Perturbation, monitoring, and adjustment of an incentive amount using statistically valuable individual incentive sensitivity for improving survey participation rate
View Patent ↗Sensitivity to incentive changes of survey participant may be computed and analyzed. Participants and one or more attributes associated with the participants may be identified. The participants may be clustered into one or more clusters according to the one or more attributes. An incentive amount to be given to a participant in a cluster of said one or more clusters may be perturbed by performing random perturbation computation. The incentive may be distributed to the participant. One or more responses of the participant may be monitored. Individual incentive sensitivity representing incentive sensitivity of responsiveness of the participant per incentive change may be computed based on the monitoring. Incentive amount computation may be dynamically adjusted responsive to determining that the individual incentive sensitivity changed by a predefined criterion.
1. A method comprising:
calculating, by a processor, an incentive score per action for a participant;
determining an incentive amount based on an incentive score;
in response to determining that there are more incentives left to be distributed, calculating, by the processor, an optimal incentive and optimal frequency of the optimal incentive;
distributing, by the processor, the optimal incentive to the participant through a network;
modifying, by the processor, the optimal incentive by modeling responsiveness of the participant using a regression analysis with at least three parameters comprising an incentive delta, incentive frequency and responsiveness delta;
calculating, by the processor, an individual incentive sensitivity for the participant;
adjusting, by the processor, the individual incentive sensitivity based on the modifying;
determining, by the processor, whether a change between the individual incentive sensitivity and the adjusted individual incentive sensitivity is statistically valuable,
wherein the modeling responsiveness of the participant using a regression analysis reduces processor cycle time in obtaining the incentive amount that is more accurate.
2. The method of claim 1 , wherein the incentive delta represents a change of the incentive amount distributed to the participant.
3. The method of claim 1 , wherein the incentive frequency represents distribution frequency to the participant.
4. The method of claim 1 , wherein the incentive frequency represents distribution interval to the participant.
5. The method of claim 1 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive delta.
6. The method of claim 1 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive frequency.
7. The method of claim 1 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive delta and a change of the individual incentive sensitivity of the participant to the incentive frequency.
8. A system comprising:
a memory device; and
a hardware processor coupled with the memory device, the hardware processor performing:
calculating an incentive score per action for a participant;
determining an incentive amount based on an incentive score;
in response to determining that there are more incentives left to be distributed,
calculating an optimal incentive and optimal frequency of the optimal incentive;
distributing the optimal incentive to the participant through a network;
modifying the optimal incentive by modeling responsiveness of the participant using a regression analysis with at least three parameters comprising an incentive delta, incentive frequency and responsiveness delta;
calculating an individual incentive sensitivity for the participant;
adjusting the individual incentive sensitivity based on the modifying;
determining whether a change between the individual incentive sensitivity and the adjusted individual incentive sensitivity is statistically valuable,
wherein the modeling responsiveness of the participant using a regression analysis reduces hardware processor cycle time in obtaining the incentive amount that is more accurate.
9. The system of claim 8 , wherein the incentive delta represents a change of the incentive amount distributed to the participant.
10. The system of claim 8 , wherein the incentive frequency represents distribution frequency to the participant.
11. The system of claim 8 , wherein the incentive frequency represents distribution interval to the participant.
12. The system of claim 8 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive delta.
13. The system of claim 8 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive frequency.
14. The system of claim 8 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive delta and a change of the individual incentive sensitivity of the participant to the incentive frequency.
15. A non-transitory computer readable storage medium storing a program of instructions executable by a machine to perform a method comprising:
calculating an incentive score per action for a participant;
determining an incentive amount based on an incentive score;
in response to determining that there are more incentives left to be distributed, calculating an optimal incentive and optimal frequency of the optimal incentive;
distributing the optimal incentive to the participant through a network;
modifying the optimal incentive by modeling responsiveness of the participant using a regression analysis with at least three parameters comprising an incentive delta, incentive frequency and responsiveness delta;
calculating an individual incentive sensitivity for the participant;
adjusting the individual incentive sensitivity based on the modifying;
determining whether a change between the individual incentive sensitivity and the adjusted individual incentive sensitivity is statistically valuable,
wherein the modeling responsiveness of the participant using a regression analysis reduces hardware processor cycle time in obtaining the incentive amount that is more accurate.
16. The non-transitory computer readable storage medium of claim 15 , wherein the incentive delta represents a change of the incentive amount distributed to the participant.
17. The non-transitory computer readable storage medium of claim 15 , wherein the incentive frequency represents distribution frequency to the participant.
18. The non-transitory computer readable storage medium of claim 15 , wherein the incentive frequency represents distribution interval to the participant.
19. The non-transitory computer readable storage medium of claim 15 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive delta.
20. The non-transitory computer readable storage medium of claim 15 , wherein the responsiveness delta represents a change of the individual incentive sensitivity of the participant to the incentive frequency.