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Automatic Big Data Machine Learning Marketing Solutions for Telecom

G-STAT BRAINs Marketing machine learning applications, help Telecom companies increase responses to outbound and inbound campaigns by up to 50% while shortening projects’ time-to-results from months to hours.

Telecom markets are reaching saturation.‎ ‎The level of customer acquisition is dropping, while ARPU is under intense pressure. One of the primary challenges is developing an effective customer retention management process. More customers are contacting the service centers and companies are offering a greater selection of retention rewards while the need to answer the following questions has increased:

  • Which customers are actually about to churn and which are complaining in order to obtain better deals?
  • What is the probability of every customer responding to each retention recommendation?
  • How customer response to retention reward will impact the customer’s ARPU?

Retention BRAINs allow Telecom companies to identify which customers are at high risk of churn and to offer them the retention recommendation that most likely to increase its revenue or bring about minimal erosion of its ARPU.

For low churn-risk customers, Sales BRAINs recommends what are the offers out of all products and services sold by the company (packages, add-ons, rate plans, VAS, handsets, etc.) that have the highest probability of increasing such customer’s ARPU.

Value BRAINs enables Telecoms to simulate the impact of different actions on the lifetime value of segments of customers as well as individual customers (such as migrating iPhone customers to Android handsets, migrating from rate plan A to rate plan B).

G-STAT BRAINs applications perform the retention optimization process as follows:

  • Automatic development and execution of dozens of churn prediction models based on product lines and customer segments, rather than a single churn model usually developed and deployed by the organization.
  • Automatic development and running of dozens of the response probability models for each customer for every retention recommendation or cross-sell offer (rate plans migration, handsets, etc.).
  • Automatic development and execution of dozens of churn prediction models based on product lines and customer segments, rather than a single churn model usually developed and deployed by the organization.
  • Personalized customer retention recommendation prioritization based on the offer which will produce the greatest expected revenue.
  • Transferring the retention recommendation to the organizational CRM system (through the campaign management tool used by the company) as the basis for operating effective and smart proactive and reactive targeted retention activities.

G-STAT applications enable marketing staff [without any statistical know-how] to develop and deploy complex statistical big data machine learning models through a user-friendly interface, in less than a day rather than the man-months and years currently required when using the data mining tools available on the market to obtain the same results.

G-STAT BRAINs applications can be deployed in a company within a few weeks, allowing it to improve its 1-to-1 retention process and showing quick ROI within 1-2 months.