Customer emotional state analysis for optimized financial transactions

The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods for optimized communications based on a customer emotional state. In aspects of the system and method, a customer social media account is analyzed for past social media posts. Customer emotional states are determined for the past social media posts. The past social media posts are also associated with financial transactions made by the customer such that emotional states are linked to specific financial transactions. The system and method monitor the customer social media account for new social media posts. A new social media post can be detected. An emotional state can be determined for the new social media post. The system and method collect the financial transactions with the same emotional state. The system and method generate an offer for similar products and/or related to the financial transactions. The offer is communicated to the customer.

BACKGROUND

Customers receive a large number of offers and/or advertisements such that customers generally ignore, or do not pay enough attention to the offers and/or advertisements (simply referred to as offers). The offers are often generic in nature and do not address the customer's specific needs at the time. Further, the offers can be ignored due to the customer's present mood. Financial institutions and other offer providers waste resources generating and sending the offers that customers will most likely ignore due to their emotional state.

BRIEF DESCRIPTION

The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods for optimized communications based on a customer emotional state. In aspects of the innovation, a customer social media account is analyzed for past social media posts. Customer emotional states are determined for the past social media posts. The past social media posts are also associated with financial transactions made by the customer such that emotional states are linked to specific financial transactions. The innovation monitors the customer social media account for new social media posts. A new social media post can be detected and an emotional state can be determined for the new social media post. The innovation collects the financial transactions with the same or similar emotional state. The innovation generates an offer for similar products and/or related to the financial transactions. The offer is communicated to the customer.

In aspects, the subject innovation provides substantial benefits in terms of tailoring offers and/or advertisements for the individual customer. Further, there is a benefit in increasing the likelihood of a response to the offer using knowledge of customer's emotional state. These and other benefits of the innovation will be better understood upon a review of the detailed description infra.

DETAILED DESCRIPTION

With reference toFIG. 1, an example input/output diagram100for generating offers based on a customer emotional state is depicted. A customer social media datapoint110is detected by an emotional state component120. The customer social media datapoint110can be data shared by the customer to a social media website or social media platform. For example, a social media datapoint110can be a post to a customer's Facebook account and/or wall. The social media website may be any communication shared by the customer that is for consumption by family members, friends, and/or aquantinces of the customer. In some cases, the communication shared may be viewable by anyone (e.g., the general public).

In the situation where the communications is posted to the social media website or social media platform and is viewable by anyone (e.g., not password protected or restistrited from viewing), the communications may be collected by monitoring the sites. In cases where the communication is protected through various forms of security (e.g., password protected), the customer may have provided prior authorization for the collection of communications in order to facilitate data collection as described herein. The social media communications may be linked to the customer based on email alias information, phone number information, internet protocol address, or other manners of identifying a source of electronic communication.

It is noted that in accordance with one or more implementations described in this disclosure, users may opt-out of providing personal information, demographic information, location information, proprietary information, sensitive information, social communication information, or the like in connection with data gathering aspects. Moreover, one or more implementations described herein may provide for anonymizing collected, received, and/or transmitted data. Further, a user may opt-out of providing information at any time, regardless of whether the user previously opted-in to providing the information.

The emotional state component120monitors the customer's social media account for new social media datapoints110. The emotional state component120determines the customer's emotional state based on one or more of the social media datapoints110. The emotional state component120can determine the emotional state using implicit and/or explicit means. For implicit determination of the emotional state, in one embodiment, the emotional state component120can use machine learning or historical analysis and/or algorithms to make the determination. The emotional state component120accesses data sources130to determine the emotional state of the social media datapoint110.

In one embodiment, the emotional state component120utilizes machine learning of historical data to facilitate emotional state determination. The data sources130can include a social media account database140. The social media account database140includes previous social media datapoints. The social media account database140includes further information about the social media datapoints. The information can include time, location, person tags, business tags, hashtags, or the like.

The emotional state component120analyzes the social media account database for content to match with a root word database150. The root word database150is a collection of trigger words indicative of a specific emotional state of the customer. For example, a trigger word may be happy, sad, angry, or the like. The emotional state component120parses a social media datapoint for root words. The emotional state component120matches a trigger word in the root word dictionary150. The root words in the root word dictionary150are each associated with corresponding emotional states. The emotional state component120associates the social media datapoint having the trigger word with the customer emotional state associated with the trigger word found in the root word dictionary150. For example, a social media datapoint includes the word “exam.” Exam is matched in the root word dictionary150and is determined to be associated with apprehension. In another embodiment, the social media datapoint include a separate emotional state tag. For example, Customer A may post “Customer A is feeling angry” where “angry” is selected from suggested emotions for Customer A to explicitly convey in the social media datapoint.

