Around 1981, the term outsourcing entered our lexicons. Two decades later, we had the BPO boom in India, China, and the Philippines with every street corner magically sprouting call centers. Now in 2023, the industry is transitioning into an era of analytics, attempting to harness their sea of data towards profitability, efficiency, and improved customer experience.
The Information Ocean
The interaction between BPO agents and customers generates huge volumes of both structured and unstructured (text, audio) data. On the one hand, you have the call data that measures metrics such as the number of incoming calls, time taken to address issues, service levels, and the ratio of handled vs abandoned calls. On the other hand, you have customer data measuring satisfaction levels and sentiment.
Insights from this data can help deliver significant value for your business whether it’s around more call resolution, reduced call time & volume, agent & customer satisfaction, operational cost reduction, growth opportunities through cross-selling & upselling, or increased customer delight.
The trick is to find the balance between demand (customer calls) and supply (agents). An imbalance can often lead to revenue losses and inefficient costs and this is a dynamic that needs to be facilitated by processes and technology.
Challenges of Handling Data
When you are handling such sheer volumes of data, the challenges too can be myriad. Most of the clients wage a daily battle with managing these vast volumes, harmonizing internal and external data, and driving value through them. For those that have already embarked on their analytical journey, the primary goals are finding the relevance of what they built, driving scalability, and leveraging new-age predictive tools to drive ROI.
Delivering Business Value
The business value delivered from advanced Analytics in the BPO industry is unquestionable, exhaustive and primarily influences these key aspects:
1. Call Management
Planning agent resources based on demand (peak and off-peak) and skillsets accounting for how long they take to resolve issues can impact business costs. AI can help automate the process to help optimize costs. An automated and real-time scheduling and resource optimization tool that has led one of our BPO clients to a cost reduction of 15%.
2. Customer Experience
Call center analytics give agents access to critical data and insights to work faster and smarter, improve customer relationships and drive growth. Analytics can help understand the past behavior of a customer/similar customers and recommend products or services that will be most relevant, instead of generic offers. It can also predict which customers are likely to need proactive management. A real-time cross-selling analytics has led to a 20% increase in revenue.
3. Issue Resolution
First-call resolution refers to the percentage of cases that are resolved during the first call between the customer and the call center. Analytics can help automate the categorization process of contact center data by building a predictive model. This can help with a better customer servicing model achieved by appropriately capturing the nuances of customer chats with contact centers. This metric is extremely important as it helps in reducing the customer churn rate.
4. Agent Performance
Analytics on call-center agents can assist in segmenting those who had a low-resolution rate or were spending too much time on minor issues, compared with top-performing agents. This helps the call center resolve gaps or systemic issues, identify agents with leadership potential, and create a developmental plan to reduce attrition and increase productivity.
5. Call Routing
Analytics-based call routing is based on the premise that records of a customer’s call history or demographic profile can provide insight into which call center agent(s) has the right personality, conversational style, or combination of other soft skills to best meet their needs.
6. Speech Analytics
Detecting trends in customer interactions and analyzing audio patterns to read emotions and stress in a speaker’s voice can help reduce customer churn, boost contact center productivity, improve agent performance and reduce costs by 25%. AI tools have clients in predicting member dissatisfaction to achieve a 10% reduction in first complaints and 20% reduction in repeat complaints.
7. Chatbots and Automation
Thanks to the wonders of automation, we can now enhance the user experience to provide personalized attention to customers available 24/7/365. Reduced average call duration and wage costs improve profitability. Self-service channels such as the help center, FAQ page, and customer portals empower customers to resolve simple issues on their own while deflecting more cases for the company.
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