GB2624394A

GB2624394A - Methods and systems for targeted distribution of tasks amongst mobile devices

Info

Publication number: GB2624394A
Application number: GB2217061.7A
Authority: GB
Inventors: Larry Adeniran Babatunde; Gerard Joseph Laptore Armand; John Mangan Kieran
Original assignee: Grapedata Ltd
Current assignee: Grapedata Ltd
Priority date: 2022-11-15
Filing date: 2022-11-15
Publication date: 2024-05-22
Also published as: GB202217061D0; WO2024104999A1

Abstract

Targeted distribution of tasks amongst mobile devices in a network by defining a target task location; defining a target area encompassing the target location; determining mobile devices within the network which are/were within the target area (note, includes the location); sending a notification to the devices that the task is available for completion; receiving location data from the devices at a time of commencement and/or completion of the task. Also, targeted distribution of tasks amongst mobile devices in a network by defining a target task location; defining a target area encompassing the target location; determining mobile devices within the network which are/were at the target location and if the number of devices is above a threshold, sending a notification to the devices that the task is available for completion; otherwise, determining mobile devices within the network which are/were within the target area and (if the number of devices is above a threshold) sending a notification to the devices that the task is available for completion. This maximises the likelihood of obtaining high-quality response data and minimises the risk of obtaining unreliable/unsuitable response data.

Description

METHODS AND SYSTEMS FOR TARGETED DISTRIBUTION OF TASKS AMONGST MOBILE DEVICES

FIELD OF THE INVENTION

The present invention relates to methods and systems for targeted distribution of tasks amongst mobile devices, and more particularly, but not exclusively, to hyper-targeted distribution of surveys amongst the mobile devices of potential respondents.

BACKGROUND

Conducting digital surveys on the Internet that require a respondent to visit a specific location is becoming more common. In the traditional context, a survey distributor would physically visit a location to identify and question prospective respondents within the location area identified for distribution of the survey. By contrast, digital surveys allow low-cost, immediate distribution of surveys to many potential respondents. However, digital surveys distributed via the Internet have the innate challenge of accurately verifying the location of the respondent. This is especially important for digital surveys that are required to be completed within a ring-fenced geolocation. For example, a digital survey may seek to collect information from individuals within a specific location (e.g., a store, shop floor, airport, etc.).

It is thus typical in the field of digital surveys that the process of participating in a survey is initiated by a potential contributor declaring themselves available or suitable to take part in said survey. The survey process initiation may occur according to one of several known methods. For example, a potential contributor may make a survey selection from a list of available surveys. Alternatively, a potential contributor may declare themself available for surveys at or within specified locations. These known methods of process initiation have in common the fact that initiation of the survey process is enacted via a "pull" action, i.e. by action on the part of the contributor. Consequently, the group of active contributors from whom survey data may be acquired tends to be subjective, unpredictable, and/or otherwise sub-optimal. For example, the group of contributors tends not to include those potential contributors who would be strong or desirable respondents but who may consider themselves too busy to register an interest, or otherwise enact the appropriate pull action. Conversely, the group of contributors may comprise respondents who have a low probability of being in one of the desired locations at the appropriate time (or otherwise fulfilling an important condition in the process initiation), or who are sub-optimal respondents in the sense that they have a poor record of providing accurate survey data or are demographically unsuited to the survey.

Known methods of survey process initiation via pull actions also tend to be too slow to satisfy the needs of urgent or time-sensitive surveys, and may produce surveys of unpredictable quality. Such methods, by virtue of the need for up-front action by the potential contributor, are also known to be subject to contributor demotivation, whereby contributors frequently applying to surveys for which they are subsequently deemed unsuitable become disillusioned and demotivated to continue, wasting contributor time and leading to low rates of contributor retention. Contributor demotivation makes it difficult for a distributor to build up a core of experienced respondents capable of reliably completing complex surveys.

