During the initial discovery conversations, the client highlighted several operational gaps that limited the effectiveness of their recovery team.
High Manual Calling Effort
Recovery teams spent a large amount of time manually dialing consumers and logging outcomes. This slowed overall productivity and reduced the time available for cases that needed deeper attention.
Limited Multilingual Engagement
Many consumers were not comfortable speaking in English, which made conversations difficult. As a result, connect rates dropped and customer experience suffered.
Incomplete Data Capture
Key information, such as payment commitments or reasons for delayed payment,s was often recorded in an unstructured way or not entered at all. This created gaps that made follow-ups harder.
Lack of Real-Time CRM Updates
Since updates were added manually, CRM records frequently lagged. Delayed entries and occasional inconsistencies made it difficult to trust the data during decision-making.
Minimal Campaign Visibility
Supervisors did not have one central space to view campaign progress or call performance. This limited their ability to monitor activities and respond quickly when issues came up.
Compliance Concerns
Manual operations increased the risk of calling outside approved time windows or mishandling sensitive information. Without automated checks, compliance became harder to maintain consistently.
The client partnered with DataToBiz to create a multilingual voicebot that could automate outbound recovery calls, capture accurate consumer responses, and update CRM records without human intervention.
Outbound Calling Automation: Integrated with telephony providers (e.g., Twilio/Exotel) to initiate calls, apply retry logic, and log call outcomes in real time.
Dynamic Scripting: Personalized greetings and payment reminders using live CRM data (name, due amount, due date).
AI/NLP-Powered Data Capture: Extracted structured payment dates and classified delay reasons from open-text responses.
CRM Integration: Bi-directional, token-based API sync to log commitments, outcomes, and delay reasons automatically.
Multilingual STT/TTS: High-quality speech recognition and synthesis tuned for six languages and regional accents.
Campaign Management Portal: Role-based web interface for launching campaigns, monitoring live results, and exporting call records.
Compliance & Security: Role-based access control (RBAC), encryption, and configurable calling hours.
Modular Platform Design
The voicebot platform followed a modular design that combined calling automation, natural language understanding, multilingual speech processing, and CRM integration.
Automated Outbound Calling Setup
Outbound calling was powered through SIP trunk connections to telephony providers such as Twilio or Exotel. The system handled automated scheduling, retry logic, and calling windows that aligned with compliance requirements.
Context Aware Call Scripts
Dynamic call scripts were created from live CRM information so every consumer received context-specific reminders. When any profile lacked complete data, the voicebot applied fallback responses to maintain call flow.
Natural Language Layer for Accurate Responses
The natural language layer extracted and standardised payment dates from spoken responses and classified reasons for delay using transformer-based models. Speech recognition and speech synthesis were tuned for six languages and multiple regional accents to make the conversation natural and easy to follow.
Seamless CRM Integration
Two-way API integration ensured that every commitment, response, and outcome was recorded accurately in the CRM with proper field mapping, error handling, and audit logs.
Portal for Campaign Control and Monitoring
A role-based portal supported campaign launches, performance tracking, and data exports, with dashboards built for both desktop and mobile use. Continuous monitoring, version control, and automated updates kept the platform reliable over time.
Lower Manual Effort and Better Focus for Agents
Manual calling effort dropped sharply as the voicebot handled almost 70 % of repetitive outbound calls. Agents were able to shift their time toward complex conversations that needed human judgment.
Higher Consumer Engagement
Customer engagement improved as the voicebot supported multiple languages. Reach expanded by 60 %, connect rates increased, and the overall interaction became more natural for non-English speaking customers.
Accurate and Faster CRM Updates
CRM data remained accurate and nearly real-time because every commitment and outcome synced automatically. This removed errors and ensured the recovery workflow stayed smooth and dependable.
Clearer Campaign Oversight
Supervisors gained real-time visibility into every active campaign, making tracking and decision-making easier. Performance trends were clearer, and interventions could be planned without delay.
Stronger Compliance
Automated controls enforced the right calling windows and protected sensitive customer information. Compliance strengthened naturally as the system managed rules consistently across every campaign.
CONCLUSION
By introducing a secure multilingual voicebot, DataToBiz helped the client modernise its debt recovery function. The platform streamlined communication, captured reliable data, and gave supervisors far stronger visibility into day-to-day performance. These improvements allowed the team to scale their recovery operations with confidence while improving the overall experience for consumers.
Technology & Software
India
End to End Project Lifecycle Management
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