How E-Commerce Is Cutting 100% of After-Call Work Using AI

TL;DR

• AI eliminates after-call work by automating tasks like data entry and summarization.
• After-call work time is reduced, allowing agents to focus on customer interactions.
• AI reduces after-call work, boosting efficiency and allowing agents to handle more calls
• Response times improve by minimizing after-call work and streamlining processes.
• Productivity is boosted as AI reduces after-call work, enhancing agent performance.

After-call work (ACW)—the time agents spend documenting customer interactions, updating CRM systems, and completing other administrative tasks post-call—has long been a thorn in the side of contact centers. 

While ACW is essential for maintaining accurate records and ensuring a seamless customer experience, it can significantly slow down an agent’s productivity.

For example, despite its technological capabilities, Amazon struggles with prolonged ACW due to manual documentation by agents after each customer interaction. This significantly impacts agent productivity, especially during high-volume periods like Black Friday.

This ongoing issue compounds the challenge of maintaining high-quality service while keeping operational costs in check.

For e-commerce companies, where the volume of customer interactions can be overwhelming, the impact of ACW is even more pronounced. 

With the pressure to provide quick, efficient service, the manual post-call tasks can become a bottleneck, draining time agents could otherwise spend resolving customer issues.

This creates a cycle of inefficiency: more ACW means fewer customer interactions and increased pressure on agents to clear out their post-call tasks, often leading to burnout and declining job satisfaction. 

As e-commerce grows, so does the need to rethink the traditional ACW process to keep up with the ever-growing customer expectations.

However, the question remains: How can e-commerce companies overcome this persistent challenge and streamline their processes without compromising customer experience or agent performance? 

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What is After-Call Work (ACW)?

After-call work (ACW) refers to the tasks that customer service agents must complete after speaking with a customer. 

These tasks typically include updating customer records, entering data into CRM systems, documenting the interaction details, scheduling follow-up actions, and performing other administrative duties. 

ACW is crucial in maintaining accurate records and ensuring customer issues are tracked and resolved effectively.

In e-commerce, where customer interactions are high in volume and require speed, managing ACW efficiently becomes a critical challenge. 

Long after-call times can slow the process, negatively impacting customer satisfaction and agent productivity.

Traditional ACW's Challenges: Why AI Automation Is Necessary in E-Commerce

Without AI automation, the ACW process in traditional call centers can be time-consuming and inefficient, especially for e-commerce enterprises that handle large customer queries.

Traditional ACW Process in E-Commerce

1. Manual Documentation: After each call, agents must record all relevant customer interaction details, update order status, track returns, or process customer requests.
2. CRM Updates: After-call data entry is critical for maintaining accurate customer records in CRM systems. However, this often requires the agent to switch between systems, leading to delays.
3. Follow-up Scheduling: If a follow-up is needed, agents must manually schedule callbacks or actions in the system.
4. Time Consumption: On average, the after-call work time per agent can take up to 45 seconds or more per call, depending on the complexity of the issue being handled. This time adds up, especially in high-volume call centers.

Challenges Faced by E-Commerce Companies Without AI for ACW Automation

How to Cut Down on After-Call Work in a Call Center

Reducing after-call work in a call center is essential for improving productivity and efficiency, especially in e-commerce. However, AI can help reduce ACW by,

• Automated Data Entry: AI tools automatically record and update customer information in the CRM, eliminating manual entry tasks. This significantly reduces the time spent on administrative duties, allowing agents to focus on customer interactions.
• Real-Time Transcription and Summarization: AI can instantly transcribe and summarize calls, ensuring that agents don’t have to review the entire conversation before entering call notes into the system.
• Automated Follow-ups: Instead of manually scheduling callbacks or follow-up tasks, AI can automatically set reminders or trigger next steps based on customer needs, such as sending a follow-up email or initiating a refund process.

AI automation is crucial for e-commerce companies to streamline after-call work (ACW) tasks, improve efficiency, and enhance customer satisfaction by reducing manual labor, increasing agent productivity, and ensuring accurate data entry.

Seamlessly integrate Convin’s AI across all your communication channels!

How E-Commerce Companies Are Automating ACW with AI

In the e-commerce sector, efficient customer service operations are paramount for millions of customers reaching out for support daily. ACW has become a significant bottleneck for contact centers. 

While necessary, ACW tasks consume valuable time that could otherwise be used to assist more customers.

