Skip to content

QUERRI FOR CUSTOMER SUCCESS

Less Spreadsheet Firefighting. More Retained Revenue.

Your CS team tracks accounts across CRM, helpdesk, product, and spreadsheets — but the full customer picture lives nowhere. Querri connects your data, reads the unstructured signals your tools miss, and turns fragmented customer context into action-ready insights. No SQL. No waiting on a data ticket.
Try Querri Free Request Demo
Querri customer success analytics dashboard

What Customer Success teams use Querri for

Every CS analysis. One platform.

From churn signal detection to QBR prep — every analysis your team runs, in one place.

Early Churn Signal Detection

73% of CS leaders say identifying at-risk customers is the best activity to automate with AI — but most tools only show you structured metrics. Querri extracts risk signals from the text your dashboards can't read: negative sentiment in tickets, escalation themes in call notes, complaint patterns in NPS verbatims. Combined with usage and billing data, it builds a risk picture that's weeks ahead of a formal health score alert.

Try asking

Which accounts have had negative sentiment tickets and a usage drop in the last 30 days?
Show me accounts with the highest complaint volume relative to their ARR this quarter
Churn signal detection and at-risk account analysis — Querri

How it works

How Querri Works for Customer Success

Step 1 — Connect

Connect Your Entire CS Data Stack

Upload exports or pull live data through native connectors — HubSpot, Salesforce, BigQuery, Google Drive, and more. Querri handles the joins, field alignment, and column matching automatically. No data engineering dependency required. Querri can: ✓ Connect to HubSpot CRM, Salesforce, BigQuery, and more ✓ Upload CSV and Excel exports from Zendesk, Gainsight, ChurnZero, and more ✓ Join CRM, support, product, and billing data automatically — no SQL required

Step 2 — Clean

Clean the Fragmented Data Your CS Team Relies On

Real-world CS exports have inconsistent account IDs, duplicate contact records, mismatched date ranges, and missing fields. Querri's agentic preprocessing detects and fixes all of it automatically — before any analysis runs. Querri can: ✓ Deduplicate account records and customer contacts across CRM and helpdesk exports ✓ Normalize account IDs and fix inconsistent status values across systems ✓ Handle missing timestamps, blank required fields, and format mismatches

How it works

From fragmented CS exports to leadership-ready output in four steps

Any CS ops manager can run this workflow. No SQL, no data engineering ticket, no waiting in a queue.

01
One-time setup

Connect

Upload exports from your helpdesk, CRM, or survey tool — or connect live to HubSpot, Salesforce, BigQuery, and Google Drive.

02
Automatic

Clean

Querri automatically normalizes account IDs, deduplicates contact records, fixes date formats, and resolves field mismatches across your CS data sources.

03
Conversational

Analyze

Ask your question in plain English. Querri runs multi-step analysis — churn signals, health score inputs, account segmentation, ticket theme discovery — and shows its reasoning in explicit, inspectable steps.

04
Your format

Share

Export to Excel, PowerPoint, or PDF. Build a live CS dashboard. Or schedule the whole workflow to run automatically every week.

See each step in action with our playbooks

Step-by-step walkthroughs for real CS workflows — from connecting your first export to building an automated weekly account health report.

Browse Playbooks

Step 3 — Analyze

Answer CS Questions Without a Data Engineering Ticket

Which accounts show early churn signals? What complaint themes are most common this quarter? How does NPS correlate with product adoption? Querri's AI data analyst answers these questions from your actual ticket text, CRM exports, and usage data — not just structured counts. Every step is explicit and inspectable — so you can defend the finding before you share it with the VP of CS. Querri can: ✓ Analyze ticket and note text to identify recurring themes and risk indicators ✓ Ask churn, health, and account performance questions in plain English ✓ Compare trends by segment, account tier, or time period — with step-by-step logic you can inspect

The reality for most CS teams

You're sitting on thousands of customer signals. Most tools just can't read them.

Based on research from Gainsight, ChurnZero, and Custify across 1,500+ CS leaders and practitioners.

73%

Of CS leaders want to automate churn risk identification

But most tools only surface risk from structured metrics. The real signals — negative tone in tickets, complaint themes in notes, disengagement in verbatims — are locked in free text.

32%

Of organizations have a single place tracking all customer data

CRM, helpdesk, product analytics, billing, surveys — each system tells a different part of the story. CS ops spends hours every week stitching them together manually.

83%

Of CS professionals use spreadsheets daily

Not because they want to — but because no single tool connects all their sources and answers questions without a data team or SQL knowledge.

