Systems and methods for generating and analyzing user behavior metrics during makeup consultation sessions
A server device detects initiation of a video conferencing session between a consultation device utilized by a makeup professional and a client device utilized by a user receiving a makeup consultation from the makeup professional. The server device extracts data from the client device during the video conferencing session, the data characterizing behavior of the user performed on the client device with respect to suggested cosmetic effects transmitted by the makeup professional via the consultation device to the client device. The server device applies weight values to the extracted data and generates one or more hesitation metrics based on the weight values and causes the one or more hesitation metrics to be displayed in a user interface on the consultation device.
1. A method implemented in a server device, comprising:
detecting initiation of a video conferencing session between a consultation device utilized by a makeup professional and a client device utilized by a user receiving a makeup consultation from the makeup professional;
extracting data from the client device during the video conferencing session, the data characterizing behavior of the user performed on the client device with respect to suggested cosmetic effects transmitted by the makeup professional via the consultation device to the client device;
applying weight values to the extracted data;
generating one or more hesitation metrics based on the weight values; and
causing the one or more hesitation metrics to be displayed in a user interface on the consultation device.
2. The method of claim 1 , wherein extracting the data from the client device comprises extracting data relating to a predetermined grouping of target events corresponding to user behavior on the client device.
3. The method of claim 2 , wherein applying the weight values to the extracted data comprises applying predetermined weight values for each event in the grouping of target events.
4. The method of claim 3 , wherein the grouping of target events comprises at least one of:
selection by the user on the client device of a type of cosmetic effect;
selection by the user on the client device of a variation in attribute of the selected type of cosmetic effect; and
removal by the user on the client device of a type of cosmetic effect.
5. The method of claim 4 , wherein each type of cosmetic effect corresponds to cosmetic effects for different facial features.
6. The method of claim 4 , wherein the variation in the attribute of the selected type of cosmetic effect comprises a color variation of the type of cosmetic effect.
7. The method of claim 4 , wherein the variation in the attribute of the selected type of cosmetic effect comprises enhancement or reduction of a cosmetic effect.
8. The method of claim 1 , wherein causing the one or more hesitation metrics to be displayed in the user interface on the consultation device comprises:
sorting the one or more hesitation metrics; and
causing the sorted one or more hesitation metrics to be displayed in the user interface on the consultation device.
9. A system, comprising:
a memory storing instructions;
a processor coupled to the memory and configured by the instructions to at least:
detect initiation of a video conferencing session between a consultation device utilized by a makeup professional and a client device utilized by a user receiving a makeup consultation from the makeup professional;
extract data from the client device during the video conferencing session, the data characterizing behavior of the user performed on the client device with respect to suggested cosmetic effects transmitted by the makeup professional via the consultation device to the client device;
apply weight values to the extracted data and generate one or more hesitation metrics based on the weight values; and
cause the one or more hesitation metrics to be displayed in a user interface on the consultation device.
10. The system of claim 9 , wherein the processor extracts the data from the client device by extracting data relating to a predetermined grouping of target events corresponding to user behavior on the client device.
11. The system of claim 10 , wherein the processor applies the weight values to the extracted data by applying predetermined weight values for each event in the grouping of target events.
12. The system of claim 11 , wherein the grouping of target events comprises at least one of:
selection by the user on the client device of a type of cosmetic effect;
selection by the user on the client device of a variation in attribute of the selected type of cosmetic effect; and
removal by the user on the client device of a type of cosmetic effect.
13. The system of claim 12 , wherein each type of cosmetic effect corresponds to cosmetic effects for different facial features.
14. The system of claim 12 , wherein the variation in the attribute of the selected type of cosmetic effect comprises a color variation of the type of cosmetic effect.
15. The system of claim 9 , wherein the processor causes the one or more hesitation metrics to be displayed in the user interface on the consultation device by:
sorting the one or more hesitation metrics; and
causing the sorted one or more hesitation metrics to be displayed in the user interface on the consultation device.
16. A non-transitory computer-readable storage medium storing instructions to be implemented by a computing device having a processor, wherein the instructions, when executed by the processor, cause the computing device to at least:
detect initiation of a video conferencing session between a consultation device utilized by a makeup professional and a client device utilized by a user receiving a makeup consultation from the makeup professional;
extract data from the client device during the video conferencing session, the data characterizing behavior of the user performed on the client device with respect to suggested cosmetic effects transmitted by the makeup professional via the consultation device to the client device;
apply weight values to the extracted data and generate one or more hesitation metrics based on the weight values; and
cause the one or more hesitation metrics to be displayed in a user interface on the consultation device.
17. The non-transitory computer-readable storage medium of claim 16 , wherein the processor extracts the data from the client device by extracting data relating to a predetermined grouping of target events corresponding to user behavior on the client device.
18. The non-transitory computer-readable storage medium of claim 17 , wherein the processor applies the weight values to the extracted data by applying predetermined weight values for each event in the grouping of target events.
19. The non-transitory computer-readable storage medium of claim 18 , wherein the grouping of target events comprises at least one of:
selection by the user on the client device of a type of cosmetic effect;
selection by the user on the client device of a variation in attribute of the selected type of cosmetic effect; and
removal by the user on the client device of a type of cosmetic effect.
20. The non-transitory computer-readable storage medium of claim 19 , wherein each type of cosmetic effect corresponds to cosmetic effects for different facial features.
21. The non-transitory computer-readable storage medium of claim 19 , wherein the variation in the attribute of the selected type of cosmetic effect comprises a color variation of the type of cosmetic effect.