Analytics – BPO Service Provider

-Solid Footings


Big Data – Drive science into actions through actionable insight

Data analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain. Data is extracted and categorized to identify and analyse behavioral data and patterns, and techniques vary according to organizational requirements.

The big data revolution is taking the world by storm and some studies have shown that when a company’s operations are informed by data analytics, profits rise by 5%-10%. Leveraging predictive data analytics is no longer a competitive advantage but rather a competitive necessity. Our big data is turned into meaningful and insightful reporting.

By deploying analytics, we not only reduce costs and improve efficiency for our clients but also help them swiftly achieve the strategic market breakthroughs essential for gaining—and sustaining—advantages over their competitors.

bpo service provider

Our use of analytics generates valuable business outcomes for clients in three ways. All businesses should aim for the same results with their outsourcing providers:

Improve operational engines

We provide clients a single source of high-quality, consistently-recorded data on performance of various functions.

Uncover hidden insights

We generate additional insights by tracking data across different parts of the organization, and use it to optimize outcomes or to balance competing objectives.

Innovate to drive top-line growth

We help clients manage data—from the front office, back office or both—to generate process innovations, improve time-to-market and increase revenue.

Most importantly we understand that as business process outsourcing (BPO) matures, so does the industry’s ability to improve outcomes for clients. Our research shows an industry moving toward a “cost-plus” value proposition that focuses on business impact, not just operational cost reduction.

-Analytical Customer Relationship Management (CRM)


Statistical modeling used to better understand and fully engage with customers while also maximizing profits on all channels.


Giving due credit to customers’ response models for marketing decreases the risk and increases the bottom line. We do this by producing a statistical measure. This ranks customers according to the likeliness of them responding to communication from your company.

Furthermore, Geocoding of customers and prospects, links target information to specific locals on interactive maps and allow your company a more hands-on and in-depth understanding of leverage patterns and relationships, not evident on charts and tables alone.


We focus our attention and efforts on constantly improving customer experience, as this is an integral strategic component of customer-driven business. The best way to acquire business and ensure a customer’s lifetime value increases, is not by meeting their expectations, but by exceeding them. Mango5 has built a reputable foundation by doing this.


  • Capture and record the thoughts, behaviours and attitudes of your customer base
  • Bring integral customer insights to the fore
  • Continuously enhance customer experience


This model uses strategic incentive to increase customer lifetime value and decrease lapsing/churning.

-Our Specialisation

Insurance clients acquired
Telecommunications fixed and mobile contracts acquired
Calls handled inbound and outbound to date
Higher customer returns
Longer customer lifecycles
Lower churn of client base

- Dynamic Services

  • Address Cleaning and Address Matching
  • Geocoding of data
  • Response models
  • Customer life time value models
  • Predictive dialler optimisation
  • Website traffic analytics
  • Data enhancements
  • Product profiling
  • Credit risk model enhancements

Business Intelligence

  • Unique services to suit customers’ individual needs
  • Customer intelligence capabilities
  • Human capital effectiveness
  • Operational operations and operational effectiveness

Outputs of Mango5

  • Increase revenue
  • Decrease costs
  • Use efficient time management
  • Improve expense management
  • Increase operational visibility

We build BI warehouses of the data to gain real time insight into the data and business. Machine learning software is used to develop predictive models, where they increase turnover or reduce costs.
The predictive tools are automated via software.
Technologies used : R , Python, Power Bi, .net.