BPOs Enhance CX with AI
According to a 2023 release, Gartner expects that by 2025, 80% of customer service and support teams shall be utilizing GenAI in some way to enhance agent efficiency and customer experience. Every company, large or small, has a customer service team, whether in-house or outsourced. US alone employs three million customer service agents, who have a annual wage bill of $120 billion.
Even though a major expense, customer support is a major factor that influences brand equity, satisfaction with products and recommendations, loyalty, company revenue and reputation. It is then no surprise that the largest investment in AI is expected to be towards enhancing customer experience and retention, as it immediately impacts both bottom-line costs as well as revenue.
Let us look at some of the innovative ways in which AI is transforming BPO operations:
Automating Routine Tasks: AI is automating repetitive and mundane tasks like answering common queries or handling routine account updates and transactions. AI-powered chatbots or virtual assistants ensure 24x7 service availability without increasing workforce costs. It reduces the workload of human agents and speeds-up response times. High volume of interactions can be handled using automation with high efficiency, maintaining consistent performance during peaks without compromising on service quality.
Faster Response Times: AI reduces wait times and accelerates issue resolution. It retrieves relevant information for a quick analysis to resolve customer inquiries. It also can monitor and escalate unresolved issues in real-time, ensuring no customer is left waiting for a solution.
Seamless Experience Across Channels: Customers switch between channels and expect the same experience across all of them. AI enables businesses to deliver this consistent customer service across various media like phone, chat, web, email, social media and apps. Omnichannel solutions powered by AI integrate data, presenting a single customer view to agents and eliminating any need for repeating previous interactions.
Self-Service Options: AI solutions can be designed to provide guided users through troubleshooting steps or to provide personalized recommendations based on previous interactions. AI-powered knowledge bases, FAQs and chats empower customers to resolve their issues independently, without the need of interacting with an agent. This goes a long way in improving operational efficiency without an increase of workforce.
Reduced Abandonment Rates: GenAI driven bots reduce abandonment rates by offering more dynamic, personalized responses compared to traditional rule-based ones that rely on pre-programmed answers to a limited set of queries. GenAI bots are capable of generating unique and smart responses informed by the companyโs training materials and past customer interactions, allowing them to address a wider range of customer issues more effectively and providing solutions tailored to individual needs.
Strategic Impact
Besides operational improvements, integration of AI makes a strategic impact on BPO workforce management. When routine tasks are automated, managersโ and leadersโ time becomes available for driving higher-value decisions that impact revenue growth with a longer-term focus. Here, too, AI supports decision-making with data analysis, forecast future workforce needs and allocate resources more efficiently.
Some ways in which AI makes a more strategic impact are:
Streamlined Workforce Planning and Scheduling: AI-driven workforce management systems optimize staffing by predicting demand and adjusting schedules accordingly. This reduces the risk of overstaffing during low-demand periods or understaffing during peak times.
By aligning staffing levels with customer demand patterns, BPOs can avoid unwarranted labor costs and improve resource utilization, ultimately boosting both CX as well as profitability. In addition, flexible scheduling by factoring in employee availability and preferences ensures higher productivity and motivation. A more proactive workforce management strategy ensures better alignment between shift demands and agent availability.
Data-Driven Decisions: AI predicts trends by analyzing historical data and patterns as well as external factors. This allows BPOs to anticipate customer needs and allocate the right resources more effectively. With data driven decisions, they can optimize staffing levels to meet SLAs, address seasonality as well as improve employee productivity. Peak periods can be managed with minimum overtime, while maintaining expected resolution times.
Improved Employee Engagement: With AI-driven workforce management tools, tasks can be assigned based on agent skills, availability and performance metrics, ensuring that employees are engaged for tasks suited to their strengths. This intelligent allocation reduces employee stress and burnout while increasing productivity and job satisfaction. Optimized scheduling and shift management also offer flexibility to employees in managing work-life balance while meeting the organizationโs operational requirements.
Conclusion
Though the application of AI in customer service may be in its nascent stage, its potential is immense and transformative for the BPO industry.
Many customers still prefer interacting with live agents, and to answer that, generative AI is already finding advanced applications with human-like speech recognition and response capabilities. Some companies, however, are cautious and use AI only to enhance agent training rather than live customer interactions. Nonetheless, the broader trend is clear: AI is becoming an integral part of customer service strategies and shaping the future of BPO workforce management and customer experience.
(Authored by Vikas Wahee, Head of Solutions, BPM & ITES, FLOW from Kyvos )
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