Attempts to address these problems have focused on ring-fencing survey distributions within a specific geographic area. A commonly used method is to use a potential contributor's country information and IP address for location validation. Inputs of user profile information allow additional restrictions to survey distribution. For example, a user who inputs a city as part of their address details may be reasonably assumed, for the purposes of survey distribution, to reside in said city, or at least be in close proximity thereto.

However, distributing a digital survey to respondents based on IP address location presents two challenges. Firstly, IP address targeting is usually broad and not sufficiently accurate for the needs of some surveys. Secondly, such distribution does not determine whether the survey was actually completed whilst the respondent was in a given location.

US 2014343984 Al is concerned with spatial crowdsourcing systems and methods that assign spatial tasks to be performed by contributors. The systems and methods attempt to verify the validity of responses provided by the contributors, but rely on contributors volunteering for tasks by submitting the spatial regions in which they are interested in or willing to carry out tasks. These spatial regions may or may not be their actual location. Tasks to be completed are allocated not only based on the spatial region submissions but also reputation scores attributed to the contributors, whereby each contributor's reputation score represents or indicates a probability with which the contributor will perform a task correctly. Each task to be completed is assigned a confidence threshold constituting the minimum acceptable reputation score of a contributor, corresponding to the minimum acceptable quality level of the task's result. Tasks are then distributed to contributors who satisfy the threshold, or to multiple contributors whose aggregate reputation score satisfied the threshold. Reputation scores are calculated on the basis of mining previous answers of a contributor, but do not include any information element related to the actual location of a contributor at the time of survey completion. Locations are not reported automatically by a user's device to the crowdsourcing system.

CN 109033865 A is concerned with a task distribution method for privacy protection in spatial crowdsourcing. The method involves a spatial crowdsourcing platform, an agent, and a contributor. According to the method, user data is sent to the spatial crowdsourcing platform by using a data collection protocol based on anonymity. A task assignment algorithm based on a reverse auction is used to help the spatial crowdsourcing platform to generate the task assignment and a reward scheme. According to the algorithm, the contributors bid for work at locations to which they must travel. Locations are not automatically detected and no attempt is made to verify the contributor's location or the reliability of their responses.

D. Li, J. Zhu and Y. Cui, "Prediction-Based Task Allocation in Mobile Crowdsensing," 2019 15th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN), 2019, pp. 89-94, doi: 10.1109/M5N48538.2019.00029 is concerned with leveraging the semiMarkov model to predict the position distribution of contributors and tasks. According to their prediction-based task allocation, the connection probability between a contributor and a task is calculated under a time constraint, according to which the maximum overall system utility and lowest travelling cost can be derived.

US 2020021603 Al is concerned with systems and methods of verifying the reliability and validity of tasks executed by crowdsourced contributors. Key task implementing procedures are computerized and mapped as system events and/or contributor actions, which are recorded as data when contributors navigate in the computer platforms and/or systems. Data obtained is compared to reference data relating to the expected geographic location and/or time stamp of task completion. The degree of reliability and validity of the contributor response is then assessed based on the match between the obtained and reference data.

SUMMARY

The present inventors have realised that, despite the known methods above, there exists a need for survey process initiation which is of improved quality and efficiency, and which can be initiated quickly, automatically and according to objective, verifiable criteria, thereby maximising the likelihood of obtaining high-quality response data and minimising the risk of obtaining unreliable and/or unsuitable response data.

Better predictability of identifying suitable respondents based on, for example, historical geolocation of a contributor has the potential to solve this problem.

The present inventors have realised that hyper-targeted surveys, i.e. surveys distributed based on a set of parameters in addition to instantaneous geolocation, offer a solution to this problem. The set of parameters may include, for example, a combination of demographic parameters provided as part of a contributor's profile at application sign-up, based on information submitted by the user such as age; gender; location; device type; income level; occupation; education; behavioural parameters including trackable behaviours such as application activity levels, and degrees of participation in one or more previous surveys; and psychographic parameters including, but not limited, to data on lifestyle, habits, and patterns associated with the user's responses in past surveys.

