Patent Issued for Dynamic ranking of recommendation pairings

2022 JUL 18 (NewsRx) — By a Information Reporter-Staff Information Editor at Insurance coverage Each day News — From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Casalaina, Marco (San Francisco, CA, US), Sanghavi, Tejas (San Francisco, CA, US), submitted on May well 24, 2019, was printed online on June 28, 2022.

The patent’s assignee for patent number 11373232 is salesforce.com inc. (San Francisco, California, United States).

News editors obtained the adhering to quote from the history details supplied by the inventors: “A problem for companies is figuring out which solution, service, or actions are suitable suits for new and present buyers. Shoppers are bombarded with advertisements, provides and promotions and they are receiving immune to these, in particular due to the fact most of it applied to be based on what the organization wants to endorse, relatively than what the personal wants or requirements. Broad brush regulations, these kinds of as heuristic or intuitive principles, or purchaser segments, are not equipped to achieve the exact efficiency as a personalised advice that is unique to every specific customer. Giving these irrelevant offers may frustrate customers top to dissatisfaction or even attrition.

“Thus, there is a will need for an enhanced techniques and procedures for pinpointing proper products and products and services that are suitable for particular shoppers to generate sales of solutions or services.”

As a supplement to the history data on this patent, NewsRx correspondents also attained the inventors’ summary information for this patent: “Some implementations of the disclosed units, equipment, procedures and computer system method products are configured for integrating a machine finding out prediction system with business policies to form tips in around real-time centered on propensity of the concentrate on object to take. The predictive product is repeatedly updated with advice responses obtained by the method (shut-loop suggestions). The described devices and techniques also provide a answer to the “cold start” dilemma to give tips for constructing a prediction product when facts is missing.

“As described in further depth below, these prediction system may well be seamlessly built-in with any variety of application or provider such as a Purchaser Marriage Management (CRM) System, a social networking process, or any other consumer or company software program. While CRM platforms are reviewed herein as an example of an application or services, the illustrations of programs or products and services explained herein may possibly be substituted for any suitable application or assistance this sort of as individuals explained earlier mentioned.

“Existing solutions use heuristic and intuitive guidelines to proven product fit suggestions. On the other hand, these broad-brush policies do not attain the same functionality as a customized recommendation that is special to each individual person purchaser. Device finding out strategies for individualized tips function when sizeable quantities of facts are offered. Even so, businesses with massive catalogues of solutions maximize the likelihood that they will offer you shoppers irrelevant services/solutions because the machine finding out (ML) designs are poorly trained.

“By way of illustration, Raymond works as Inside of Revenue for a Sunrise Insurance coverage, a main insurance policy supplier that serves large-touch B2C (business enterprise-to-consumer) and more compact B2B (enterprise-to-enterprise) customers. He largely focuses on current accounts and increasing their share of wallet throughout their complete solution line, for instance by supplying Dwelling or Renter’s insurance policy solutions to present Automobile insurance policy consumers. Nonetheless, simply just providing added insurance policy products and solutions to existing clients, who do not need to have this sort of items or previously have acquired comparable items, might frustrate prospects who could come to feel pressured by undesirable solicitations or irritated by obtaining irrelevant details.

“Using conventional techniques, gives might be furnished in accordance with static guidelines. For illustration, the in-residence marketing group at Dawn Insurance policies may perhaps outline account outreach techniques just about every quarter based on advert-hoc analyses about which styles of buyers are most likely to obtain precise products. These procedures also contain many state certain guidelines centered on which items can be marketed in just about every point out. Nevertheless, the application of static procedures ignores client-certain characteristics.”

The claims provided by the inventors are:

“1. A approach comprising: transmitting by using a communications interface a person or a lot more guidelines for delivering a graphical person interface (GUI) for presentation at a customer product, the graphical person interface determining a plurality of object definitions processing an indicator of a variety of a designated object definition of the plurality of item definitions configuring a prediction product primarily based, at the very least in component, on the specified item definition that has been selected producing, applying the prediction product, for just about every of a plurality of suggestions, a corresponding one of a plurality of propensity scores in affiliation with a goal object occasion of the specified item definition primarily based, at least in part, on a set of knowledge area values involved with the target object instance of the selected item definition choosing at least 1 suggestion of the plurality of tips based mostly, at least in component, on the corresponding propensity rating and dynamically updating the prediction model primarily based, at minimum in portion, on a reaction to the selected advice.