For e-commerce businesses, the goal is clear: reduce after-call work time, enhance agent productivity, and ultimately improve customer satisfaction. 

A report by Metrigy indicates that 74.5% of companies planned to adopt generative AI for customer-related activities by the end of 2023, underscoring the rapid integration of AI in enhancing customer service.

Convin has harnessed the power of AI to automate ACW processes, enabling contact centers to overcome these challenges while achieving greater efficiency.

AI-Powered Solutions to Streamline the ACW Process

Convin understands the challenges e-commerce companies face in handling high customer interactions, highlighting the potential adverse effects of manual ACW processes on productivity and human error.

1. Automated Call Summarization

One of the core features of Convin’s AI-powered solution is automated call summarization. Instead of relying on agents to manually summarize calls or input details into the CRM system, Convin’s AI listens to the entire customer interaction, extracts key information, and generates a summary in real-time. 

This AI-generated call summary helps agents quickly move on to the next task without spending additional time post-call.

By automating the ACW process, Convin drastically reduces average after-call work time, typically spent transcribing or summarizing customer conversations.

2. Seamless CRM Integration

Integrating AI with CRM systems can significantly improve the efficiency of after-call tasks. Convin automatically updates customer profiles and records relevant details, such as the customer’s query, product information, and next steps, eliminating the need for agents to enter this data manually. 

This integration ensures the information is accurate, up-to-date, and accessible for future interactions.

Automating CRM updates ensures a seamless data flow, enhancing agent performance and decreasing the after-call work time associated with data entry.

3. Automated Follow-Up Actions

Follow-up actions are often a key part of after-call work. Convin automates follow-up scheduling based on predefined rules. 

For example, if a customer requests a refund, Convin will trigger an automatic follow-up task to ensure the refund is processed on time, removing the need for the agent to log that task manually.

This reduction in administrative burden helps agents focus on resolving customer issues instead of spending time planning follow-ups, leading to a more efficient ACW process.

AI Summarization and the Technology Behind It

Convin’s AI summarization leverages Natural Language Processing (NLP) and machine learning (ML) to transcribe, analyze, and summarize conversations in real-time. 

The technology scans speech for key details—such as customer queries, resolutions, and follow-up actions—and compiles this information into concise, actionable summaries.

The accuracy of AI transcription depends on several parameters, including context understanding, tone analysis, and language processing. 

With advancements in large language models (LLMs), AI can process complex language structures and diverse dialects, which is especially important in multilingual regions like India and the US, where people frequently switch between languages and dialects. 

A well-trained LLM can decipher these variations, ensuring that AI systems effectively understand and transcribe conversations in multiple languages, leading to more accurate summaries and smoother workflows.

Nick Jiwa, Founder and President of CustomerServ, notes that AI technologies can revolutionize call center performance in customer service by making it more efficient, productive, and personalized. However, human agents remain essential for empathy and complex issue resolution. ​- Expert Insight

Benefits of Automating ACW with Convin’s AI Solutions

Adopting AI-driven tools like Convin streamlines call center ACW and substantially benefits e-commerce businesses. These include:

1. Significant Reduction in After-Call Work Time

Convin automates post-call tasks, reducing after-call work time and improving productivity by focusing on customer interactions, reducing errors, and enhancing the overall customer experience.

2. Improved Agent Productivity

Convin automates after-call work, allowing agents to focus on customer service, reducing repetitive tasks, and increasing efficiency in the call center.

3. Enhanced Customer Experience

Convin's automation enhances customer experiences by reducing wait times and providing agents with comprehensive information, thereby reducing frustration for both agents and customers.

4. Increased Data Accuracy

Convin automates post-call data entry, reducing errors and ensuring accurate documentation of customer concerns, leading to better decision-making and increased customer satisfaction.

5. Reduced Agent Burnout and Turnover

Automating repetitive administrative tasks like post-call data entry reduces agent burnout and job dissatisfaction, resulting in lower turnover rates and increased engagement in customer problem-solving.

E-commerce businesses utilize AI-driven solutions like Convin to automate ACW, improve operational efficiency, and boost customer satisfaction. This technology allows for faster, more efficient customer service, ensuring businesses stay ahead in the competitive e-commerce environment.