In an aspect, there is provided a method for targeted distribution of tasks amongst mobile devices in a network. The method comprises: defining (e.g. obtaining by an apparatus or network node) a target location for a task to be completed; defining (e.g. obtaining by an apparatus or network node) a target area encompassing the target location; determining (e.g. detecting or identifying), by an apparatus of the network, one or more mobile devices within the network that are currently, or have been within a particular time period in the past, located at the target location or within the target area; sending, from the apparatus, to the determined one or more mobile devices, a notification (e.g. a respective or broadcast/multicast notification) that the task is available for completion; receiving, by the apparatus, from each mobile device of the one or more mobile devices, first information associated with a first location of that mobile device, the first location being a location of that mobile device at a time of commencement of the task using that mobile device; and/or receiving, by the apparatus, from each mobile device of the one or more mobile devices, second information associated with a second location of that mobile device, the second location being a location of that mobile device at a time of completion of the task using that mobile device.

The determining one or more mobile devices may comprise detecting that the one or more mobile devices within the network are currently located at the target location or are within the target area.

The method may further comprise defining a time period for completion of the task, wherein a historical geolocation profile of a mobile device is used to predict whether the mobile device will be in the target location or target area during the defined time period for carrying out the task.

The determining one or more mobile devices may comprise determining that the one or more mobile devices within the network have been located at the target location or within the target area during a predefined time period.

The task may comprise a survey that is to be completed.

The method may further comprise capturing (e.g. receiving, by the apparatus, from the one or more mobile devices) data associated with the completion of the task.

The data associated with the completion of the task may include a response to the survey.

The method may further comprise assessing the or calculating an individual respondent's reliability index based on captured geolocation data, at least one of the first and/or second information, and/or a historical geolocation profile of the mobile device, the respondent reliability index being indicative of a quality of the completion of the task.

The method may further comprise aggregation of individual respondent reliability assessments across multiple surveys, providing a reliability index associated with the individual.

The method may further comprise aggregation of the reliability assessments of all respondents for the current survey, providing a reliability index for the current survey results.

The method may further comprise determining, by the apparatus, that a number of the one or more mobile devices that are currently, or have been within the particular time period in the past, located at the target location is greater than or equal to a first threshold number of mobile devices. The notification may be sent to the determined one or more mobile devices (e.g. that are currently, or have been within the particular time period in the past, located at the target location) responsive to the determination that the number of the one or more mobile devices that are currently, or have been within the particular time period in the past located at the target location is greater than or equal to the first threshold number of mobile devices.

The method may further comprise determining, by the apparatus, that a number of the one or more mobile devices that are currently, or have been within the particular time period in the past, located at the target location is less than a first threshold number of mobile devices; responsive to determining that the number of the one or more mobile devices that are currently, or have been within the particular time period in the past, located at the target location is less than the first threshold number of mobile devices, determining (e.g. detecting/identifying) one or more additional mobile devices that are currently, or have been within the particular time period in the past, within the target area but not at the target location, such that the number of mobile devices that are currently, or have been within the particular time period in the past, located at the target location and the number of additional mobile devices is greater than or equal to the first threshold number of mobile devices. The notification may be sent to the determined one or more mobile devices (e.g. that are currently, or have been within the particular time period in the past, located at the target location and the one or more additional mobile devices) responsive to the determination that the number of mobile devices that are currently, or have been within the particular time period in the past, located at the target location and the number of additional mobile devices is greater than or equal to the first threshold number of mobile devices.

A historical geolocation profile of a mobile device may be used to predict the likelihood of the second information being provided, and using this prediction to decide whether or not to include that mobile device amongst the mobile devices to receive the notification.

