# US 10,769,701 B1 · Sensory-based delivery of content > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,769,701 B1 - Document ID: US10769701B1 - Status: Granted - Kind: B1 - Application number: 15/907,031 - Filed: 2018-02-27 - Granted: 2020-09-08 - Earliest claimed: 2018-02-27 - Assignees: Amazon Technologies, Inc. - Applicants: Amazon Technologies, Inc. - Inventors: Corby Winer; Amanda Crivlare; Michael Naro Norman; Matthew Douglas Morton; Whitney Weisman - Web page: https://patentgrep.com/patent/US10769701B1 ## CPC - G06Q 30/0631: {Recommending goods or services} - G06F 3/016: {Input arrangements with force or tactile feedback as computer generated output to the user} - G06F 3/017: {Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883)} - G06F 3/0346: with detection of the device orientation or free movement in a three-dimensional [3D] space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors - G06Q 30/0257: {User requested} - G06Q 30/0641: {utilising user interfaces specially adapted for shopping} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Various embodiments of systems and methods allow, in connection with a customized web landing page, a “shake to reveal” content functionality, wherein an end-user customer provides input, via an electronic device, with respect to predefined categories, and content responsive to the input is determined. The content may include a product or service recommendation and will have one or more sensory aspects pertaining thereto. Upon performance of a triggering action on the end-user device, the device is provided with aural, visual, haptic, or other feedback conveying the sensory aspects. Further, the content is displayed on the device. Varying forms of end-user triggering actions may be performed, and embodiments may use a neural network trained on a data set to generate the recommendations and select content for the end-user. ## Claims ### Claim 1 A computer-implemented method, comprising: receiving an input in response to at least one question about a prospective consumer of a product; determining first recommendation content responsive to the input, the first recommendation content having a sonic aspect pertaining to the product; receiving accelerometer data regarding a first triggering motion performed on an electronic device; providing aural feedback on the electronic device, the aural feedback relating to the sonic aspect and generally synchronous with the first triggering motion; providing the first recommendation content for presentation on the electronic device; receiving accelerometer data regarding a second triggering motion performed on the electronic device; determining a second recommendation content responsive to the first input; providing the aural feedback on the electronic device, the aural feedback generally synchronous with the second triggering motion; and providing the second recommendation content for presentation on the electronic device. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the input comprises at least one of: a tactile question response, an image, a video, or an aural command. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, further comprising: providing at least one of visual, haptic, or tactile feedback on the electronic device. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, further comprising: providing at least one of a feedforward, recurrent, radial basis function, modular, and self-organizing neural network; training the neural network on a data set, the data set comprising preferences and histories; and applying the neural network to optimize the determination of content responsive to the input. ### Claim 5 A computer-implemented method, comprising: receiving at least one input with respect to at least one predefined category; determining a plurality of content responsive to the at least one input, each content of the plurality of content having a sensory aspect pertaining thereto; receiving accelerometer data regarding a plurality of triggering actions performed on an electronic device; providing, through the electronic device, feedback relating to a plurality of sensory aspects and generally synchronous with the plurality of triggering actions; and providing at least a portion of the plurality of content corresponding to the plurality of sensory aspects for presentation on the electronic device. ### Claim 6 (depends on 5) The computer-implemented method of claim 5, wherein the feedback relating to the sensory aspect comprises at least one of aural, visual, haptic, or tactile feedback on the electronic device. ### Claim 7 (depends on 5) The computer-implemented method of claim 5, further comprising: setting a triggering action acceptability threshold, the triggering action acceptability threshold configured such that unintended or other minimal electronic device movements are not accepted as a triggering action. ### Claim 8 (depends on 5) The computer-implemented method of claim 5, further comprising: verifying that triggering action functionality is present and accessible on the electronic device. ### Claim 9 (depends on 5) The computer-implemented method of claim 5, wherein the at least one input comprises at least one of: a tactile question response, an image, a video, or an aural command. ### Claim 10 (depends on 9) The computer-implemented method of claim 9, further comprising: determining, in response to an additional triggering action, additional content responsive to the at least one input, the additional content having a sensory aspect pertaining thereto; providing, in response to the additional triggering action, additional feedback on the electronic device, the feedback relating to the sensory aspect; and providing the additional content for presentation on the electronic device. ### Claim 11 (depends on 5) The computer-implemented method of claim 5, further comprising: receiving a second input with respect to at least one predefined category; and updating the content presented on the electronic device pursuant to the second input. ### Claim 12 (depends on 5) The computer-implemented method of claim 5, further comprising: training a neural network on a data set; and applying the neural network to optimize the determination of content responsive to the at least one input. ### Claim 13 A computing system, comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the computing system to: receive at least one input with respect to at least one predefined category; determine a plurality of content responsive to the at least one input, the content having a sensory aspect pertaining thereto; receive accelerometer data regarding a plurality of triggering actions performed on an electronic device; provide, through the electronic device, feedback relating to a plurality of sensory aspects and generally synchronous with the plurality of triggering actions; and provide at least a portion of the plurality of content corresponding to the plurality of sensory aspects for presentation on the electronic device. ### Claim 14 (depends on 13) The computing system of claim 13, wherein the feedback relating to the sensory aspect comprises at least one of aural, visual, haptic, or tactile feedback on the electronic device. ### Claim 15 (depends on 13) The computing system of claim 13, wherein the instructions when executed further cause the computing system to: set a triggering action acceptability threshold, the triggering action acceptability threshold configured such that unintended or other minimal electronic device movements are not accepted as a triggering action. ### Claim 16 (depends on 13) The computing system of claim 13, wherein the instructions when executed further cause the computing system to: verify that triggering action functionality is present and accessible on the electronic device. ### Claim 17 (depends on 13) The computing system of claim 13, wherein the at least one input comprises at least one of: a tactile question response, an image, a video, or an aural command. ### Claim 18 (depends on 13) The computing system of claim 13, wherein the instructions when executed further cause the computing system to: determine, in response to an additional triggering action, additional content responsive to the at least one input, the additional content having a sensory aspect pertaining thereto; provide, in response to the additional triggering action, additional feedback on the electronic device, the feedback relating to the sensory aspect; and provide the additional content for presentation on the electronic device. ### Claim 19 (depends on 13) The computing system of claim 13, wherein the instructions when executed further cause the computing system to: receive a second input with respect to at least one predefined category; and update the content presented on the electronic device pursuant to the second input. ### Claim 20 (depends on 13) The computing system of claim 13, wherein the instructions when executed further cause the computing system to: train a neural network on a data set; and apply the neural network to optimize the determination of content responsive to the at least one input.