The emotional state component120can provide a determined emotional state160for the detected customer social media datapoint110to an offer component170. The offer component170matches the determined emotional state160of the social media datapoint110to an offer. The offer component170can utilize machine learning and/or historical analysis or the like to determine an offer best suited to convey to the customer.

The offer component170analyzes the social media account database140in view of a financial institution database180. The financial institution database180includes financial transactions of an account associated with the customer. The financial institution database180includes information about the financial transactions. The information can include type of transaction, items purchased, an offer associated with the transaction, transaction time, and the like.

In one embodiment, the offer component170matches a social media datapoint to a financial transaction. The social media datapoint is matched temporally to a financial transaction. The offer component170associates the social media datapoint with the financial transaction such that the datapoint is assumed to be a factor in causing the financial transaction or vice versa.

In one embodiment, the offer component170determines a time of a financial transaction. The offer component170searches social media datapoints on the social media account database140that are within a frame of the time of the financial transaction. The offer component170finds a social media datapoint having at least one trigger word in the root word database150. The offer component170associates the social media datapoint with the financial transaction.

The offer component170generates an offer to communicate to the customer based on the previous financial transactions associated with social media datapoint emotional states. For example, a customer has previously purchased ice cream after posting a social media data with a determined emotional state of sadness. Upon determination of a new social media datapoint with a sadness emotional state, the offer component170generates an offer for ice cream coupons or other ice cream products and/or products associated with a previous purchase. The offer component170communicates the offer190to the customer. The communication can be made over email, text message, API notification through social media or mobile phone application or the like.

With reference toFIG. 2, and continuing reference toFIG. 1, a component diagram of the emotional state component120is depicted. The emotional state component120includes a monitoring component210. The monitoring component210continuously checks the social media account database140to detect new social media datapoints.

The new social media datapoints may be for a specific customer or across a set of customers. For example, details related to an inferred emotional state of a customer and an associated financial transaction may be observed and retained in a database. In another example, details related to an inferred emotional state of another customer and its associated financial transaction may be observed and retained in the database (or in another database). Thus, if an inferred emotional state of one customer does not have an associated financial transaction, then patterns observed for other customers may be utilized to tailor an offer and/or advertisement for the one customer. The patterns of other customers may be utilized if the patterns match across a threshold level of customers (e.g., more than 60% of customers purchase ice cream when their inferred emotional state is “stressed.”).

The emotional state component120includes a networking component220. The networking component can connect to a mobile network, wired LAN, wireless LAN, an internet network, or the like to transmit communications. The networking component220connects to a transmission server to send and receive communications, alerts, or the like to and from a user device. The mode of the communication can be text, SMS, email, push notification via an API interface, or the like. The user device installs an application such that the communications activate the application on the user device when the transmission server sends a communication to the user device.

The emotional state component120includes a parsing component230. The parsing component230analyzes social media datapoints on word by word or phrase level. The parsing component230separates out trigger words for matching with entries in the root word database150, as described above.

With reference toFIG. 3, and continuing reference toFIG. 1, a component diagram of the offer component170is depicted. The offer component170includes a networking component310. The networking component can connect to a mobile network, wired LAN, wireless LAN, an internet network, or the like to transmit communications. The networking component310connects to a transmission server to send and receive communications, alerts, or the like to and from a user device. The mode of the communication can be text, SMS, email, push notification via an API interface, or the like. The user device installs an application such that the communications activate the application on the user device when the transmission server sends a communication to the user device. The networking component310is in communication with the purchase system120to send and receive information, commands, actions, or the like.

The offer component170includes a matching component320. The matching component320receives a determined emotional state from the emotional state component120. The matching component320associates the determined emotional state with an offer based on previous financial transactions completed by the customer.

The offer component170includes a communication component330. The communication component330receives the offer from the matching component. The communication component330sends the offer to the customer via the networking component310. The communication component330determines a communication mode with which to interact with the customer. In one embodiment, the communication component330accesses a user profile to determine a communication mode preference. The communication mode can be social media post, advertisement, text message, API notification, email, or the like.

In aspects, method400can begin at410by detecting a social media post. For example, a customer writes a new post to their Facebook account. At420, previous social media posts are analyzed for emotional states, e.g. emotional indicators. The historical social media posts are parsed for words indicative of a discreet emotional state. Continuing the example, the content of the Facebook posts, e.g. text, tags, or the like, is extracted and analyzed, e.g. the Facebook post “I have a test next week.” is parsed and the emotional state is determined to be “stressed” or “apprehension.”

