Tarification

Fullstory Alerting: Automate your response to user errors

Swiftask turns your Fullstory data into intelligent alerts. Detect friction, bugs, or drop-offs and trigger immediate action.

Resultat:

Don't suffer from errors. Get alerted and act before your customers leave your platform.

Late detection of Fullstory issues is costly

Manually monitoring Fullstory is impossible. Product and support teams spend hours navigating sessions, often missing weak signals of technical bugs or customer frustration until it's too late.

Les principaux impacts négatifs :

Reactive rather than proactive: Issues are discovered via support tickets, not by your tech teams. Churn rates rise.
Lost time in analysis: Finding the root cause in thousands of sessions eats up time that should be spent on development.
Silos between data and action: Fullstory insights remain isolated. There is no bridge between observation and automatic correction.

Swiftask connects Fullstory to your business and management tools. As soon as a critical segment is reached or a console error is detected, your AI agent analyzes the context and alerts the relevant team.

AVANT / APRÈS

Ce qui change avec Swiftask

Slow manual process

A customer encounters a JavaScript error. Support receives a ticket, forwards it to engineering. The engineer has to hunt through Fullstory to reproduce the bug. Meanwhile, the customer is frustrated.

Swiftask automation

Fullstory detects the error. Swiftask receives the event, extracts the session link and contextual data, and sends an enriched alert with pre-analyzed diagnostics to Slack or Teams.

Deploying your intelligent alerts

ÉTAPE 1 : Define your critical segments

Configure your segments in Fullstory based on behaviors (e.g., rage clicks, console errors).

ÉTAPE 2 : Connect Fullstory to Swiftask

Use Fullstory webhooks to send events from your segment to your Swiftask AI agent.

ÉTAPE 3 : Configure intelligent routing

Tell Swiftask which channel to notify and what data to include in the alert to assist with resolution.

ÉTAPE 4 : Enable automated response

Add automatic actions, such as creating a pre-filled Jira ticket with the session link.

Advanced alerting capabilities

Your agent analyzes error volume, revenue impact (via tagging), and per-user recurrence.

Connecteur cible : L'agent exécute les bonnes actions dans fullstory selon le contexte de l'événement.
Actions automatisées : Enriched alert sending, noise filtering, automatic ticket creation, AI session summarization, dynamic routing by product team.
Gouvernance native : Swiftask filters out the noise so your teams only receive high-value alerts.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-fullstory@swiftask.ai ). Vous gardez une visibilité complète sur chaque action et chaque message envoyé.

À retenir : L'agent automatise les décisions répétitives et laisse à vos équipes les actions à forte valeur.

Why automate Fullstory

1. Reduced MTTR

Resolution time is cut in three thanks to direct access to the faulty session.

2. Bug prioritization

Focus on the errors that affect the largest number of users.

3. Superior customer experience

Solve issues before the customer even needs to contact support.

4. Data-driven culture

Every product decision is backed by visual evidence from Fullstory.

5. Productivity gains

Automate data collection to allow your engineers to code, not search.

Privacy and compliance

Swiftask applique des standards de sécurité enterprise pour vos automatisations fullstory.

Encrypted data: Session data is transmitted via secure and encrypted channels.
Granular control: You decide which Fullstory data is shared with AI agents.
Full audit trail: Every triggered alert is tracked in Swiftask for post-incident review.
GDPR compliance: Swiftask adheres to the highest data protection standards.

Pour aller plus loin sur la conformité, consultez la page gouvernance Swiftask et ses détails d'architecture de sécurité.

RÉSULTATS

Impact on your performance

Métrique	Avant	Après
Detection time	Several hours (manual)	Seconds
Churn reduction	High (unresolved errors)	Measurable decrease (-15%)
Support efficiency	Manual triage time	AI-powered automated triage
Engineering focus	Reactive	Proactive bug management

Passez à l'action avec fullstory

Don't suffer from errors. Get alerted and act before your customers leave your platform.

Générez vos rapports Fullstory automatiquement avec l'IA

Cas d'usage suivant.