The agent captures both structured ratings and open-ended qualitative feedback across all dimensions of network experience. Typical categories include voice call quality (clarity, dropped calls, connection time), data speed satisfaction (streaming, browsing, downloads), coverage reliability (indoor, outdoor, commute), and overall service perception. Each category uses a combination of numerical scales, multiple choice options for specific scenarios, and free-text fields for detailed descriptions. The adaptive conversation flow means a subscriber reporting 5G speed issues gets specific follow-ups about location, device, and time of day, while a subscriber who is generally satisfied moves through the survey in under a minute.

Traditional telecom CSAT programs rely on IVR prompts after support calls, quarterly email surveys, or web portal pop-ups. These methods suffer from low response rates (2-5%), response bias toward extremely satisfied or dissatisfied subscribers, and delayed data that arrives weeks after the experience occurred. A conversational AI agent asks one question at a time in a chat-native format, adapts follow-ups based on previous answers, and can be triggered via SMS or in-app notification within minutes of a relevant event like a resolved outage or a support interaction. The result is 5-10x more responses, richer diagnostic detail on negative experiences, and real-time data that arrives while the issue is still actionable rather than in a quarterly report that lands on someone's desk two months later.

Yes. You configure one core feedback flow with your standard quality dimensions, then customize per region to reflect different network technologies (4G vs. 5G vs. fixed broadband), local coverage challenges, and regional service priorities. Each region is tagged automatically so responses route to the correct regional network team and roll up into a national-level dashboard. A market where you recently launched 5G might include questions about 5G availability and handoff quality, while a rural market focuses on basic coverage and voice reliability. All data flows into a single reporting view where your operations team can benchmark regions against each other and track improvement over time.

When a subscriber reports severe issues like persistent no-service zones, repeated dropped calls, or data speeds consistently below usable thresholds, the agent immediately sends an alert to the designated network operations or customer experience team through email, Slack, or your preferred notification channel. The alert includes the subscriber's location data, the specific scores and descriptions they provided, their account segment, and their tenure. This gives your team a window to respond proactively, whether that means opening a network investigation ticket for the reported location, offering a service credit, or escalating to a retention specialist before the subscriber decides to switch carriers.

Tars connects natively with CRMs like HubSpot, Salesforce, and Zoho CRM, and integrates with hundreds of additional tools through Zapier and webhooks. For telecom-specific platforms, the webhook API supports custom integrations with any BSS/OSS system that accepts HTTP requests, including network management platforms, trouble ticketing systems, and subscriber data warehouses. Feedback data can flow alongside your existing subscriber records so your CX and network teams can correlate experience feedback with account data like plan type, tenure, device model, and usage patterns, enriching your understanding of which subscriber segments are most impacted by specific network issues.

Tars is SOC 2 Type 2 certified, ISO 27001 compliant, and supports GDPR-compliant data handling including consent capture and data deletion. All data is encrypted both in transit and at rest. For telecom operators subject to sector-specific regulations like FCC data privacy rules in the US or TRAI guidelines in India, the platform supports configurable consent flows and data retention policies. Subscriber feedback, including any personally identifiable information like phone numbers or account IDs, is stored securely and accessible only to authorized team members. You can also configure the agent to collect anonymous feedback when you want honest network quality assessments without tying them to specific accounts.

Most subscribers complete the feedback conversation in 60-90 seconds. The adaptive question logic ensures satisfied subscribers move through quickly with simple ratings, while subscribers who flag specific network problems get targeted follow-up questions that capture the diagnostic detail your engineering teams need to investigate. This is significantly shorter than traditional multi-page telecom surveys, which is a major reason conversational agents achieve dramatically higher completion rates. The chat format also feels less burdensome because subscribers see one question at a time rather than a wall of 20 questions on a single page.

Tars supports multi-language conversations, which is essential for telecom operators serving diverse subscriber bases across multiple markets or within multilingual countries. The agent can conduct the entire feedback conversation in the subscriber's preferred language, whether that is English, Spanish, Arabic, Hindi, or dozens of other supported languages. Multilingual support ensures you capture representative feedback from your full subscriber population rather than only the segment comfortable responding in a single language, which is critical for operators in markets like the Middle East, Southeast Asia, or multilingual European countries where subscriber bases span multiple language groups.