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askotter / Solutions / Real-Time Change Detection
/// real-time monitoring

Know what changed. Fix it before it costs you.

askotter monitors every metric across every connected tool. When something moves, the right person gets an alert with context in under 5 minutes.

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GA Google Analytics ST Stripe SH Shopify ME Meta Ads ◆ DATA LAKE 4 sources ◎Real-Time Change Detection
/// under the hood

Every metric. Every tool. Agents that adapt.

askotter watches your data lake around the clock. When revenue drops, conversions spike, or traffic shifts, it catches the change and alerts the right person. Agents adjust thresholds and refine detection on their own. No manual tuning required.

Five days is too long to find a broken checkout.

Most teams find out something broke from a weekly report. That means days of lost revenue. askotter cuts that to minutes. A broken checkout on Tuesday gets flagged on Tuesday, not the following Monday.

/// DETECTION CAPABILITIES
→ Cross-platform anomaly detection
→ Alerts with root cause context
→ Severity scoring to filter noise
→ Auto-routing to the right team member
→ Historical pattern matching
→ Adaptive thresholds
POWERED BY INTEGRATIONS
CHANGE FEED · REAL-TIME 4 SOURCES MONITORED
2:14pCRITCheckout error rate: 0.3% → 4.7%, mobile gateway timeoutShopify
2:16pWARNCorrelated: theme deploy at 2:11 PM, CSS overflow on .checkout-btnShopify
1:42pWARNMeta CPA up 23% vs 7-day average, audience fatigue likelyMeta Ads
12:08pINFONew keyword ranking: #4 for "best crm tools" (was #11)Search Console
11:30aOKStripe payment latency normalized, 120ms avg (was 890ms)Stripe
10:15aINFOEmail campaign open rate 28.4%, above benchmarkHubSpot
/// real-world scenario

Catching a silent checkout failure

How change detection saved $47K in 18 minutes.

2:11 PM
Theme update deployed to Shopify
Developer pushes a CSS change. No errors in the deploy log.
2:14 PM
askotter detects anomaly
Checkout error rate jumps from 0.3% to 4.7%. askotter flags it.
2:16 PM
Root cause identified
Error spike started 3 minutes after deploy. Mobile checkout button hidden by CSS overflow.
2:29 PM
Fix deployed, revenue restored
CSS reverted. Error rate drops to 0.2%. Revenue impact: $412 vs $47K if found Friday.
BEFORE vs AFTER
METRIC
BEFORE
WITH ASKOTTER
Time to detect issue
5-7 days (weekly report)
3 minutes
Revenue lost per incident
$20K-$50K average
Under $500
Root cause investigation
Half-day manual dig
Automatic, 2 minutes
Alert routing
Someone notices eventually
Self-healing, right person, instantly
/// pain points eliminated

What Changes Before You Notice

Insights That Arrive Too Late
See the problem →
Manual Reporting
See the problem →
/// kpi reference

KPIs monitored by this solution

Learn what each metric means, where it lives, and what causal analysis reveals about why it changes. Browse the full KPI Glossary →

Conversion Rate → ROAS → Uptime SLA →

Other Solutions

Unified Data Lake Natural Language Queries Cross-Platform Attribution Predictive Intelligence Automated Root Cause Analysis

Problems We Solve

Data Silos Manual Reporting Insights That Arrive Too Late Broken Attribution The Analyst Bottleneck Tool Sprawl

Integrations

Shopify Stripe Google Analytics Google Ads Google Search Console Meta Ads HubSpot WordPress GitHub SAP

Stop finding out on Monday. Know on Tuesday.

Setup takes under an hour. No engineering required.

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