Systems and methods for determining customer metrics

A method performed by a computing system, the method comprising:

• accessing, by a customer metric management circuit, an account database storing a plurality of transaction statistics with respect to a financial account of a customer, at least one of the plurality of transaction statistics indicative of a first transaction between the customer and a merchant;
• accessing, by the customer metric management circuit, a social media database storing a plurality of social media activities of the customer;
• parsing information from a social media account associated with the customer to selectively retrieve relevant information, wherein the relevant information is (i) information that pertains to at least one of the merchant, to a competitor of the merchant, or to an industry in which the merchant conducts business, (ii) location information of the customer, and (iii) a sentiment exhibited by the customer towards the merchant or another business, wherein the information about the customer includes at least one of a birthday or a life event;
• identifying, by the customer metric management circuit, a residential address of the customer from the relevant information parsed from the social media account associated with the customer;
• determining, by the customer metric management circuit, an eligibility of the customer to receive an incentive based on the residential address of the customer, wherein the customer is eligible if the residential address is in the same geographic area as the merchant, and wherein the customer is not eligible if the residential address is in a different geographic area as the merchant, and wherein the system flags an ineligible customer as being ineligible, the flag provided to the merchant in any subsequent recommendations;
• determining, by the customer metric management circuit, a probability model of the customer based on the plurality of transaction statistics and the plurality of social media activities of the customer, the probability model indicating a first probability that the customer will conduct a second transaction with the merchant within a first future time period and a second probability that the customer will conduct the second transaction with the merchant within a second future time period ending later than the first future time period;
• adjusting a value of the probability model in response to detecting the sentiment exhibited by the customer, wherein the probability model increases responsive to detecting a positive sentiment and decreases responsive to detecting a negative sentiment, wherein the positive sentiment includes one or more of posting an online positive review of the merchant, detecting a regular pattern of transactions with the merchant over time, posting a negative review of a competitor of the merchant, living proximate to the merchant, or indicating interest in a web page or application associated with the merchant;
• determining, by the customer metric management circuit, a desirability score for the customer, wherein the desirability score is based on a tendency for the customer to post a positive merchant review, a tendency to post about a merchant experience on social media, a level of social media influence of the customer, and an income level of the customer;
• creating a special occasion designation for the customer, wherein the special occasion designation is based on at least one of a certain time of year that the customer has visited the merchant based on a transaction history of the customer and a known special occasion of the customer based on information retrieved from the social media account;
• recommending, by the customer metric management circuit, an incentive for the customer based on the eligibility of the customer, the probability model, the special occasion designation, and the desirability score;
• calibrating the incentive based on a probability threshold, wherein the incentive is greater when the probability model is less than the probability threshold by a higher value than when the probability model is less than the probability threshold by a lesser value;
• generating a dashboard comprising a customer metrics table, a probability model graph, and an incentives button, wherein the customer metrics table includes the first probability that the customer will conduct the second transaction within the first future time period and the second probability that the customer will conduct the second transaction within the second future time period, and wherein the probability model graph illustrates the probability of return of the customer over time;
• providing the dashboard to a merchant device;
• providing, by the customer metric management circuit, a recommendation to the merchant device based on the customer being eligible, the recommendation including the eligibility of the customer, the incentive, the desirability score, the special occasion designation, and the probability model;
• and
• providing, by the merchant device, the incentive to the customer during a checkout process by applying the incentive to a purchase price associated with a transaction.

A non-transitory computer readable media having computer-executable instructions embodied therein that, when executed by a customer metric management circuit of a computing system, causes the computing system to perform operations, the operations comprising:

• accessing, by the customer metric management circuit, an account database storing a plurality of transaction statistics with respect to a financial account of a customer, at least one of the plurality of transaction statistics indicative of a first transaction between the customer and a merchant;
• accessing, by the customer metric management circuit, a social media database storing a plurality of social media activities of the customer;
• parsing information from a social media account associated with the customer to selectively retrieve relevant information, wherein the relevant information is (i) information that pertains to at least one of the merchant, to a competitor of the merchant, or to an industry in which the merchant conducts business, (ii) location information of the customer, and (iii) a sentiment exhibited by the customer towards the merchant or another business, wherein the information about the customer includes at least one of a birthday or a life event;
• identifying, by the customer metric management circuit, a residential address of the customer from the relevant information parsed from the social media account associated with the customer;
• determining, by the customer metric management circuit, an eligibility of the customer to receive an incentive based on the residential address of the customer, wherein the customer is eligible if the residential address is in the same geographic area as the merchant, and wherein the customer is not eligible if the residential address is in a different geographic area as the merchant, and wherein the system flags an ineligible customer as being ineligible, the flag provided to the merchant in any subsequent recommendations;
• determining, by the customer metric management circuit, a probability model of the customer based on the plurality of transaction statistics and the plurality of social media activities of the customer, the probability model indicating a first probability that the customer will conduct a second transaction with the merchant within a first future time period and a second probability that the customer will conduct the second transaction with the merchant within a second future time period ending later than the first future time period;
• adjusting a value of the probability model in response to detecting the sentiment exhibited by the customer, wherein the probability model increases responsive to detecting a positive sentiment and decreases responsive to detecting a negative sentiment, wherein the positive sentiment includes one or more of posting an online positive review of the merchant, detecting a regular pattern of transactions with the merchant over time, posting a negative review of a competitor of the merchant, living proximate to the merchant, or indicating interest in a web page or application associated with the merchant;
• determining, by the customer metric management circuit, a desirability score for the customer, wherein the desirability score is based on a tendency for the customer to post a positive merchant review, a tendency to post about a merchant experience on social media, a level of social media influence of the customer, and an income level of the customer;
• creating a special occasion designation for the customer, wherein the special occasion designation is based on at least one of a certain time of year that the customer has visited the merchant based on a transaction history of the customer and a known special occasion of the customer based on information retrieved from the social media account;
• recommending, by the customer metric management circuit, an incentive for the customer based on the eligibility of the customer, the probability model, the special occasion designation, and the desirability score;
• calibrating the incentive based on a probability threshold, wherein the incentive is greater when the probability model is less than the probability threshold by a higher value than when the probability model is less than the probability threshold by a lesser value;
• generating a dashboard comprising a customer metrics table, a probability model graph, and an incentives button, wherein the customer metrics table includes the first probability that the customer will conduct the second transaction within the first future time period and the second probability that the customer will conduct the second transaction within the second future time period, and wherein the probability model graph illustrates the probability of return of the customer over time;
• providing the dashboard to a merchant device;
• and
• providing, by the customer metric management circuit, a recommendation to the merchant device based on the customer being eligible, the recommendation including the eligibility of the customer, the incentive, the desirability score, the special occasion designation, and the probability model;
• wherein the merchant device is configured to provide the incentive to the customer during a checkout process by applying the incentive to a purchase price associated with a transaction.