In a further aspect, there is provided an apparatus in a mobile network. The apparatus comprises a receiver, a transmitter, and a processor. The receiver the transmitter and the processor are arranged to cause the apparatus to: obtain (e.g. by the receiver or the processor) a target location for a task to be completed; obtain (e.g. by the receiver or the processor) a target area encompassing the target location; determine (e.g. by at least one of the receiver and the processor) one or more mobile devices within the network that are currently, or have been within a particular time period in the past, located at the target location or within the geographical area; send, (e.g. by the transmitter) to the one or more mobile devices, a (respective or broadcast/multicast) notification that the task is available for completion; receive (e.g., by the receiver) from each mobile device of the one or more mobile devices, first information associated with a first location of that mobile device, the first location being a location of that mobile device at a time of commencement of the task using that mobile device; and receive (e.g., by the receiver) from each mobile device of the one or more mobile devices, second information associated with a second location of that mobile device, the second location being a location of that mobile device at a time of completion of the task using that mobile device.

In a further aspect, there is provided a system for targeted distribution of tasks amongst mobile devices. The system comprises: the apparatus of any preceding aspect; and one or more mobile devices. Each mobile device is arranged to: receive the notification from the apparatus that the task is available for completion; optionally, commence the task; responsive to commencement of the task using that mobile device, send, to the apparatus, the first information corresponding to that mobile device; optionally, complete the task; and, responsive to completion of the task using that mobile device, send, to the apparatus, the second information corresponding to that mobile device.

In a further aspect, there is provided a method performed by an apparatus of a mobile network, the method comprising: obtaining a target location for a task to be completed; obtaining a target area encompassing the target location; determining that one or more mobile devices within the network are currently, or have been within a particular time period in the past, located at the target location or within the target area; sending to the one or more mobile devices a notification that the task is available for completion; receiving information associated with a first location of each of the one or more mobile devices at a time corresponding to commencement of the task; and receiving further information associated with a second location of each of the one or more mobile devices at a time corresponding to completion of the task.

In a further aspect, there is provided a method for targeted distribution of tasks amongst mobile devices in a network. The method comprises: defining, by an apparatus of the network, a target location for a task to be completed; defining, by the apparatus, a target area encompassing the target location; populating, by the apparatus, a first set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located at the target location; determining, by the apparatus, whether the first set of mobile devices includes of a number of mobile devices greater than or equal to a threshold number of mobile devices; and if the first set of mobile devices includes a number of mobile devices greater than or equal to the threshold number of mobile devices, sending, from the apparatus to each mobile device of the first set of mobile devices, a notification that the task is available for completion; or, if the first set of mobile devices includes of a number of mobile devices less than the threshold number of mobile devices, populating, by the apparatus, a second set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located within the target area (e.g. but not the target location), and sending, from the apparatus to each mobile device of the second set of mobile devices, a notification that the task is available for completion.

The method may further comprise completing, by each mobile device of the first set of mobile devices, the task; and capturing, by the apparatus, information associated with a location of each mobile device of the first set of mobile devices at a time corresponding to commencement and/or completion of the task.

The method may further comprise completing, by each mobile device of the second set of mobile devices, the task; and capturing, by the apparatus, information associated with a location of each mobile device of the second set of mobile devices at a time corresponding to commencement and/or completion of the task.

In a further aspect, there is provided an apparatus of a mobile network, the apparatus comprising: a receiver; a transmitter; and a processor. The receiver, the transmitter, and the processor are arranged to cause the apparatus to: define a target location for a task to be completed; define a target area encompassing the target location; populate a first set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located at the target location; determine whether the first set of mobile devices includes a number of mobile devices greater than or equal to a threshold number of mobile devices; and, if the first set of mobile devices includes a number of mobile devices greater than or equal to the threshold number of mobile devices, send to each mobile device of the first set of mobile devices, a notification that the task is available for completion; or, if the first set of mobile devices includes a number of mobile devices less than the threshold number of mobile devices populate a second set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located within the target area (e.g. but not the target location), and send to each mobile device of the second set of mobile devices, a notification that the task is available for completion.

In a further aspect, there is provided a program or plurality of programs arranged such that when executed by a computer system or one or more processors it/they cause the computer system or the one or more processors to operate in accordance with the method of any of the preceding aspects.

In a further aspect, there is provided a machine-readable storage medium storing a program or at least one of the plurality of programs according to the preceding aspect.

