Loyalty system via specific user profiling

Abstract

The present invention relates to a loyalty system via specific user profiling that includes an external database of objective data, a tokeniser, a loyalty asset calculation protocol focusing on the characteristics selected by the user or pre-defined rules, and correlation and deduction means to generate additional data as an input for the loyalty asset calculation and specific rewards for the user. In a general embodiment, the system of the invention provides a unique user profile through correlation and deduction means, together with the other elements of the system, as well as specific rewards for the user.

Description

[0001] Loyalty system based on specific user profiling

[0002] Description

[0003] Technology Sector

[0004] The technological sector of this invention falls within the field of loyalty and fidelity management systems. More specifically, it relates to the creation and implementation of a loyalty system that utilizes specific user profiling. This system is framed within information technology, and more specifically, the development of logical processes and data analytics for specific purposes.

[0005] The invention focuses on the implementation of algorithms and advanced data processing technologies to segment and better understand user behavior and preferences. Furthermore, it uses machine learning and predictive analytics techniques to personalize rewards and loyalty programs based on each user's profile, interests, and behavior. This technological approach seeks to improve the efficiency of loyalty programs and promote greater user engagement in different industries, such as e-commerce, banking, hospitality, and other sectors where user loyalty is crucial to business success. The invention is based on the collection of transaction data, online behaviors, and user preferences, which places it at the intersection of data technology and customer relationship management (CRM).

[0006] Previous State of the Art

[0007] Patent CA 2919047 relates to a system and method for operating an integrated platform for customized loyalty programs, whereby multiple user retailers (or merchants) manage their own loyalty program as part of a larger master program, where members' points can be accumulated and redeemed at any participating user retailer store. The objective of such a system is to provide users with a single rewards card that they can use with multiple merchants (to accumulate and redeem their points), and to allow merchants to access centralized data of their members' spending and purchasing trend data stored in the system.

[0008] Likewise, patent document EP 3940618 discloses a method for managing a loyalty program comprising a predefined number of steps including at least one progression step and at least one reward attribution step, the method being implemented on a server comprising: - a reward database comprising, for each reward attribution step, a list of respective first type rewards distributed over several categories, and at least one first type reward attribution rule, and,° at least one second type reward, associated with a probability, The method comprises, when a user reaches a reward attribution step of his loyalty program, determining a reward to be delivered to the customer, said determination comprising: - performing a random draw of a type of reward to be delivered to the customer according to the probability associated with each second type reward,- if the random draw yields a second-type reward, determining the reward to be delivered as the obtained second-type reward, - if not, ° determining, according to the reward attribution step, the customer's purchase history and the first-type reward attribution rule, a first-type reward category, and ° determining the reward to be delivered to the customer as a first-type reward of the determined category.,

[0009] Also found in disclosures such as US patent application 2013 / 0311266 are a computer system and method that determines personalized transaction yields for one or more payment methods in real time and can automatically process the transaction in the optimally advantageous vehicle. Embodiments of the invention reveal a system and method that can assess and instantly generate reward offers for credit issuers and arbitrate, present, and reconcile those reward offers for consumers.

[0010] Specifically, WO 2005 / 088508 establishes an incentive program system and process for redeeming incentive program points. The system or process may be implemented using a computer-readable medium containing instructions for managing the incentive program account. The system includes a database for storing points associated with a first incentive program account and a processor that, in response to instructions from a program participant, redeems a number of the points either as a discount for a transaction or as points in a second incentive program account.The process includes storing points associated with a first incentive program account; identifying transactions available for redemption of an incentive program discount or a second incentive program account to which one or more points may be transferred; and either applying a discount to one or more of the transactions available for redemption of an incentive program discount or transferring points to the second incentive program account.

[0011] On the other hand, document US 2017 / 0017978 teaches a system, a computer-readable medium, and a method for managing interactions with third parties. The method includes identifying at least one transaction, where each transaction is between a first device and one of a plurality of second devices; obtaining transaction data for each identified transaction; identifying at least one redemption, where each redemption is between the first device and one of a plurality of third devices; obtaining redemption data for each identified redemption; determining, based on the transaction data and the redemption data, a total point value associated with the first device; and generating a machine-readable token for the first device, the token including each transaction identifier and each redemption identifier, the token further including metadata, where the metadata includes the determined total point value.

[0012] Finally, there are also developments such as the one proposed in WO 2019 / 222658 , which discloses systems and methods for processing reward accounts using a distributed ledger. According to one embodiment, at a node in a distributed ledger network for a plurality of reward program participants, the node comprising at least one computer processor, a method for processing reward accounts using a distributed ledger may include: (1) receiving a request to withdraw an amount of reward points from a customer account for a customer maintained by a distributed ledger; (2) retrieving, from the distributed ledger, a reward point balance for the customer account; (3) verifying that the reward point balance in the customer account is greater than the amount of reward points to be withdrawn;(4) write a deduction of the reward point amount from the reward point balance in the customer's account on the distributed ledger; and (5) cause a financial instrument to be issued in response to the deduction. Thus, it is clear that there remains a need for the development of a loyalty point or asset system based on user-specific profiling.

