Predictive Analytics for
Telecommunications
No other industry is changing as fast as telecommunications.
As technology advances, service and pricing plans evolve, and the market becomes more saturated, telecommunications companies face increasing competition for customers. How are the top companies gaining a competitive edge in the marketplace?
Eight out of 10 telecommunication services companies on the S&P 500 use software from SPSS.
Predictive Analytics for Telecommunications
Helping leading telecommunication organisations to use SPSS predictive analytics to gain the insight they need to make better, faster, more effective decisions. By learning more about their customers, and those customers’ preferences and needs, telecom companies can be more successful in this highly competitive industry.
Telecoms that use predictive analytics are in good company. Eight out of 10 telecommunications services companies on the S&P 500 have used software from SPSS. More than half of the telecommunications companies on the Forbes 500, Forbes International 500, S&P 500, S&P Global 1200, and S&P Europe 350 have also used SPSS software.
Primary Analytics Solutions for Telecommunications
Design the analytical solution that is best for your business.
Analytical CRM
Helping telecommunications managers answer specific questions about their customers that ultimately help drive profitability through tailored marketing.
- Who: Which customer will buy this product?
- What: Type of interaction is most appropriate?
- Where: Through which touchpoint
- When: At what point in time?
- Why: Driven by what motivation?
Real-time scoring enables you to deliver the right offer to the right person through the right channel with the right message
Planning and Optimisation
A significant proportion of customers are on the wrong price plan and may be paying too much, increasing their likelihood to churn. Give them the best value bundle without impacting ARPU.
Helping telecommunication companies use optimisation to:
- Calculate the best price bundle for those at risk of churn.
- Enable significantly shorter planning and decision horizons, resulting in cumulatively better decision making
- Help the company increase revenues while minimizing the operational costs of running the service centre
Call Centre Optimisation
What is the target for the first call resolution?
How often do customers repeatedly contact the customer call centre to solve an urgent problem, but the line is always busy?
Predictive Analytics delivers tailored information to call centre agents that pull together the most important data on the client. The data is drawn from different operating systems and from different models to provide the most relevant up-to-date information to the call centre agents.
Predictive Analytics turns existing service call centres into revenue generators by accurately predicting sales opportunities, and retention risks, and delivering the appropriate scripts.
Fraud Detection
How much money is lost through fraud? How does your compare its peers?
There are many ways to avoid paying for telecommunications services, from stealing phone card numbers to bypassing phone circuitry. The result? Fraudulent activity costs the telecommunications industry billions annually, forcing some companies to go out of business.
Predictive Analytics helps in detecting telecommunications fraud in real-time.
In practice, this has led to:
- Significant ROI
- Significantly reduced telecommunications fraud for more than 150 telecommunication companies worldwide
- Saved money by enabling real-time fraud detection
Reduction in Bad Debt
Discover how to develop data mining applications to reduce bad debt. Use data to score customers’ credit risk, at the application stage, profile their normal or “at risk” usage and during the collections process when an account may fall into arrears.
Helping telecommunications organisations reduce risk by:
- An analytical methodology for identifying accounts profiles that have sequentially moved into and out of mercantile actions. These accounts are in severe debt and have had many collection actions such as service restrictions imposed against them
- An application and set of models that score phone accounts at the application stage to identify their propensity to never pay or to be an account that will go into a high level of arrears
Telecommunications Case Studies
Case Study – SiMobil
To prosper in a crowded market, telecom provider Si.mobil wanted to find new ways to cut costs and boost revenues. It identified customer retention and handset investment as key areas for improvement. Si.mobil deployed powerful data modeling software to reveal deep insights into customer behavior – predicting whether customers are likely to churn and which handsets they are likely to choose. Predicting churn helps Si.mobil boost retention by 10 percent, saving EUR1.1 million a year.
Case Study – Eircom
Ireland-based telecommunications service provider eircom wanted to reduce the business risk of customers switching to its competitors’ networks by understanding the factors predicting churn. The company worked with the Version 1 SPSS team to implement IBM SPSS predictive analytics software – enabling it to identify which customers were most likely to switch, and why.
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Version 1’s SPSS experts can consult and deliver a wide variety of analytics solutions across a broad range of industry sectors. Find out more at the links below.
