Abstract: Method and systems generate optimized and online targeted messages. Various campaign criteria are provided having different advertising or marketing goals that cause the delivery of targeted messages. Messages may be generated based upon customer data, customer preferences, life events, marketing campaigns, predictive models, and/or propensity scores. For instance, messages may be sent when a propensity threshold score is exceeded indicating a high likelihood of a milestone event, which may be indicative of customer behavior or an event that is relevant to the campaign goal, thereby sending more relevant messages to customers. A milestone propensity score may be calculated using a predictive modeling algorithm having weighted data variables, which may include data provided by the customer or accessed through various sources, such as monitoring customer online interactions with their permission.

Abstract: Method and systems generate optimized and online targeted messages. Various campaign criteria are provided having different advertising or marketing goals that cause the delivery of targeted messages. Messages may be generated based upon customer data, customer preferences, life events, marketing campaigns, predictive models, and/or propensity scores. For instance, messages may be sent when a propensity threshold score is exceeded indicating a high likelihood of a milestone event, which may be indicative of customer behavior or an event that is relevant to the campaign goal, thereby sending more relevant messages to customers. A milestone propensity score may be calculated using a predictive modeling algorithm having weighted data variables, which may include data provided by the customer or accessed through various sources, such as monitoring customer online interactions with their permission.

Abstract: Method and systems generate optimized and online targeted messages. Various campaign criteria are provided having different advertising or marketing goals that cause the delivery of targeted messages. Messages may be generated based upon customer data, customer preferences, life events, marketing campaigns, predictive models, and/or propensity scores. For instance, messages may be sent when a propensity threshold score is exceeded indicating a high likelihood of a milestone event, which may be indicative of customer behavior or an event that is relevant to the campaign goal, thereby sending more relevant messages to customers. A milestone propensity score may be calculated using a predictive modeling algorithm having weighted data variables, which may include data provided by the customer or accessed through various sources, such as monitoring customer online interactions with their permission.

Abstract: Method and systems generate optimized and online targeted messages. Various campaign criteria are provided having different advertising or marketing goals that cause the delivery of targeted messages. Messages may be generated based upon customer data, customer preferences, life events, marketing campaigns, predictive models, and/or propensity scores. For instance, messages may be sent when a propensity threshold score is exceeded indicating a high likelihood of a milestone event, which may be indicative of customer behavior or an event that is relevant to the campaign goal, thereby sending more relevant messages to customers. A milestone propensity score may be calculated using a predictive modeling algorithm having weighted data variables, which may include data provided by the customer or accessed through various sources, such as monitoring customer online interactions with their permission.

Abstract: A computer system for a website evaluation and recommendation tool is provided. The computer system has a platform, at least one input device, and a central processing unit in communication with the platform and the at least one input device. The central processing unit is configured to access a website and evaluate the website by assigning scores to a plurality of weighted criteria. The central processing unit may also be configured to generate an evaluation score for the website from the scores and determine whether the evaluation score meets a pre-defined standard. The central processing unit may further be configured to recommend changes to the website based on the evaluation score and the pre-defined standard.