical details behind setting up, running, and scaling this kind of research with Diaform.
Software for measuring how satisfied customers are, typically via CSAT ratings after key interactions. Traditional tools focus on collecting and dashboarding the score; Diaform adds the layer that usually stays missing, a conversation with each customer about what drove their rating.
More conversations your team can run.
Explore the other ways Diaform can turn a static request for feedback into a useful conversation.
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