Loyalty index user interface

1 . A system for presenting a loyalty index, the system comprising:

a processor; and

a computer storage medium storing instructions that are operative upon execution by the processor to:

retrieve transaction details for a plurality of users for a time period, wherein the transaction details comprise a user identifier, a transaction metric, a transaction date, and an entity identifier for each transaction in the time period;

calculate a total entity transaction metric in the time period by each user per entity;

sort the entities into user lists by total entity transaction metric by each user per entity in the time period in descending order;

calculate a total user transaction metric in the time period for each user, wherein the total user transaction metric is a summation of the total entity transaction metric of each entity that the user transacted with in the time period;

calculate an entity proportion for each entity per user, wherein the entity proportion is a proportion of the total entity transaction metric to the total user transaction metric;

filter out the entities in the user lists by a highest total entity transaction metric for each user into a favorite entities list;

calculate an exclusivity loyalty factor proportion, wherein the exclusivity loyalty factor proportion is an average value of the entity proportion for each entity in the favorite entities list weighted by the total entity transaction metric of each user with that entity;

train a machine learning model with the transaction details using the exclusivity loyalty factor proportion;

predict loyalty indexes using the trained machine learning model;

automatically generate and present, for each entity and corresponding exclusivity loyalty factor proportion, index icons associated with the loyalty indexes, the index icons including a natural language description of the exclusivity loyalty factor proportion in a user interface; and

automatically move the index icons to a list in the user interface in descending order of the exclusivity loyalty factor proportion without user input, thereby reducing user interaction events and associated computational processing.

2 . The system of claim 1 , wherein the instructions are further operative to:

retrieve transaction details for the plurality of users for a second time period;

calculate a total entity transaction metric in the second time period by each user per entity;

sort the entities into secondary user lists by total entity transaction metric by each user per entity in the second time period in descending order;

filter out the entities in the secondary user lists by a highest total entity transaction metric for each user into a secondary favorite entities list;

compare the favorite entities list with the secondary favorite entities list by user;

calculate a stability loyalty factor proportion, wherein the stability loyalty factor proportion is a number of entities that are the same on the favorite entities list and the secondary favorite entities list per user divided by the number of users;

present the stability loyalty factor proportion with a corresponding index icon in the user interface; and

automatically move the index icon to a list in the user interface in descending order of stability loyalty factor proportion that is perpendicular to the list of exclusivity loyalty factor proportion.

3 . The system of claim 1 , wherein the transaction details further comprise a transaction category for each transaction.

4 . The system of claim 3 , wherein the instructions are further operative to:

calculate a total entity transaction metric in the time period by each user for each transaction category per entity;

sort the entities into lists by total entity transaction metric by each user for each transaction category per entity in the time period in descending order;

calculate a total transaction metric in the time period for each user;

calculate an entity proportion for each user for each transaction category;

filter out the entities in the lists by the highest total entity transaction metric for each user for each transaction category into a favorite entities lists for each transaction category; and

calculate an exclusivity loyalty factor proportion for each transaction category, wherein the exclusivity loyalty factor proportion for each transaction category is an average value of entity proportion for each transaction category for each entity in the favorite entities list for each transaction category weighted by the total entity transaction metric of each user with that entity in each transaction category.

5 . The system of claim 1 , wherein the instructions are further operative to:

sort the favorite entities list in descending order of transaction metric per entity;

filter the favorites entities list to a particular entity;

filter the users of the particular entity above a transaction metric threshold;

present the users above the transaction metric threshold and a corresponding transaction metric as index icons in a user interface; and

automatically move the index icons to a list in the user interface in descending order of transaction metric.

6 . The system of claim 1 , wherein the transaction details further comprise a geographic location of the entity and the user, and wherein the instructions are further operative to:

calculate a total entity transaction metric in the time period by each user per entity where the geographic location of the user is beyond a specified distance from the geographic location of the entity;

sort the entities beyond the specified distance into lists by total entity transaction metric by each user for each transaction subject per entity in the time period in descending order;

calculate an entity proportion for each user beyond the specified distance;

filter out the entities in the lists beyond the specified distance by the highest total entity transaction metric for each user into a favorite distant entities list;

calculate an exclusivity loyalty factor proportion for entities beyond the specified distance, wherein the exclusivity loyalty factor proportion for each transaction beyond the specified distance is an average value of entity for each entity in the favorite distant entities list weighted by the total entity transaction metric of each user with that entity beyond the specified distance;

present the entities, corresponding exclusivity loyalty factor proportion beyond the specified distance, and the specified distance as index icons in a user interface; and

automatically move the index icons to a list in the user interface in descending order of exclusivity loyalty factor proportion beyond the specified distance.

