Pricing

Decode customer sentiment on InsertChat with AI

Swiftask connects your AI agents to InsertChat to analyze every message in real-time. Identify frustrations and satisfaction instantly.

Result:

Turn conversational data into actionable insights to improve customer experience.

InsertChat message volumes hide the voice of the customer

Managing a constant stream of discussions on InsertChat makes manual qualitative analysis impossible. Weak signals of dissatisfaction go unnoticed, while positive trends go uncelebrated. You are flying blind.

Main negative impacts:

Data saturation: Too many conversations for effective human analysis. Satisfaction patterns get lost in the noise.
Limited reactivity: A decline in customer sentiment is only detected too late, impacting retention and brand image.
Lack of qualitative KPIs: Management is based on quantitative metrics (response time) rather than the actual quality of the interaction.

Swiftask adds an AI sentiment analysis layer to your InsertChat streams. Each exchange is scored, classified, and analyzed to give you a clear view of customer mood.

BEFORE / AFTER

What changes with Swiftask

Traditional approach

Customer support handles messages one after another without an overview. Managers must read hundreds of exchanges to identify recurring issues, wasting precious time.

Swiftask + InsertChat

AI analyzes the tone and context of every InsertChat message live. Negative sentiment alerts are escalated instantly to managers, enabling proactive intervention.

Setting up sentiment analysis in 4 steps

STEP 1 : InsertChat connection

Link your InsertChat account to Swiftask via a secure and fast configuration.

STEP 2 : AI model definition

Configure the agent to detect language nuances specific to your industry and customers.

STEP 3 : Alert parameterization

Determine the sentiment thresholds that should trigger immediate notifications to your teams.

STEP 4 : Dashboarding and reporting

Visualize global and agent-level sentiment trends directly in your Swiftask workspace.

Advanced features for your exchanges

Our AI engine evaluates not just keywords, but also emotional context, urgency, and the intent behind every message.

Target connector: The agent performs the right actions in insertchat based on event context.
Automated actions: Automatic scoring of every conversation. Classification by tags (positive, neutral, negative). Churn intent detection. Real-time alerts on frustration spikes. Automated qualitative report export.
Native governance: All analyses are centralized to facilitate service quality monitoring.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-insertchat@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

Value add for your management

1. Churn improvement

Detect early warning signs of dissatisfaction to act before the customer leaves.

2. Agent coaching

Identify friction points in exchanges to improve scripts and training.

3. Smart prioritization

Your teams prioritize the most sensitive conversations detected by AI.

4. Productivity gains

No more manual log reviews; AI gives you the summary of customer mood.

5. Strategic alignment

Base product decisions on the real feedback of your users.

Confidentiality and ethics

Swiftask applies enterprise-grade security standards for your insertchat automations.

Encrypted data: Your InsertChat exchanges are processed with the highest security standards.
GDPR compliance: Swiftask ensures full compliance in the processing of conversational data.
Internal governance: You retain full control over who accesses sentiment analyses.
Sovereign AI: No data is used to train third-party models without your consent.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Measurable impact on your support

Metric	Before	After
Log analysis	Manual audit (hours)	Real-time (instant)
Crisis detection	Late reaction	Immediate proaction
Customer satisfaction (CSAT)	Hard to correlate	Continuous improvement based on data
Manager productivity	Focus on volume	Focus on quality

Take action with insertchat

Turn conversational data into actionable insights to improve customer experience.