BRIEF DESCRIPTION

Embodiments of the present invention will now be described in more detail with reference, by way of example only, to the accompanying drawings, in which: Figure 1 depicts a system architecture for matching a user to a task, e.g. a survey, in their location; Figure 2 depicts a system architecture for verifying user location upon task completion; Figure 3 is a flow chart depicting a method for an instantaneous survey process initiation which requires that a contributor be present, or be predicted to be present, at a target location at a specific time; Figure 4 is a flow chart depicting a method for a past experience survey process initiation which requires that a contributor be present at a target location for a specified period of time; and Figure 5 is a flow chart depicting a method for a targeted survey process initiation. In the figures, like features will be denoted by like reference numerals.

DETAILED DESCRIPTION

Embodiments of the present invention involve use of geolocation data of survey respondents in order to provide a prediction of tasks that will be available and suitable as part of the respondents' daily routine. Upon survey completion, embodiments of the invention also use geolocation parameters to determine the source location of a survey response and to evaluate the level of fidelity, quality or suspiciousness that may be ascribed to said survey response. Additionally, the result of this validation may be fed back into the geolocation-based respondent identification process, further enhancing the reliability of said process.

In embodiments of the present invention, historical geolocation, whereby one or multiple last known locations are identified from a user through basic or advanced geolocation, may be performed in a first example via an ecosystem of tasks that users automatically unlock based on their location. For example, if a user walks past a first type/brand of store, they may unlock a task related to comparison of said first type/brand of store with a second, different type/brand of store. If a user is in an office, they may be offered a task relating to remote work tools, etc. The established geolocation profile of a user may then be used to predict which users are likely to be in a particular location or within a predefined proximity of said location at a specified time, thereby delimiting a group of users to be sent a specific survey. This prediction may be based on the variety of location data derived from analysing the locations of a user. A probabilistic algorithm may be used to predict the confidence level of a user being at a predicted location. The algorithm utilizes varying functions and pattern analysis to understand trends according to which the user is detected in a location. Patterns may include, but are not limited to, the date or timing of one or multiple last known location occurrences, and the mobile device used by the user when a location was captured. By analysing the multiple last known locations of the user, the algorithm determines a predicted location with the highest probability of coinciding with the user's current location. The research administrator for the geolocation process may deem this predicted location useful or appropriate if, for example, the predicted location falls within the target location, or a predefined proximity thereto, of the task, e.g. a survey.

In embodiments of the present invention, each user may make use of a mobile application on a mobile device. As part of their onboarding process for use of the app, users are requested to grant location permissions. These permissions allow the accurate determination of the user's location and identity.

In embodiments of the present invention, users may enable an "advanced geolocation" function that allows the app to track and store users' geolocation at all times, even when the application is running in the background only. The application may recurringly remind the user that this function is enabled, and/or may ask for their repeat consent at regular intervals.

S

Historical geolocation according to embodiments of the present invention also provides the research administrator (with user consent and in line with GDPR regulations) a better idea of the personal and professional profiles of users. Through historical geolocation, a user profile may be built up with reference to user interests, consumption preferences and habits. This data, combined with other captured personal details such as the demographic, behavioural and psychographic attributes of the user, provides enriched information for selecting users to complete surveys which best relate, wholly or partly, to such attributes and data.

Advantageously, historical geolocation according to embodiments of the present invention tends to result in a higher engagement as more relevant tasks will be available to a user. In the interests of improved user experience, the task completion platform may be gamified, for example in a "Pokemon Go" (RTM) fashion, with contributors being able to unlock tasks in proximity to them and attain increasing levels upon tasks' completion, whereby each level reflects a deepening engagement of the user. Users who obtain a high level tend to build a relationship of trust with the surveying company and may give consent for the app to track their live locations at agreed times. Participating contributors hence have a user experience which is enhanced over time, whereby their chances of earning high rewards tend to increase with continued use of the platform.

Advantageously, from a client and operational standpoint, historical geolocation according to embodiments of the present invention tends to improve prediction of success/qualification rate for niche surveys, aid in data/profile verification of a contributor, and enhance the depth of the user base and, as a result, diversification of the research administrator's client base.