Step 4 — Share & Automate

Automate Weekly CS Reports and Account Health Reviews

Run a prompt, get a leadership-ready CS summary — with charts, narrative insights, and multi-source comparisons. Start a drag-and-drop dashboard in seconds from a single prompt, automate it to refresh on any cadence, and share it with your team without a BI ticket. Save it as a scheduled workflow and it runs automatically on whatever cadence you need. When the VP of CS asks a follow-up question in the QBR, you're back in the analysis in seconds — not rebuilding from scratch while the room waits. Querri can: ✓ Generate CS health and renewal pipeline reports with one prompt ✓ Build drag-and-drop dashboards that refresh automatically from live CRM and support data ✓ Export to Excel, PowerPoint, PDF, or Google Sheets — automatically
"
The biggest problem in CS isn't that we don't have data — it's that it lives in five different tools and none of them agree on the same account ID.

Head of Customer Success Operations

B2B SaaS, 200-person company

New — Querri Wrapped

You ran the analysis.
Querri builds the QBR deck.

The best use of CS ops time isn't formatting slides — it's knowing what the account data means and what to do about it. Querri Wrapped closes the loop: once your analysis is done, Querri's agentic pipeline turns it into a complete, branded CS performance presentation in seconds.

25 slide templates. Interactive Plotly charts. Fullscreen 16:9 presentation mode. Export to PowerPoint or PDF. Renewal pipeline, account health trends, churn signals, and narrative — all in one output ready for the executive review.

25 slide templates Interactive charts Export to PowerPoint or PDF

Ready to see Querri in action for your specific CS workflows?

Explore our library of step-by-step CS playbooks — each one built around a real customer success job-to-be-done.

Request DemoTry Querri Free

Why Querri

Built differently — so CS teams can actually use it.

01

It reads the signals your tools can't.

Tickets, call notes, NPS verbatims — the most important customer signals are unstructured. Querri converts free text into structured columns: complaint themes, sentiment, priority, escalation flags. Signals you couldn't measure before become trackable metrics.

02

Every analysis is transparent and defensible.

Step-by-step logic you can inspect before you share it with the VP of CS. No black box, no churn predictions you can't explain. When leadership pushes back, you're back in the analysis in seconds.

03

Self-serve, without the wait.

Ask CS questions in plain English, get answers in minutes — not a two-week BI ticket. Churn signals, health score inputs, account segments — all from the same workspace, no SQL required.

The complete CS analytics workflow. One platform. Any CS ops manager can run it.

Try it free

Security & Privacy

Your customer data stays yours.

Customer success data includes renewal values, health scores, escalation records, and strategic account context — among the most sensitive data in the organization. Querri is built for teams that can't afford a data security incident.

SOC 2 Type II Certified

Independently audited →

Encryption in transit and at rest →

All customer account data is encrypted end-to-end. Tenant isolation, RBAC, SSO/MFA, and full audit logging are included at every tier.

Encryption RBAC SSO / MFA

Transparent, step-by-step analysis — not a black box →

Every step Querri takes is visible and reviewable. See exactly how a health signal or churn indicator was calculated and validate the answer before you share it with leadership.

Step-by-step audit Reviewable logic

Zero data training policy →

Your customer data is never used to train AI models. Customer data is isolated per tenant and never shared or commingled across accounts.

No model training Tenant isolation

Why Customer Success Teams Choose Querri

Simple ways to do hard things

Talk to your data through a chat interface and watch it transform in a spreadsheet view.

Reliable, repeatable data workflows

Clean, merge, and analyze once. Then set up your data workflows to run on your schedule.

Designed for humans, not machines

It’s not a black box. See an explanation of the data workflows behind every Querri.