7 . The system of claim 6 , wherein the total entity transaction metric is a transaction amount.

8 . A method for presenting a loyalty index, the method comprising:

retrieving transaction details for a plurality of users for a time period, wherein the transaction details comprise a user identifier, a transaction metric, a transaction date, and an entity identifier for each transaction in the time period;

calculating a total entity transaction metric in the time period by each user per entity;

sorting the entities into user lists by total entity transaction metric by each user per entity in the time period in descending order;

calculating a total user transaction metric in the time period for each user, wherein the total user transaction metric is a summation of the total entity transaction metric of each entity that the user transacted with in the time period;

calculating an entity proportion for each entity per user, wherein the entity proportion is a proportion of the total entity transaction metric to the total user transaction metric;

filtering out the entities in the user lists by a highest total entity transaction metric for each user into a favorite entities list;

calculating an exclusivity loyalty factor proportion, wherein the exclusivity loyalty factor proportion is an average value of the entity proportion for each entity in the favorite entities list weighted by the total entity transaction metric of each user with that entity;

training a machine learning model with the transaction details using the exclusivity loyalty factor proportion;

predicting loyalty indexes using the trained machine learning model;

automatically generating and presenting, for each entity and corresponding exclusivity loyalty factor proportion, index icons associated with the loyalty indexes, the index icons including a natural language description of the exclusivity loyalty factor proportion in a user interface; and

automatically moving the index icons to a list in the user interface in descending order of the exclusivity loyalty factor proportion without user input, thereby reducing user interaction events and associated computational processing.

9 . The method of claim 8 , further comprising:

retrieving transaction details for the plurality of users for a second time period;

calculating a total entity transaction metric in the second time period by each user per entity;

sorting the entities into secondary user lists by total entity transaction metric by each user per entity in the second time period in descending order;

filtering out the entities in the secondary user lists by a highest total entity transaction metric for each user into a secondary favorite entities list;

comparing the favorite entities list with the secondary favorite entities list by user;

calculating a stability loyalty factor proportion, wherein the stability loyalty factor proportion is a number of entities that are the same on the favorite entities list and the secondary favorite entities list per user divided by the number of users;

presenting the stability loyalty factor proportion with a corresponding index icon in the user interface; and

automatically moving the index icon to a list in the user interface in descending order of stability loyalty factor proportion that is perpendicular to the list of exclusivity loyalty factor proportion.

10 . The method of claim 8 , wherein the transaction details further comprise a transaction category for each transaction.

11 . The method of claim 10 , further comprising:

calculating a total entity transaction metric in the time period by each user for each transaction category per entity;

sorting the entities into lists by total entity transaction metric by each user for each transaction category per entity in the time period in descending order;

calculating a total transaction metric in the time period for each user;

calculating an entity proportion for each user for each transaction category;

filtering out the entities in the lists by the highest total entity transaction metric for each user for each transaction category into a favorite entities lists for each transaction category; and

calculating an exclusivity loyalty factor proportion for each transaction category, wherein the exclusivity loyalty factor proportion for each transaction category is an average value of entity proportion for each transaction category for each entity in the favorite entities list for each transaction category weighted by the total entity transaction metric of each user with that entity in each transaction category.

12 . The method of claim 8 , further comprising:

sorting the favorite entities list in descending order of transaction metric per entity;

filtering the favorites entities list to a particular entity;

filtering the users of the particular entity above a transaction metric threshold;

presenting the users above the transaction metric threshold and a corresponding transaction metric as index icons in a user interface; and

automatically moving the index icons to a list in the user interface in descending order of transaction metric.

13 . The method of claim 8 , wherein the transaction details further comprise a geographic location of the entity and the user, and wherein the method further comprising:

calculating a total entity transaction metric in the time period by each user per entity where the geographic location of the user is beyond a specified distance from the geographic location of the entity;

sorting the entities beyond the specified distance into lists by total entity transaction metric by each user for each transaction subject per entity in the time period in descending order;

calculating an entity proportion for each user beyond the specified distance;

filtering out the entities in the lists beyond the specified distance by the highest total entity transaction metric for each user into a favorite distant entities list;

calculating an exclusivity loyalty factor proportion for entities beyond the specified distance, wherein the exclusivity loyalty factor proportion for each transaction beyond the specified distance is an average value of entity for each entity in the favorite distant entities list weighted by the total entity transaction metric of each user with that entity beyond the specified distance;

presenting the entities, corresponding exclusivity loyalty factor proportion beyond the specified distance, and the specified distance as index icons in a user interface; and

automatically moving the index icons to a list in the user interface in descending order of exclusivity loyalty factor proportion beyond the specified distance.

14 . The method of claim 13 , wherein the total entity transaction metric is a transaction amount.