At430, the previous social media posts are matched to a financial transaction. The posts are matched to the financial transaction using a time frame such that the posts and the transaction are relatively close together temporally. The temporal relationship assumes a cause/effect relationship between the two. In one embodiment, a database can be built with financial transactions matched to social media posts and customer emotional states. In the example, timestamps of the Facebook posts are matched to timestamps of financial transactions of the customer, e.g. credit card transaction, online purchases, or the like. The timestamps of each can be within a certain threshold of one another. When the Facebook posts are matched to the financial transactions, the match is recorded in a database such that they are linked. The database also associates the emotional states of each Facebook post such that the emotional states are associated to a financial transaction. In the example, the timestamp of post “I have a test next week.” is determined to be within a close time period of a credit card purchase of ice cream. The determined emotional state for the post, as stated above, is “stress.” The database records an association between ice cream and stress for future use.

At440, the present emotional state of the customer is determined based on the detected social media post. The detected social media post is parsed for emotional indicators to be matched to a discreet customer emotional state. In the example, the detected Facebook post states “I have a paper due tomorrow.” The post is parsed and determined that the phrase paper due tomorrow is associated with stress.

At450, the emotional state is matched to an offer. The matching can be determined using the built database associating emotional states with financial transactions specific to the customer. An offer is generated for a product similar to and/or related to a financial transaction associated with the determined emotional state of the detected social media post. In the example, the association between stress and ice cream is determined from the built database of associations. Offers for ice cream coupons are generated. At460, the offer is communicated to the customer. The offer can be sent over a transmission server to the customer's email address, text message/SMS, mobile phone application, social media account, or the like. Finishing the example, the ice cream offer is emailed to the customer. In one embodiment, the offer is sent within a predetermined timeframe after the Facebook post such that the likelihood the customer is still in the emotional state.

Still another embodiment can involve a computer-readable medium comprising processor-executable instructions configured to implement one or more embodiments of the techniques presented herein. An embodiment of a computer-readable medium or a computer-readable device that is devised in these ways is illustrated inFIG. 5, wherein an implementation500comprises a computer-readable medium508, such as a CD-R, DVD-R, flash drive, a platter of a hard disk drive, etc., on which is encoded computer-readable data506. This computer-readable data506, such as binary data comprising a plurality of zero's and one's as shown in506, in turn comprises a set of computer instructions504configured to operate according to one or more of the principles set forth herein. In one such embodiment500, the processor-executable computer instructions504is configured to perform a method502, such as at least a portion of one or more of the methods described in connection with embodiments disclosed herein. In another embodiment, the processor-executable instructions504are configured to implement a system, such as at least a portion of one or more of the systems described in connection with embodiments disclosed herein. Many such computer-readable media can be devised by those of ordinary skill in the art that are configured to operate in accordance with the techniques presented herein.

With reference toFIG. 6and the following discussion provide a description of a suitable computing environment in which embodiments of one or more of the provisions set forth herein can be implemented. The operating environment ofFIG. 6is only one example of a suitable operating environment and is not intended to suggest any limitation as to the scope of use or functionality of the operating environment. Example computing devices include, but are not limited to, personal computers, server computers, hand-held or laptop devices, mobile devices, such as mobile phones, Personal Digital Assistants (PDAs), media players, tablets, and the like, multiprocessor systems, consumer electronics, mini computers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.

Generally, embodiments are described in the general context of “computer readable instructions” being executed by one or more computing devices. Computer readable instructions are distributed via computer readable media as will be discussed below. Computer readable instructions can be implemented as program modules, such as functions, objects, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types. Typically, the functionality of the computer readable instructions can be combined or distributed as desired in various environments.

FIG. 6illustrates a system600comprising a computing device602configured to implement one or more embodiments provided herein. In one configuration, computing device602can include at least one processing unit606and memory608. Depending on the exact configuration and type of computing device, memory608may be volatile, such as RAM, non-volatile, such as ROM, flash memory, etc., or some combination of the two. This configuration is illustrated inFIG. 6by dashed line604.

In these or other embodiments, device602can include additional features or functionality. For example, device602can also include additional storage such as removable storage or non-removable storage, including, but not limited to, magnetic storage, optical storage, and the like. Such additional storage is illustrated inFIG. 6by storage610. In some embodiments, computer readable instructions to implement one or more embodiments provided herein are in storage610. Storage610can also store other computer readable instructions to implement an operating system, an application program, and the like. Computer readable instructions can be accessed in memory608for execution by processing unit606, for example.

Device602can include one or more input devices614such as keyboard, mouse, pen, voice input device, touch input device, infrared cameras, video input devices, or any other input device. One or more output devices612such as one or more displays, speakers, printers, or any other output device can also be included in device602. The one or more input devices614and/or one or more output devices612can be connected to device602via a wired connection, wireless connection, or any combination thereof. In some embodiments, one or more input devices or output devices from another computing device can be used as input device(s)614or output device(s)612for computing device602. Device602can also include one or more communication connections616that can facilitate communications with one or more other devices620by means of a communications network618, which can be wired, wireless, or any combination thereof, and can include ad hoc networks, intranets, the Internet, or substantially any other communications network that can allow device602to communicate with at least one other computing device620.