[0013] Description of the Invention

[0014] The present invention relates to a user-specific profiling loyalty system that includes means for connecting to or extracting from an external database, a tokenizer, an asset or reward calculation protocol focused on the characteristics selected by the user or pre-established rules, in addition to correlation and deduction means to generate additional data as input or source for estimating loyalty assets and user-specific rewards.

[0015] In a general embodiment, the system of the invention provides a unique profile of the user through the correlation and deduction means in conjunction with the other elements of the system, as well as specific rewards for the user.

[0016] In a general embodiment, the tokenizer and the loyalty asset calculation protocol may use as input any data provided by the connection or extraction means to an external database or by an external database itself.

[0017] In this regard, the system may receive and process selected features or pre-established rules, or it may create them based on data provided through the asset or reward calculation protocol and the means of connecting or extracting them from an external database, either jointly or independently.

[0018] Description of the Figures

[0019] Figure 1. Diagram of the system of the invention in a general aspect.

[0020] Detailed description

[0021] The present invention relates to a loyalty system comprising means for connecting to or extracting from an external database, a tokenizer, a protocol for calculating loyalty assets or rewards focused on the characteristics selected by the user or pre-established rules, as well as correlation and deduction means for generating additional data as input for calculating loyalty assets and specific rewards for the user.

[0022] In a general aspect of the invention, the connection or extraction means correspond to a mechanism that accesses general or specified data from an external database. Said connection and extraction means comprise a data structure updated by an ETL (extract, transform, and load), through which the data of specific users and related to a manager (or client) are normalized for inclusion in a database.

[0023] Specifically, this database is linked to a component that allows the system to access relevant external data, such as demographic information, purchase history, and user preferences, among others. The system allows for generating an analysis of user behavior through a correlation engine, which results in suggestions parameterized to user needs or pre-established rules.

[0024] In this same particular aspect, third-party information is obtained from these extraction connection means through a channel preferred by the user. At the infrastructure level, this can be done through a secure public channel or by establishing a virtual private network (VPN). Regarding the data capture methodology, one particular embodiment of the invention comprises an API where the user uploads the information through a service, and another embodiment of the invention incorporates a repository-type data transmission method (FTP-type) or through the establishment of a federated database.

[0025] In the same particular aspect of the invention, the extraction, transformation, and loading (ETL) process comprises generating a curated database containing original and new elements generated by the correlation and inference means. This database has the necessary structure to feed the correlation engine and thus generate relevant information.

[0026] In the same aspect of the present invention, the tokenizer corresponds to a mechanism that allows accounting of the loyalty assets held by each user or a specific record. Particularly, the tokenizer itself is a mechanism that, in principle, allows the creation of a circular economy, without limiting exchange with other economies. In the same aspect of the invention, the loyalty asset calculation protocol comprises the application of mathematical formulas that can be parameterized with the characteristics present in the database and other external sources (external query services via API) and the determination of the amount of loyalty assets to be assigned in each case.

[0027] Specifically, this protocol corresponds to a set of rules and algorithms that determine the allocation of the type and amount of loyalty assets based on the characteristics selected by the user or pre-established rules.

[0028] In this same embodiment of the invention, the correlation and deduction means are a set of mechanisms created, from the connection or extraction means to an external database or from the database as sources, which correspond to logical means or software support or machine learning and / or artificial intelligence algorithms.

[0029] Specifically, correlation and inference are used to calculate correspondences between data, and a curated list of suggestions is generated specifically for each user or profile as a basis for allocating loyalty assets.

[0030] Also particularly, these means comprise correlation and inference techniques or algorithms to generate additional data that are incorporated into the process of calculating loyalty assets and specific rewards for the user.

[0031] In this same aspect of the invention, the correlation and deduction means allow for calculating correlations between data, generating a curated list of suggestions for the user as to which characteristics of the stored data should be taken into account to optimize the mathematical formula for allocating loyalty assets and thus optimally target campaigns.

Claims

Claims 1. A loyalty system based on user-specific profiling, characterized in that it comprises an external objective database, a tokenizer, a loyalty asset calculation protocol focused on the characteristics selected by the user or pre-established rules, and correlation and deduction means to generate additional data as input for the calculation of loyalty assets and user-specific rewards.

2. Loyalty system by specific user profiling according to Claim 1, wherein the external target database comprises a data structure updated by an ETL (extract, transform and load), through which the data of specific users and related to a manager (or client) are normalized to include them in a database.

3. Loyalty system by specific user profiling according to Claim 1, wherein the tokenizer is a system that allows accounting of the loyalty assets of each user.

4. Loyalty system by specific user profiling according to Claim 1, wherein the loyalty asset calculation protocol focused on the characteristics selected by the user or pre-established rules based on mathematical formulas that can be parameterized with the characteristics present in the database and other external sources (external consultation services via API), determines the quantity and type of loyalty assets to be assigned in each case.

5. Loyalty system by user-specific profiling according to Claim 1, wherein the correlation and deduction means allow calculating correlations between data, generating a curated list of suggestions for the user as to which characteristics of the stored data should be taken into account to optimize the mathematical formula for allocating loyalty assets and thus target the campaigns optimally. Loyalty system by specific user profiling according to Claim 1, wherein a unique user profile is provided by calculating correspondences by means of correlation and deduction.

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