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How Convin Reduces After-Call Work: A Numbers-Backed Breakdown

In e-commerce call centers, after-call work (ACW)—the few minutes agents spend after each call updating CRMs, logging summaries, and assigning follow-ups—might seem small. Still, it quickly eats into valuable time and budget. 

Now multiply that across thousands of daily calls, and it becomes clear: ACW is a hidden cost center.

Convin’s AI-driven automation minimizes this friction by shrinking the average after-call work time, helping companies serve more customers without increasing staff.

Let’s run the numbers.

Current Call Handling Without Automation

Most call centers still rely on agents to handle post-call tasks manually. Here’s what that looks like:

• Agent Pay Per Call: ₹35
• Calls Per Agent Per Day: 50
  
  • Daily Cost per Agent: ₹1,750
• Call Duration:
  
  • Talk time: 3.5 minutes
  • After-call work: 1.5 minutes
  • Total = 5 minutes per call

This means:

• Calls Per Hour: 60 ÷ 5 = 12
• Calls Per Day per Agent (8-hour shift): 96
• Total Agents: 1,500
• Daily Call Volume: 1,500 × 96 = 1,44,000 calls/day

Call Center ACW With Convin's Automation

After implementing Convin’s AI-driven ACW automation, here's how performance shifts:

• ACW Time Drops: 1.5 minutes → 30 seconds
• New Total Call Time: 3.5 + 0.5 = 4 minutes
• New Calls Per Hour: 60 ÷ 4 = 15
• New Calls Per Agent Per Day: 15 × 8 = 120
• Daily Call Volume (Same 1,500 Agents): 1,500 × 120 = 1,80,000 calls/day

Productivity & Cost Gains with Convin

• Extra Calls Per Day: 1,80,000 - 1,44,000 = 36,000 more calls/day
• Monthly Boost (22 workdays): 36,000 × 22 = 7,92,000 additional calls/month
• Annual Impact: 7,92,000 × 12 = 95,04,000 calls/year
• Cost Avoidance (₹35 per call): ₹33.26 crores/year—without hiring a single extra agent.

That’s the power of reducing after-call work time.

How Convin Enables These Gains

Here’s how Convin helps you reduce after-call work in a call center and turn it into a productivity win:

1. AI-Generated Call Summaries: No manual note-taking. Summaries are generated instantly.
2. Real-Time CRM Updates: Customer records are updated live without toggling tabs.
3. Intelligent Follow-Up Scheduling: Automatically identifies and schedules follow-ups during the call, removing manual task creation.
4. Shorter Call Wrap-Up Time: With ACW reduced by 60%, agents can handle calls faster, boosting volume and efficiency.
5. Better Accuracy & Compliance: Automated logs reduce errors and ensure consistency in customer records.
6. More Focused Agents: Less admin time lets agents focus on conversations, improving service and reducing burnout.

Why Convin Is Built for This

AI is proving to be a transformative tool for e-commerce companies, notably when eliminating after-call work (ACW). 

E-commerce companies can’t afford to lag in customer support. Automating your call center to eliminate 100% ACW is a must, given the competitive markets, seasonal volume spikes, and high customer expectations.

Convin helps you determine how to reduce after-call work in a call center by turning manual, time-consuming tasks into intelligent, automated processes.

And the best part? You don't need to hire more people to scale—just make better use of the team you already have. Let AI take care of the repetitive tasks so your team can focus on driving meaningful customer relationships.

If your company is ready to take the next step towards streamlined operations and improved customer satisfaction, it’s time to explore Convin. Schedule a Convin demo today.

FAQs

1. How can AI improve after-call work efficiency in a call center?
‍AI can automate after-call work tasks like call summarization, data entry, and follow-up scheduling, significantly reducing after-call work time, improving agent productivity, and enhancing customer satisfaction.

2. What parameters affect the accuracy of AI transcription?
‍The accuracy of AI transcription depends on factors like context understanding, language processing, tone analysis, and the model's ability to handle different dialects or regional language variations.

3. How does AI handle multilingual interactions in regions like India or the US?
‍AI systems, especially those using large language models (LLMs), are trained to process multiple languages and dialects, ensuring accurate transcription and understanding, even in multilingual environments like India or the US.

4. What is the role of NLP in AI summarization?
‍Natural Language Processing (NLP) helps AI understand, interpret, and generate human language, enabling summarization by extracting relevant details from conversations, improving data accuracy, and reducing manual input.