Contact center challenges
Multiple communication channels and fragmented data.
Agents work across several tools: telephony, email, messengers, and social media. Constantly switching between systems means even simple tasks take longer than necessary. Without real‑time guidance, basic inquiries are handled slowly or with errors.
Errors and agent handoffs.
There’s no unified knowledge base or complete customer history. As a result, agents give incorrect answers or transfer customers to other specialists, causing frustration.
Inefficient workload distribution.
During peak hours, agents are overloaded; at other times, they sit idle. Staff become stressed and turnover rises. It’s hard to staff correctly without precise volume forecasts.
Difficulty controlling quality.
With no automated reports or monitoring system, managers struggle to understand agent performance or identify the root causes of mistakes.
Key characteristics of a contact‑center automation colution
A unified workspace. Today’s market offers ready‑made omnichannel solutions that consolidate messengers, email, social media, and CRM into a single interface. All information about a given customer appears in one view, enabling smooth, real‑time resolution of inquiries.
Built‑in AI for customer service. AI can interpret the essence of a request and the customer’s history. It suggests canned responses, relevant knowledge‑base articles, and even gauges customer sentiment from voice. AI also provides real‑time translation, generates new KB articles from successful cases, and improves search accuracy.
Seamless expert collaboration. Complex issues that require specialist input are handled within a unified chat (including Microsoft Teams integration). This eliminates chaotic transfers: experts can join customer conversations, either visibly or behind the scenes and access the full chat history to provide guidance.
Predictive analytics for resource planning. To plan staffing, optimize service processes, and analyze inquiries, predictive analytics is critical. The system forecasts call volumes, even during seasonal peaks or promotions based on historical data. Agents see metrics on talk/listen time, sentiment, and issue topics. Managers receive detailed statistics across channels and queues to staff effectively.
Quality control and performance monitoring. Specialized modules track KPIs for agents and teams, identify strengths and growth areas, and flag calls requiring supervisor intervention. Call transcription and sentiment analysis provide rich material for objective feedback, detailed call reviews, and targeted training - directly boosting CSAT.
Metrics and outcomes
- Up to 40% operator time savings on lookup and customer‑data verification.
- 46% increase in customer satisfaction (CSAT) as customers receive fast, accurate support.
- 40% reduction in average handle time (AHT) thanks to a single interface and AI guidance.
- 50% boost in agent productivity: less routine work, more time for meaningful assistance.
- 66% of inquiries resolved automatically by AI handling routine requests.
- 3,850 agent hours saved per week (e.g., Lufthansa Cargo case).
- 30% lower total cost of ownership (TCO) through optimized, automated processes.
- 90% of essential features available out of the box for a rapid, low‑customization rollout.
