As an industry that runs on very thin profit margins, even slight improvements in efficiency can go a long way in helping the bottom line for telecom firms. Intensifying competition requires that firms invest their time, money and efforts into having a rich understanding of their network and customers. Moreover, infrastructure and business systems need to be made more dynamic in order to adapt to the evolving online and mobile environment.

In several telecom firms, huge amounts of data generated from millions of customers are dispersed across multiple data sources -with each business unit and product lines having their own set of data.

Business Intelligence systems help telecom firms to integrate data from multiple sources, refine data and provide an in-depth understanding into their network, customers and operations. An integrated data warehouse, good analytic capabilities and better visualization of data can help telecom firms in:

Developing a Holistic Picture
of their Customers

A single view of customers across product lines, purchasing channels and business units can help telecom firms build a coherent view which in turn helps them to not just understand the demographics but also to provides insights into their customer's personalities and behavioural patterns.

This deeper understanding can help firms differentiate their customers in a better way, making segmentation all the more enhanced.

Predicting Future
Behaviour

Companies can never really know for certain about the future, but a scientific analysis of past patterns can help firms predict the probability of future occurrences of similar scenarios. Firms can utilize this knowledge to take precautionary steps in preventing unfavourable scenarios as well as in customizing their approach towards segments of customers.

Deriving Optimal
Solutions

A deeper understanding of their customers and communication networks help telecom firms make informed decisions with regards to their expansion plans and marketing strategies. A better understanding of which strategies offer a better bang for their buck can help them in better budgeting and enhanced ARPUs thereby directly affecting the bottom line.


Market Penetration
Analysis

Deploying new network infrastructure is an enormously expensive proposition. Therefore, analyzing networks thoroughly for expansion becomes absolutely critical for telecom firms. BI tools allow telecom firms to:

  • Understand market penetration by city or by circle and filter cities based on their penetration rates. Instead of struggling with enormous spreadsheets, BI presents users with an easy to comprehend visual view of networks
  • Understand which services are most preferred in which circle so as to optimize the role-out of services in a better manner
  • Predict the probability of network failure based on past occurrences so that measures can be taken to avoid such scenarios.

Retention and Churn
Analysis

Customer Churn is a real problem faced by all telecom firms. Retaining customers at minimal costs and maximizing revenue from each customer directly impacts the bottom line. But a lack of clear understanding of customer needs and behaviours leads to firms often coming up with undifferentiated renewal and retention offers. Better analytics helps telecom firms:

  • Segment their customers in a more meaningful manner, in terms of their behavioural patterns, personalities, social networks etc.
  • Understand who are the customers most likely to churn, when they are likely to churn and mostly importantly who would not otherwise churn unless they see a renewal offer from the firm
  • Understand the factors really affecting customer churn
  • Understand the negative effects of a customer churn on other customers in the network
  • Predict the future profitability of the customer and decide if it is worthwhile to spend money to retain them
  • Optimize retention offers in accordance to the needs of the individuals.

Up-Sell /
Cross Sell

Cross-selling and up-selling directly increase the ARPU and helps telecom firms enhance overall customer experience. But siloed data and separate data sources often leaves firms with little understanding on the actual needs of their customers and their social networks. A merged clean data source and good analytic capabilities can help firms:

  • Segment their customers in a more meaningful manner, in terms of their behavioural patterns, personalities, patterns in their usage of various services offered etc. For eg identifying early adaptors and their social network can help firms target the segment early on while rolling out new services.
  • Understand the social network and behavioural patterns of customers. For eg, a better understanding of the social circle of a customer and the products used by their group can help firms come up with tailor-made offers for the customer
  • Predict future profitability of a customer and decide which customer to target with cross-sell/up-sell offers