15 . A non-transitory computer storage medium storing instructions that are operative upon execution by a processor to:

retrieve transaction details for a plurality of users for a time period, wherein the transaction details comprise a user identifier, a transaction metric, a transaction date, and an entity identifier for each transaction in the time period;

calculate a total entity transaction metric in the time period by each user per entity;

sort the entities into user lists by total entity transaction metric by each user per entity in the time period in descending order;

calculate a total user transaction metric in the time period for each user, wherein the total user transaction metric is a summation of the total entity transaction metric of each entity that the user transacted with in the time period;

calculate an entity proportion for each entity per user, wherein the entity proportion is a proportion of the total entity transaction metric to the total user transaction metric;

filter out the entities in the user lists by a highest total entity transaction metric for each user into a favorite entities list;

calculate an exclusivity loyalty factor proportion, wherein the exclusivity loyalty factor proportion is an average value of the entity proportion for each entity in the favorite entities list weighted by the total entity transaction metric of each user with that entity;

train a machine learning model with the transaction details using the exclusivity loyalty factor proportion;

predict loyalty indexes using the trained machine learning model;

automatically generate and present, for each entity and corresponding exclusivity loyalty factor proportion, index icons associated with the loyalty indexes, the index icons including a natural language description of the exclusivity loyalty factor proportion in a user interface; and

automatically move the index icons to a list in the user interface in descending order of the exclusivity loyalty factor proportion without user input, thereby reducing user interaction events and associated computational processing.

16 . The computer storage medium of claim 15 , wherein the instructions are further operative to:

retrieve transaction details for the plurality of users for a second time period;

calculate a total entity transaction metric in the second time period by each user per entity;

sort the entities into secondary user lists by total entity transaction metric by each user per entity in the second time period in descending order;

filter out the entities in the secondary user lists by a highest total entity transaction metric for each user into a secondary favorite entities list;

compare the favorite entities list with the secondary favorite entities list by user;

calculate a stability loyalty factor proportion, wherein the stability loyalty factor proportion is a number of entities that are the same on the favorite entities list and the secondary favorite entities list per user divided by the number of users;

present the stability loyalty factor proportion with a corresponding index icon in the user interface; and

automatically move the index icon to a list in the user interface in descending order of stability loyalty factor proportion that is perpendicular to the list of exclusivity loyalty factor proportion.

17 . The computer storage medium of claim 15 , wherein the transaction details further comprise a transaction category for each transaction.

18 . The computer storage medium of claim 17 , wherein the instructions are further operative to:

calculate a total entity transaction metric in the time period by each user for each transaction category per entity;

sort the entities into lists by total entity transaction metric by each user for each transaction category per entity in the time period in descending order;

calculate a total transaction metric in the time period for each user;

calculate an entity proportion for each user for each transaction category;

filter out the entities in the lists by the highest total entity transaction metric for each user for each transaction category into a favorite entities lists for each transaction category; and

calculate an exclusivity loyalty factor proportion for each transaction category, wherein the exclusivity loyalty factor proportion for each transaction category is an average value of entity proportion for each transaction category for each entity in the favorite entities list for each transaction category weighted by the total entity transaction metric of each user with that entity in each transaction category.

19 . The computer storage medium of claim 15 , wherein the instructions are further operative to:

sort the favorite entities list in descending order of transaction metric per entity;

filter the favorites entities list to a particular entity;

filter the users of the particular entity above a transaction metric threshold;

present the users above the transaction metric threshold and a corresponding transaction metric as index icons in a user interface; and

automatically move the index icons to a list in the user interface in descending order of transaction metric.

20 . The computer storage medium of claim 15 , wherein the transaction details further comprise a geographic location of the entity and the user, and wherein the instructions are further operative to:

calculate a total entity transaction metric in the time period by each user per entity where the geographic location of the user is beyond a specified distance from the geographic location of the entity;

sort the entities beyond the specified distance into lists by total entity transaction metric by each user for each transaction subject per entity in the time period in descending order;

calculate an entity proportion for each user beyond the specified distance;

filter out the entities in the lists beyond the specified distance by the highest total entity transaction metric for each user into a favorite distant entities list;

calculate an exclusivity loyalty factor proportion for entities beyond the specified distance, wherein the exclusivity loyalty factor proportion for each transaction beyond the specified distance is an average value of entity for each entity in the favorite distant entities list weighted by the total entity transaction metric of each user with that entity beyond the specified distance;

present the entities, corresponding exclusivity loyalty factor proportion beyond the specified distance, and the specified distance as index icons in a user interface; and

automatically move the index icons to a list in the user interface in descending order of exclusivity loyalty factor proportion beyond the specified distance.