Frequently Asked Questions

Why is it so hard to get a complete picture of account health?
Because the signals that matter most are scattered across at least five different systems — CRM for account history, helpdesk for support tickets, product analytics for usage, billing for contract data, and survey tools for NPS. Most CS platforms only pull from one or two of those sources, and none of them can read the unstructured text inside tickets and call notes where the real risk signals live. Querri connects all of those sources in one workspace and uses AI to extract structured signals — sentiment, complaint themes, escalation flags — from the free text your other tools can't analyze.
Which data sources does Querri work with for Customer Success?
Querri connects natively to HubSpot CRM (auto-sync every 4 hours), Salesforce (early access), BigQuery, Google Drive, PostgreSQL, MySQL, SQL Server, and Redshift. For support platforms like Zendesk, Freshdesk, or Intercom — and survey tools like Delighted, Medallia, or Gainsight exports — you upload CSV or Excel exports. Querri automatically joins your exports and standardizes field formats, even when account IDs, date ranges, or status values don't match across systems.
How is Querri different from dedicated CS platforms like Gainsight or ChurnZero?
Dedicated CS platforms are strong at workflow orchestration — health scores, CTAs, playbook execution — but they rely on structured, pre-defined data inputs. What they can't do is analyze the unstructured text inside tickets, call notes, and survey verbatims to find patterns your dashboards are missing. Querri fills that gap: it reads free text to surface complaint themes, sentiment shifts, and churn signals, then lets you combine that analysis with your CRM and billing data in one workspace. Think of Querri as the analytical layer that makes your CS platform's inputs better.
Can Querri analyze unstructured customer signals like support tickets and NPS verbatims?
Yes — and this is one of Querri's strongest capabilities for CS teams. Upload a ticket export or NPS response file and Querri can cluster records by theme, identify sentiment patterns, surface the most common issue types even when tagging is inconsistent, and flag which accounts are generating the highest-risk signals. This is especially valuable for QBR prep and churn post-mortems, where the most actionable evidence is in the free text, not the score.
How long does it take to build a weekly CS health report?
Once your data is loaded, running a weekly CS summary takes a few minutes. The first-time setup — connecting your sources and defining your key questions — is a one-time investment. After that, save it as a scheduled workflow and the Monday CS digest refreshes automatically, delivered to Google Sheets or your Querri Library without anyone having to pull exports and rebuild a spreadsheet.
Can CS ops teams without SQL skills actually use this?
Yes. Querri was built for people who understand the customer — not people who write SQL. Ask questions the same way you'd ask them in a QBR — 'Which enterprise accounts had negative sentiment tickets and a usage drop this month?' — and get answers with charts, tables, and narrative. For ops managers who do know SQL: every step Querri takes is visible and inspectable, so you can verify the logic before you share a finding with the VP of CS.
Is Querri secure enough for sensitive customer account data?
Yes. Querri is SOC 2 Type II certified, with encryption in transit and at rest, tenant isolation, RBAC, SSO/MFA support, and audit logging. Customer data is never used to train AI models. Role-based access controls let you manage exactly who can see what — so CSMs see their own book of business, team leads see team performance, and sensitive ARR or contract data stays appropriately scoped.
How does Querri handle messy exports from multiple CS tools?
Querri's agentic preprocessing automatically detects and fixes the formatting issues that make real-world CS exports unreliable for analysis — extra header rows, inconsistent account ID formats, duplicate contact records, missing timestamps, merged cells. It handles this at ingestion, before any analysis begins, so you're not spending half your day cleaning data before you can understand what's actually happening in your book of business.
What is customer success analytics and why does it matter?
Customer success analytics is the practice of analyzing the data your CS operation generates — ticket text, NPS responses, product usage, billing events, account activity — to understand which customers are healthy, which are at risk, and where to focus CSM time. The challenge for most CS teams isn't access to data: they generate enormous amounts of it. The challenge is that the most valuable signals — themes in call notes, sentiment in survey verbatims, patterns in support tickets — are unstructured and hard to analyze at scale. Querri solves this by letting CS ops teams analyze free text and combine exports from multiple sources to ask questions in plain English, without waiting for a BI report or building pivot tables by hand.

Resources

Go deeper on CS analytics

Step-by-step playbooks and practical guides for the workflows CS teams run every day.

Playbooks

Step-by-step Support Operations

How to Track and Improve First Response Time by Channel and Agent

A walkthrough for analyzing FRT across your support channels, identifying breach patterns, and surfacing the agent-level data your SLA reviews need.

Read the playbook
Step-by-step Support Operations

How to Analyze Ticket Volume Drivers to Reduce Repeat Contacts

Identify the root causes behind high ticket volume and recurring contact reasons — so your team can fix the issues driving them, not just respond faster.

Read the playbook

Articles

FRT

11 First Response Time Reporting Mistakes CS Teams Make

The most common FRT measurement errors — from calendar-time miscalculations to bot-inflated averages — and how to fix each one.

Read article
NPS

From Survey Chaos to Clear Themes: Analyzing NPS Responses at Scale

Turn hundreds of open-ended NPS verbatims into structured themes, sentiment trends, and account-level signals that matter for retention.

Read article
Text Analysis

How to Actually Make Sense of Unstructured Text Data

A practical guide to extracting structured insight from tickets, call notes, and survey verbatims — the customer signals most tools can't read.

Read article
Dashboards

How to Turn Dashboards into Decision Systems (Not Just Displays)

Why most CS dashboards don't drive action — and how to design account health views that connect signals to next steps.

Read article
Reporting

The Power of Clear, Concise, and Actionable Leadership Reporting

How to build the CS performance summaries your leadership team will actually use — for QBRs, board reviews, and weekly health check-ins.

Read article
Segmentation

Customer Segmentation: The Complete Guide for Data-Driven Teams

The frameworks CS and marketing teams use to segment accounts by behavior, risk, and value — and how to keep those segments consistent across systems.

Read article

Your customers are signaling churn before it happens. Querri helps you see it.

Connect your CS data stack, extract risk signals from the text your tools can't read, and build the account health view your team actually trusts.

Start for Free Browse CS Playbooks