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Blog›SaaS / Customer Success

Know Which Accounts Are at Risk Before They Tell You

Most churn is visible weeks before it happens — in login frequency, support volume, and survey scores. AnalityQa AI AI surfaces those signals as a single health score your whole team can act on.

Try AnalityQa AI AI free →See live examples
SaaS customer success team reviewing analytics

The problem

  • →Usage data lives in your product database, NPS responses sit in a survey tool, and support tickets are in Zendesk — nobody has a single view of account health.
  • →CS managers build health score spreadsheets manually each week, which are stale by the time they reach the team.
  • →Red accounts are only identified after a cancellation notice arrives, not weeks earlier when intervention would have worked.
  • →There is no consistent definition of 'at-risk' across CSMs — each rep uses different signals and thresholds.

Why the usual approach breaks down

Data is split across four systems

Product events, CRM records, support tickets, and NPS responses each live in separate tools — Amplitude, HubSpot, Zendesk, Delighted — with no shared customer ID. Joining them requires engineering time most CS teams do not have.

Composite scoring is brittle in spreadsheets

Weighted averages across multiple data sources break whenever a field name changes or a new data source is added. Excel formulas that reference external exports are not maintainable at scale.

Dashboards go stale within days

BI dashboards built by data teams take weeks to deliver and become outdated the moment account data changes. CS managers end up re-requesting the same report every week.

No automated alerting when scores drop

Even when a health score model exists, teams lack the infrastructure to get notified when an account crosses a risk threshold — so the score is checked occasionally rather than acted on continuously.

How AnalityQa AI AI solves it

Upload your data — or connect it live — and ask in plain English.

01

Connect your product DB and CSV exports in one step

Upload CSV exports from your CRM, NPS tool, and support platform, or connect directly to your PostgreSQL/MySQL product database. AnalityQa AI AI maps customer IDs across sources automatically.

02

Define health score logic in plain language

Ask AnalityQa AI AI to weight usage frequency at 40%, NPS at 30%, and open support tickets at 30%. It writes and runs the scoring query without requiring you to know SQL.

03

Auto-generate red/yellow/green segmentation

AnalityQa AI AI buckets every account into health tiers based on your thresholds and outputs a prioritized at-risk list with the specific signals driving each score.

04

Scheduled dashboards refresh automatically

Set the health score dashboard to update daily. AnalityQa AI AI re-runs the scoring logic against fresh data and surfaces any accounts whose score changed significantly since the last run.

05

Anomaly flagging surfaces early churn signals

Beyond the composite score, AnalityQa AI AI flags accounts with sudden drops in a single dimension — for example, daily active users falling 50% week-over-week — even before the overall score turns red.

You askedGenerated in 4.2s

"Show me the health score distribution across all accounts this month."

MRR

€328k+4.1%

Net retention

112%+3pp

Churn

2.4%−0.6pp

Bar chart: account count by health tier (green 58%, yellow 27%, red 15%)

Last 12 mo
Segment ASegment BSegment CSegment DSegment ESegment F

Table: account name, prior score, current score, score delta, primary driver

Table: account name, health score, risk driver (usage / NPS / support tickets), CSM owner

A dashboard built in AnalityQa AI — from question to chart, no SQL.

Real examples

Paste your data. Ask. Ship.

You

Show me the health score distribution across all accounts this month.

AI

AnalityQa AI AI scores every account using your defined formula and plots the full distribution across health tiers.

Bar chart: account count by health tier (green 58%, yellow 27%, red 15%)
You

Which accounts dropped more than 10 points in health score over the last 30 days?

AI

AnalityQa AI AI compares current and prior-period scores for every account and returns the accounts with the steepest decline, sorted by magnitude.

Table: account name, prior score, current score, score delta, primary driver
You

Give me the full at-risk list with the top reason each account is flagged.

AI

AnalityQa AI AI filters to red-tier accounts and identifies which single metric is most responsible for each account's low score.

Table: account name, health score, risk driver (usage / NPS / support tickets), CSM owner
You

How does health score correlate with contract renewal date?

AI

AnalityQa AI AI cross-references health scores against renewal dates from your CRM export and highlights accounts that are both at-risk and renewing within 90 days.

Scatter plot: health score vs. days to renewal, color-coded by tier
You

Show average health score by CSM to see if workload is balanced.

AI

AnalityQa AI AI groups accounts by assigned CSM and computes the average health score and red-account percentage for each rep.

Bar chart: CSM name vs. average health score, with red-account count overlay

What teams get out of it

✓CS teams using composite health scores identify at-risk accounts an average of 6 weeks before cancellation.
✓Automated scoring replaces 4-6 hours of weekly manual spreadsheet work per CSM.
✓Accounts flagged as red-tier and contacted within two weeks show materially higher save rates than those identified reactively.
✓A consistent, data-driven health definition aligns CS, Sales, and product teams on which accounts need attention.

Frequently asked questions

Can AnalityQa AI AI connect directly to Amplitude or Segment?+

AnalityQa AI AI connects to PostgreSQL and MySQL databases, and accepts CSV and Excel exports from any source. If your Amplitude or Segment data flows into a data warehouse (Redshift, BigQuery, Snowflake), you can connect to that directly. Otherwise, export the relevant event data as CSV and upload it.

How does AnalityQa AI AI handle personally identifiable information in customer data?+

Data you upload is processed only to answer your queries and is not used to train models or shared with third parties. You can also pseudonymize account names before uploading if your data governance policy requires it.

How accurate is the health score if data sources are incomplete?+

AnalityQa AI AI surfaces data gaps explicitly rather than silently dropping records. If an account has no NPS response, for example, it will tell you the score was calculated on available dimensions only. You can choose to exclude incomplete accounts or apply a conservative default.

Does AnalityQa AI AI replace our customer success platform (Gainsight, ChurnZero)?+

No. CS platforms handle workflow automation, playbooks, and CRM sync. AnalityQa AI AI is an analytics layer — it helps you explore data, build models, and answer ad-hoc questions fast. Most teams use it alongside their CS platform rather than instead of it.

Can I customize the health score formula without help from a data team?+

Yes. You describe the formula in natural language — weights, dimensions, thresholds — and AnalityQa AI AI translates that into a scoring query. You can iterate by asking follow-up questions like 'increase the weight on support tickets to 40%' and the model updates immediately.

How often does the health score dashboard refresh?+

You can schedule the dashboard to refresh daily, weekly, or on any custom cadence. Each refresh re-runs the scoring logic against whatever data is currently connected, so scores stay current without manual effort.

What is the pricing model?+

AnalityQa AI AI is priced as a SaaS subscription. Plans vary by the number of connected data sources, query volume, and seats. There is a free trial that lets you upload your own data and run the full health score workflow before committing.

Related guides

SaaS / Customer Success

Customer Churn Analysis Without the Spreadsheet Grind

SaaS / Customer Success

Understand How Customers Actually Use Your Product

Your data has answers. Start asking.

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