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Analyze customer sentiment on Social Intents with AI

Swiftask connects your Social Intents chats to AI models to detect, classify, and analyze customer sentiment in real time.

Result:

Instantly identify dissatisfied customers and improve your service quality with actionable data.

Your Social Intents conversations are untapped goldmines

Every day, your agents handle dozens of chats on Social Intents. But without systematic analysis, you miss weak signals: customer frustration, product trends, or sales opportunities. Data remains buried in chat history.

Main negative impacts:

  • Delayed crisis detection: Unaddressed customer dissatisfaction can escalate quickly. Without proactive analysis, you often react too late.
  • Underutilized customer data: The overall sentiment of your customer base is invisible. You are navigating without qualitative performance indicators.
  • Manual analysis costs: Rereading hundreds of transcripts to assess satisfaction is impossible at scale for a support team.

Swiftask automates sentiment analysis on every message received via Social Intents. You get a clear score and automatic tags for every interaction.

BEFORE / AFTER

What changes with Swiftask

Without automated analysis

Your agents finish chats without knowing if the customer is truly satisfied. Managers must manually sample conversations to assess quality, which is time-consuming and subjective.

With Swiftask + Social Intents

Every chat is analyzed in real time by AI. If sentiment turns negative, an alert is sent to a supervisor. You have a global dashboard of customer satisfaction.

Enable Social Intents sentiment analysis in 4 steps

STEP 1 : Connect Social Intents to Swiftask

Authenticate your Social Intents account in Swiftask to enable chat stream reading.

STEP 2 : Configure the AI analysis engine

Choose the AI model and define sentiment scales (positive, neutral, negative) tailored to your business.

STEP 3 : Define automated actions

Create rules: for example, send a Teams notification if the sentiment is 'very negative'.

STEP 4 : Visualize your insights

Track the evolution of customer sentiment in real time via automatically generated reports.

Advanced features for your chats

AI analyzes tone, word choice, urgency, and the emotional context of every customer message.

  • Target connector: The agent performs the right actions in social intents based on event context.
  • Automated actions: Automatic chat classification (positive/negative). Emotional urgency detection. Frustration keyword extraction. Real-time alerts on critical chats.
  • Native governance: All data is aggregated to provide a macroscopic view of your customer experience.

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

Each Swiftask agent uses a dedicated identity (e.g. agent-social-intents@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.

Why analyze sentiment with Swiftask

1. Increased customer reactivity

Intervene immediately on conversations that are going poorly.

2. Continuous support improvement

Identify recurring friction points in your response processes.

3. Easier agent coaching

Use sentiment data to train your teams on complex cases.

4. Automated reporting

Stop wasting time creating satisfaction reports manually.

5. Seamless integration

Works in the background without disrupting your agents or customers.

Data security and privacy

Swiftask applies enterprise-grade security standards for your social intents automations.

  • Guaranteed privacy: Your chat data is processed according to the strictest GDPR standards.
  • Environment isolation: Each workspace is completely isolated to ensure the security of your insights.
  • Enterprise compliance: Swiftask meets the security standards required for businesses of all sizes.

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

RESULTS

Measure the impact on your CX

MetricBeforeAfter
Dissatisfaction detection timeSeveral days (or never)Instantaneous
Customer data qualitySubjective and fragmentedObjective and exhaustive
Analysis capacityLimited sampling100% of conversations

Take action with social intents

Instantly identify dissatisfied customers and improve your service quality with actionable data.

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