Siftree labels every ticket, chat, call, and review by root cause, then shows which contact drivers are growing, with quotes attached.
Ticket #48211Oct 3
Live chatOct 4
Contact drivers · Week 41
18,240
conversations this quarter100% labeled · no sampling
+ 9 more drivers · 412 contacts
“QA reviews 2% of conversations. The other 98% are a mystery.”
QA sample
2%
Read by a reviewer
Siftree
100%
Labeled by driver, sentiment, risk
Own your intelligence
Your drivers, your scales, your rules — not the help desk's defaults.
Ticket #48211
Rewards member · Mobile app
“I redeemed 500 points and nothing showed up at checkout.”
Labels
Contact driver
1 of 14 · your taxonomy
because “redeemed 500 points”
Sentiment
Fixed scale
because “nothing showed up”
Escalation risk
Fixed scale
because 3rd contact in 4 days
Lands in the trend
Rewards points missing
312
▲+41%Quoted in the weekly report as [1]
Contact drivers by week
Rewards points missing tripled after the Oct 3 mobile checkout update.
Contacts per week, by driver
Rewards points missing
Shipping delay
Packaging defect
Product usage
Subscription change
Rewards points missing
Mobile checkout redemptions since the Oct 3 update.
Shipping delay
Down after the carrier switch on Sep 30.
Redemption help article
Linked in only 12% of related tickets.
Tagging vs. labeling
QA reads 2% of conversations
Every ticket, chat, call, and review
Tags agents forget to apply
14 fixed drivers, applied the same way
Anecdotes product can ignore
Counts, trends, and quotes
Issues found three months late
An alert the week a driver jumps
What lands
Weekly contact-driver report
Lumera Support · Week 41
What's growing
Rewards points missing rose 41% week over week, driven by mobile checkout redemptions1Ticket #48211 · Oct 3. Sentiment on the driver fell from neutral to negative.
What's shrinking
Shipping-delay contacts fell 18% after the carrier switch on Sep 302Call recording · Oct 2.
Every claim links to the post, call, or page it came from.
SiftreeApp7:02 AM
Rewards points missing up 41% week over week
312 contacts in Week 41, mostly mobile checkout redemptions. Sentiment turned negative. 3 quotes attached.
Thresholds you set, delivered to Slack or email.
Task schedule
Approve the task once. It keeps running and repairs itself.
Every conversation, labeled
| Conversation | Channel | Contact driver | Sentiment |
|---|---|---|---|
| “I redeemed 500 points and nothing showed up at checkout.” | Ticket | Rewards points missing | Negative |
| “Third time asking where my order is.” | Call | Shipping delay | Negative |
| “The pump broke after a week.” | Review | Packaging defect | Negative |
| “Can I use the moisturizer under SPF?” | Chat | Product usage | Neutral |
Labeled records you can filter, export, or query from Claude and ChatGPT.
Start with a prompt
Copy one into the Siftree agent.
“What are the top five reasons customers contacted us this month, by channel?”
“Which contact drivers grew fastest after the October release?”
“Where do refund requests and cancellation language show up together?”
“Which drivers have no matching help-center article?”
“Summarize this week's escalations for the CX standup.”
“Alert me when any driver grows 25% week over week.”
Questions
FAQ
No. Siftree labels every conversation in the window you choose, so small but fast-growing drivers show up before they become big ones.
Yes. Paste your existing tags or let Siftree propose a taxonomy from a sample. Labels come from a fixed list, so trends stay comparable over time.
Yes. Call recordings are transcribed and labeled in the same dataset as tickets and chats.
A chat assistant answers once from what it can see in the conversation. Siftree collects and connects your data, labels every record the same way, re-runs on a schedule, and cites the source behind each claim. You can still ask from ChatGPT or Claude through Siftree MCP.
Access is scoped to the channel and the accounts you grant. Tasks run in an isolated sandbox, creating or running a task requires approval, and every action is written to an activity log.
No. Describe the outcome in plain language. Siftree scopes the work, builds and tests the pipeline, and asks for approval before anything runs.
Sources
Gong
PylonManual ticket taggingOne analyst, every team
Siftree
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[Machine-readable summary](https://www.siftree.com/llms.txt) — full machine-readable index.