“2. The system recited in assert 1, wherein each individual propensity rating indicates a respective chance that the selected one of the plurality of recommendations will be recognized.

“3. The approach recited in declare 1, whereby deciding upon at minimum a person suggestion is performed in accordance to a filter rule.

“4. The method recited in claim 1, even further comprising: ordering the plurality of recommendations dependent, at minimum in aspect, on a predetermined hierarchy.

“5. The strategy recited in assert 1, the approach more comprising: processing an indication of a variety of one or a lot more item fields involved with the specified item definition wherein the prediction design is even more configured dependent, on the one or a lot more item fields that have been picked.

“6. The strategy recited in declare 5, the system more comprising: picking the concentrate on item instance dependent, at least in section, on a prediction team, the prediction group staying dependent on a designated one of the object fields.

“7. The strategy recited declare 1, whereby the selected object definition is a get hold of object involved with an account object.

“8. The strategy recited in claim 1, whereby the prediction design is dynamically up to date based on a plurality of responses, each and every reaction corresponding to a respective a single of the suggestions.

“9. A databases program carried out employing a server program, the database program configurable to trigger: transmitting by using a communications interface a single or much more instructions for supplying a graphical consumer interface (GUI) for presentation at a consumer gadget, the graphical user interface determining a plurality of object definitions processing an indication of a selection of a specified object definition of the plurality of item definitions configuring a prediction product dependent, at minimum in portion, on the designated item definition that has been selected producing, using the prediction design, for each individual of a plurality of tips, a corresponding just one of a plurality of propensity scores in association with a concentrate on item instance of the designated item definition primarily based, at the very least in aspect, on a set of details subject values connected with the concentrate on item instance of the specified object definition deciding upon at the very least 1 recommendation of the plurality of recommendations dependent, at the very least in aspect, on the corresponding propensity rating and dynamically updating the prediction design dependent, at the very least in section, on a response to the chosen advice.

“10. The computing process recited in declare 9, whereby just about every propensity rating signifies a respective chance that the chosen a single of the plurality of tips will be recognized.

“11. The databases technique as recited in declare 9, the databases procedure more configurable to cause: processing an sign of a selection of one or more item fields involved with the designated object definition whereby the prediction design is further more configured based mostly, on the a single or additional item fields that have been chosen.

“12. One particular or additional non-transitory laptop or computer readable media owning guidance stored thereon for undertaking a approach, the process comprising: transmitting by using a communications interface just one or a lot more recommendations for giving a graphical user interface (GUI) for presentation at a shopper unit, the graphical user interface identifying a plurality of item definitions processing an sign of a selection of a selected item definition of the plurality of item definitions configuring a prediction design primarily based, at minimum in element, on the specified object definition that has been chosen creating, making use of the prediction design, for every of a plurality of recommendations, a corresponding just one of a plurality of propensity scores in affiliation with a concentrate on object instance of the designated object definition primarily based, at least in portion, on a established of facts subject values associated with the goal item instance of the selected object definition picking at minimum a single suggestion of the plurality of tips based mostly, at least in section, on the corresponding propensity score and dynamically updating the prediction product based mostly, at least in part, on a reaction to the selected suggestion.

“13. The database process as recited in assert 11, the databases method more configurable to cause: deciding upon the goal item occasion dependent, at minimum in portion, on a prediction team, the prediction group currently being primarily based on a selected a single of the item fields.

“14. The database technique as recited in assert 11, wherein the selected item definition is a get hold of object associated with an account object.

“15. The non-transitory computer-readable media as recited in claim 12, the system further more comprising: processing an indication of a selection of just one or much more item fields related with the designated item definition wherein the prediction product is further more configured based mostly, on the 1 or a lot more item fields that have been chosen.

“16. The non-transitory computer-readable media as recited in assert 12, the process further comprising: choosing the concentrate on object occasion primarily based, at minimum in aspect, on a prediction team, the prediction team being based on a designated just one of the item fields.

“17. The non-transitory computer-readable media as recited in claim 12, wherein the specified item definition is a make contact with object associated with an account item.”

For additional details on this patent, see: Casalaina, Marco. Dynamic position of suggestion pairings. U.S. Patent Range 11373232, filed May perhaps 24, 2019, and published on-line on June 28, 2022. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11373232.PN.&OS=PN/11373232RS=PN/11373232

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