Optimizing effectiveness of content in electronic messages among a system of networked computing device
Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to optimize effectiveness of content in electronic messages as a function, for example, modifiable portions of the content. In some examples, a method may include publishing a first electronic message including data representing a subset of components of electronic message, identifying a performance criterion against which a performance metric may be monitored, monitoring a value of the performance metric, determining a match, and publishing a second electronic message.
1 . A method comprising: receiving data signals to cause formation of an electronic message; determining a component of the electronic message; identifying one or more message performance criteria with which to form the electronic message; characterizing a component to identify a component attribute; predicting the component attribute matches a message performance criterion to form a predicted component attribute; transmitting the electronic message including the predicted component attribute via a network for presentation and implementation on user interfaces on a number of computing devices; monitoring a range of values for a performance metric, including an engagement rate, associated with a number of multiple forwarding events associated with propagated electronic messages, the performance metric including a complexity value for the component attribute describing a reading level of a subpopulation of recipients; detecting a value of the performance metric is non-compliant; characterizing another component to identify another component attribute; predicting the another component attribute matches the message performance criterion to form another predicted component attribute; and transmitting an alternate electronic message including the another predicted component attribute via the network for presentation and implementation on the user interfaces on the number of computing devices, wherein the alternate electronic message with the another predicted component attribute being generated and transmitted as a social network-based message including data by a publishing optimizer when the value of the performance metric is detected as non-compliant, the data associated with the alternative electronic message being transmitted to publish the alternative electronic message in a data arrangement configured to present the predicted component attribute at a monitored point of time, the data arrangement being published in response to a time point selection, the alternative electronic message also being published, wherein the another predicted component attribute is configured to enhance a rate of propagation of the alternative electronic message to the computing devices, any of which is configured to propagate the alternative electronic message to other computing devices in parallel.
2 . The method of claim 1 wherein characterizing the component comprises:
classifying the component to identify the component attribute as one or more of a word, a phrase and a topic, and further classifying the component as associated with one or more of media type data and channel type data; and
tagging the component with metadata.
3 . The method of claim 1 wherein characterizing the component comprises:
applying a natural language processing algorithm to characterize the component in the electronic message to implement wording embedding to represent the component as a vector.
4 . The method of claim 1 wherein characterizing the component comprises:
determining a similarity between the component and one or more other components with which to substitute the component with at least one of the other components as an alternate component.
5 . The method of claim 4 wherein determining the similarity comprises:
determining a cosine similarity between vectors representing the component and the one or more other components.
6 . The method of claim 1 wherein predicting the component attribute comprises:
applying machine learning algorithm or a deep learning algorithm to form one or more clusters of data associated with the component attribute.
7 . The method of claim 6 wherein predicting the component attribute comprises:
predicting one or more performance curves based on the one or more clusters of data associated with the component attribute.
8 . The method of claim 1 wherein predicting the component attribute comprises:
predicting one or more performance curves based on the message performance criterion.
9 . The method of claim 1 wherein predicting the component attribute comprises:
predicting one or more performance curves to predict a level of engagement as a function of time.
10 . The method of claim 1 further comprising:
selecting the electronic message based on a first performance curve during a first interval of time; and
selecting another electronic message based on a second performance curve during a second interval of time.
11 . A system comprising:
a memory including executable instructions; and
one or more processors of a computer system that when executing the instructions causes the computer system to perform operations comprising:
receive data signals to cause formation of an electronic message; determine a component of the electronic message;
identify one or more message performance criteria with which to form the electronic message;
characterize a component to identify a component attribute;
predict the component attribute matches a message performance criterion to form a predicted component attribute;
transmit the electronic message including the predicted component attribute via a network for presentation and implementation on user interfaces on a number of computing devices;
monitor a range of values for a performance metric, including an engagement rate, associated with a number of multiple forwarding events associated with propagated electronic messages, the performance metric including a complexity value for the component attribute describing a reading level of a subpopulation of recipients;
detect a value of the performance metric is non-compliant;
characterize another component to identify another component attribute;
predict the another component attribute matches the message performance criterion to form another predicted component attribute; and
transmit an alternate electronic message including the another predicted component attribute via the network for presentation and implementation on the user interfaces on the number of computing devices, wherein the alternate electronic message with the another predicted component attribute being generated and transmitted as a social network-based message including data by a publishing optimizer when the value of the performance metric is detected as non-compliant, the data associated with the alternative electronic message being transmitted to publish the alternative electronic message in a data arrangement configured to present the predicted component attribute at a monitored point of time, the data arrangement being published in response to a time point selection, the alternative electronic message also being published, wherein the another predicted component attribute is configured to enhance a rate of propagation of the alternative electronic message to the computing devices, any of which is configured to propagate the alternative electronic message to other computing devices in parallel.
12 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
classify the component to identify the component attribute as one or more of a word, a phrase and a topic, and further classifying the component as associated with one or more of media type data and channel type data; and
tag the component with metadata.
13 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
apply a natural language processing algorithm to characterize the component in the electronic message to implement wording embedding to represent the component as a vector.
14 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
determine a similarity between the component and one or more other components with which to substitute the component with at least one of the other components as an alternate component.
15 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
determine a cosine similarity between vectors representing the component and one or more other components.
16 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
apply machine learning algorithm or a deep learning algorithm to form one or more clusters of data associated with the component attribute.
17 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
predict one or more performance curves based on the one or more clusters of data associated with the component attribute.
18 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
predict one or more performance curves based on the message performance criterion.
19 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
predict one or more performance curves to predict a level of engagement as a function of time.
20 . The system of claim 11 wherein execution of the instructions by the one or more processors of the computer system causes the computer system to perform operations further comprising:
select the electronic message based on a first performance curve during a first interval of time; and
select another electronic message based on a second performance curve during a second interval of time.