The Power of Predictive Analytics
The Power of Predictive Analytics: Predictive Analytics in the Telecom Industry
We are living in a world of real-time predictions, in which being able to anticipate events and predict customers’ behavior means a competitive differentiator in the industry.
The telecom industry is one of the top changing environments in which technologies constantly evolve, and the market tends to quickly saturate. Therefore, being able to extract hidden value from recently discovered patterns and drive towards real time predictions will mean a competitive advantage for businesses.
About 28% of businesses are actively using Predictive Analytics, according to 2018 research from Dresner Advisory Services, reaching an all-time high importance. Predictive analytics is changing business by using statistical, modeling, Artificial Intelligence, Machine Learning, and predictive models which are applied to better understand customers and foresee buying patterns, potential risks, and likely opportunities.
In this regard, McKinsey’s Global Institute survey in the Telecom Industry also confirms that “analytics and machine learning techniques have a great impact on the Telecom Industry”, so businesses find great benefits across Predictive Analytics use cases.
Telecom enterprises can now optimize and uncover new statistical patterns which form the backbone of Predictive Analytics. This also allows the detection of insights to be made even faster enabling more effective and better decisions. It helps to analyze information to reveal key trends and correlations while predicting the likelihood of certain events.
However, the opportunity of Predictive Analytics is not only what we can predict but the fact that now we can do it. The historical data we currently analyze can probably become a prediction, but how do companies turn data into predictions?
Companies need either a team of data scientists’ to parse the information gathered, or a software tool powerful enough to format data files, link nodes, organize the information, build predictive models and make predictions visible. The Telecom industry is witnessing how powerful predictive tools are and how companies can benefit from them by providing a layout for proper planning and optimization of resources.
MedUX provides information through performance prediction models
In MedUX, we use Machine Learning and Artificial Intelligence to improve the proactive analysis and prediction capabilities with MedUX HOME and MOBILE, which measure the User Experience in fixed broadband and mobile networks respectively:
- MedUX predicts network performance and failures and works on its proactive optimization together with telecom providers. With the proper and real-time information, companies can handle customer expectations when outages occur and improve their services
- Foresee new trends in consumer behavior, by making sense of consumer data and building proprietary predictive models. These analyses are oriented to the extraction and presentation of aggregated insights for decision making.
- Personalize strategies to target individual consumers based on multi-model data, using radical personalisation and clustering techniques
- Predict lifetime value and risk of churn. Predictive analytics help on the construction of predictive models that enable to poll millions of customer observations and variables to identify issues. By acting upon the right identified recommendations, telecom companies can reduce customer churn.
Particularly, MedUX is working to provide information, through performance prediction models for mobile networks, to the telecom service providers so they can assess which parameters they should optimize if they want to improve their service in certain areas. This will allow to predict the mobile network status (4G/LTE), understand the relationship between measured parameters and being able to act upon them.
In this regard, MedUX has been able to identify that radio parameters, geographical area, and other environmental variables can influence the network performance predictions and the quality perceived by the customers and also help to identify the network elements that may be susceptible to improvement.
These analyses are delivered to providers, through MedUX’s own metrics, as well as technical and commercial QoS KPIs, to help providers focus their investment into the key points that really affect the end-user experience.
Telecom companies can benefit from a strategic advantage and predict not only the success rate of a new idea based on past customer preferences, but also target the right customer at the right time based on past behavior and choices. Then, there is a higher added value in using these tools that shift predictive analytics into commercial effectiveness and business growth.
The way in which people experience the network has become the main driver of customer satisfaction and loyalty. That means anticipating the client’s expectations and, when necessary, detecting problems before customers could complain.
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