SYSTEM AND METHOD OF ANALYZING SOCIAL MEDIA TO PREDICT THE CHURN PROPENSITY OF AN INDIVIDUAL OR COMMUNITY OF CUSTOMERS
First Claim
1. A computer implemented method of collecting/mining data relating to social media influence around a customer, and analyzing said data to predict a customer'"'"'s predisposition to either leave a subscription or a service or reduce his/her engagement with a subscription or a service which comprises:
- a) receiving a plurality of social media inputs associated with the customer;
b) determining a churn probability for the customer; and
c) performing an action based on the determined churn probability.
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Abstract
A system and method for mining social media signals and cues i) created by a user (for example, a customer) and/or ii) to which the user is exposed (the “data”), and for processing that data as it relates to a service (including a fee or subscription-based service), in order to predict the user'"'"'s predisposition or likelihood to either leave the subscription or the service or reduce his/her engagement with the subscription or the service.
61 Citations
23 Claims
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1. A computer implemented method of collecting/mining data relating to social media influence around a customer, and analyzing said data to predict a customer'"'"'s predisposition to either leave a subscription or a service or reduce his/her engagement with a subscription or a service which comprises:
- a) receiving a plurality of social media inputs associated with the customer;
b) determining a churn probability for the customer; and
c) performing an action based on the determined churn probability.
- a) receiving a plurality of social media inputs associated with the customer;
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2. A computer-implemented method to characterise social influence and to predict behavior of a user, said user being part of a social network which comprises a) creating a dynamically updatable social influence profile of the user, b) predicting future behavior of the user based on influence given by the user and received by the user from his social circles, and thereafter c) predicting the user'"'"'s predisposition to either leave a subscription or a service or reduce his/her engagement with a subscription or a service.
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3. A computer implemented method of collecting/mining data relating to social media influence around a customer, and analyzing said data to predict a customer'"'"'s predisposition to either leave a subscription or a service or reduce his/her engagement with a subscription or a service comprises:
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a) identifying a social media profile of the customer; b) comparing customer and his social media profile to clusters of customers, based upon similar social media profiles (“
cohorts”
); andc) calculating predicted churn behavior of the customer, based upon known churn behavior of cohorts. - View Dependent Claims (4, 5)
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6. A system, comprising:
- an information module that is configured to identify a user of a service;
a probability module that is configured to determine a churn probability for the user of the service; and
an action module that is configured to perform an action based on the determined churn probability. - View Dependent Claims (7)
- an information module that is configured to identify a user of a service;
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8. A computer implemented method of designing an efficient customer retention program for managing customer churn among customers of a business, the customer retention program including an analysis of the causes of customer churn and identifying customers who are most likely to churn in the future, so that appropriate steps may be taken to prevent customers who are likely to churn in the future from churning, the method comprising:
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a) identifying a social media profile of the customer; b) comparing customer and his social media profile to clusters of customers, based upon similar social media profiles (“
cohorts”
);c) calculating predicted churn behavior of the customer, based upon known churn behavior of cohorts; and d) performing an action based on the predicted churn behavior of the customer.
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- 9. A computer-implementable method for predicting and delivery of churn signals for customers that are at risk of terminating their subscription and/or service to the customer retention units at the provider company, wherein the churn predictions are generated by analysis of full social media profiles of customers.
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17. A machine implemented system that predicts and delivers churn signals to customer relationship management (CRM) software of service-based or subscription businesses for customers who are at risk of cancelling their services which comprises:
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a) a processor system that lives on the CRM software as a plug in; b) a second processor that continuously monitors and processes SMPs of that company'"'"'s customers to find new churn signals; and c) a third processor with live communication between the first and the second processor and which delivers new signals from the first processor to the second as soon as new churn signals are predicted. - View Dependent Claims (18, 19, 20, 21, 22)
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23. A non-transitory, tangible computer-readable medium storing instructions adapted to be executed by a computer processor to perform a method for generating a customer churn prediction, for an entity in need of such prediction, said method comprising the steps of:
- extracting and receiving, by a churn prediction program executing on the computer processor, a variety of social media inputs;
pre-processing the social media inputs to identify relevant social media posts, data trends and social network structures (pre-processed data);
extracting and engineering features of the pre-processed data, such features comprising at least one of i) assessed social media postings, ii) assessed life events, iii) assessed engagement with the entity and competitors of said entity iv) assessed trend predisposition of customers to the entity based upon their prior churns, v) assessed one or more communities of customers to the entity and predisposition of the customers to the entity to churn based upon churn risk of the one or more communities;
create feature vectors based at least upon i) to v);
aggregating feature vectors into a database and creating churn model in the processor (churn model of aggregated features);
determining, by the churn prediction program executing on the computer processor, predicted churn behavior of any one customer to the entity based upon, the comparison of at least one feature vector of the any one customer to the churn model of aggregated features.
- extracting and receiving, by a churn prediction program executing on the computer processor, a variety of social media inputs;
Specification