Showing posts with label Big Data Analytics. Show all posts
Showing posts with label Big Data Analytics. Show all posts

Monday, 7 August 2023

How big data analytics can empower BPOs?

The changing dynamics of the digital platform has a direct impact on businesses. The emergence of disruptive technologies have led most companies to rethink and act upon their digital strategies. The rise of Social Media, Analytics, and Cloud- collectively called SMAC – has made it imperative for companies to metamorphose and adapt to these changes in order to meet the challenges of tomorrow. Most companies are now leaving behind legacy business models and taking steps towards digital transformation by adopting SMAC or Big Data analytics in particular, in order to gain competitive advantage.


There has been much buzz around Big Data and how it is helping companies enhance their business productivity and extend better services to their customers. Internet users leave digital footprints behind through their online activities and this leads to the generation of a huge amount of structured and unstructured data – collectively known as Big Data. According to studies, as much as 2.6 Exabyte of data is generated every day around the world and about 90% of the data in the world today has been generated in the past two years. Mining and analysis of this data can provide invaluable insights that can help companies, especially those in the BPO sector, offer better services to their clients.

Evolution of the Contact Centre

BPO companies and their clients are sitting on gold mines of data, which can be extracted and analysed to deliver critical information. The advantage that Big Data offers is that of predictive analysis. More and more companies are now relying on predictive analysis than reactive analysis to make business more productive and offer better customer service. With the gold rush that disruptive technologies have created, businesses are finding it strategically more advantageous to take a proactive approach in handling problems and discovering opportunities.

BPO businesses can highly profit from Big Data analytics because of the volume of data they gather. By analysing current data, they can generate strategic insights for their clients and build better customer relationships. The rise of disruptive technologies have completely reshaped BPO-customer relationships now. Businesses now need to focus more on reinforcing customer relationships by mapping customer preferences and delivering more personalised services. And data can be instrumental in achieving this end. According to reputed research firm Gartner, 70 per cent of the most profitable companies will be relying on Big Data for real time predictive analysis by the year 2016.

Predictive analytics can help in analysing customer preferences and derive insights into behaviours and attitudes which can be used to aid in furthering better customer relations. Besides building a healthy customer relationship, predictive analytics can also help in improving customer satisfaction. With the information derived from analytics, BPOs can design targeted programmes by identifying customers who will most profit from their campaigns and focus on one-to-one customer interactions.

There are other ways too in which BPO entities can benefit from predictive analytics. With this technology, BPO entities can help their employees meet key metrics by accurately identifying key service demands and provide deliverables accordingly. Consequentially, businesses can maximise their work force and promote employee productivity at the same time.

This is particularly true for BPO centres that provide voice calling services. Knowing the customer’s communication preferences based on his personality will help BPOs put the customer with the right executive who can cater to his requirements. With the right permutation and combination, better productivity can be achieved from operations as the customers get what they want and the agent feels more productive on delivering the right service.

Predictive analytics can also play an important role on servicing newly introduced products. It can provide useful insights into the response of the target audience to a new service or product for brands. BPOs that will deploy predictive analytics will not only be able to deliver better business outcomes but also help their clients make smarter decisions.

There are several BPO providers who have come to realise the value of being able to mine out useful information from the huge volumes of transactional data they handle every day. In the long run, the quality of services provided by a BPO can be greatly differentiated using predictive analysis. This can play as a differentiator in business and hence lead to more business wins for a particular company.

Analysis of transactional data provides clients with actionable insight into their business operations – enabling them to improve working capital management, claim full discounts from their providers for paid-within-terms invoice processing or increase customer acquisition, satisfaction and retention, for example.

Brands are always on the hunt for new ways to add value to the services they bring to customers. As the consumers’ standards of good customer service continue to rise, brands must always be, or at least try to be, one step ahead of upcoming trends. Keeping up with the demands of the market means innovating constantly and creating unique strategies to stand out.

Thanks to the emergence of data analytics, brands now have a way to personalize the customer experience like never before.

As per a recent research by IT major Accenture, which also has its presence in the BPO sector, about 42 per cent of high performing BPOs, which are the ones that get full value from their BPO relationships said that analytics is a major component in their service delivery package.

Clearly, Big Data is the newest source of value creation in a business and it’s time that the BPO sector gears up for adopting this new technology as meaningful information culled from analytics deliver real outcomes, which can be critical for clients. Data science, a continuously growing field, has given birth to several forms of analytics processes with myriad applications for brands, including customer service, sales, and marketing. Familiarizing yourself with the many forms of analytics can help you make business decisions that would improve the customer experience.

How data scientists make an impact in BPO industry?

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.