Figure 1 is a schematic illustration (not to scale) showing an embodiment of a system architecture 100. In this embodiment, the system architecture 100 is for matching a user to a task, e.g. survey, in their location. The architecture 100 comprises a user mobile application 102 on a mobile device, a user location service 104, a graph database 106 (more specifically, in this embodiment, a Neo4J graph database), an internal web application 108, a tasks service 110, a Kafka topic 112, a task location matching service 114, a task view service 116, and a database 118 (more specifically, in this embodiment, a MongoDB NoSQL database).

Via a first communications link 120, the user's location is passed with their device's unique identifier from the mobile application 102 to the user location service 104 via HTTPS.

Via a second communications link 125, the user location service 104 stores this information in the graph database 106. By way of analogy, if one considers a map of the earth to be a 'graph', the graph database 106 allows a user's location to be stored as a respective 'node' on the graph, allowing for subsequent quick searching and grouping. The user location service 104 stores the identifier of the user's device as a node in the graph database 106, as well as updating its location. For example, the node may be referred to as 'Device' and have the following associated relevant properties: latitude, longitude, lastLocationTimestamp. When the node is inserted or updated in the database 106, the following relationships may also be created/initiated/updated: * A USED_BY relationship between the Device and the corresponding User: (:Device) [:USED_BY]->(:User).

* An IN_RANGE relationship between the Device and each task targeting that location: (:Device)-[:IN_RANGE]->(:Task). The IN_RANGE relationship also receives a timestamp property, representing the moment in time when the Device was last in range of the task's targeted location.

The research administrator for the architecture 100 may save or update a target location and a predefined proximity target, e.g. a target area being a geographical area which may be bounded by a nominal maximum distance(s) from the target location, of a task in the internal web application 108, which web application 108 sends, via a third communications link 130, a HTTPS message to the tasks service 110.

Via a fourth communications link 135, the tasks service 110 publishes the new or updated task information to the dedicated Kafka topic 112.

Via a fifth communications link 140, the task location matching service 114 consumes the new or updated task information, which includes the location of the task.

The task location matching service 114 saves tasks targeting a specific location as 'Task' nodes with the following properties: latitude, longitude, maxDistance, maxMinutesAfterLastInRange. An IN_RANGE relationship between a task and all matching devices is also created/updated whenever one of the following properties is changed for a task: latitude, longitude, maxDistance, maxMinutesAfterLastInRange.

Via a sixth communications link 145, the task location matching service 114 performs a query on the graph database 106 to retrieve users within a configurable defined location for the task. A device may be considered in range of a task's targeted location if the following conditions are met: * The distance between the device's location (device latitude and longitude) and the location targeted by the task (task latitude and longitude) does not exceed the task's maxDistance value (derived from the predefined proximity target set by the administrator); and/or * The time span between the device's lastLocationTimestamp and the time at which the IN_RANGE relationship is created does not exceed the task's maxMinutesAfterLastInRange value.

Via a seventh communications link 150, the task location matching service 114 publishes the user task match information (e.g. which may comprise a list of users/user devices that are within the predefined proximity target area and, optionally, satisfy one or more other criteria) to the dedicated Kafka topic 112.

Via an eighth communications link 155, the task view service 116 consumes the user task match information.

Via a ninth communications link 160, the task view service 116 saves the user task match information to a NoSQL database 118.

A user may open the mobile application 102 and navigate to view their available tasks. The user mobile application 102 makes, via a tenth communications link 165, a HTTPS request to the task view service 116 to retrieve a list of available tasks.

Via an eleventh communications link 170, the task view service 220 queries the NoSQL database 118 for available tasks for the user, and returns them to the mobile application 102.

The user may then participate in location-based surveys in which they may be required to navigate to a specific location and interview individuals fitting the target audience. On submission of the survey by the user (e.g. using the mobile application 102 on the user device), the mobile application 102 captures the respondent's location to determine that they are in the correct location when the survey response is being submitted or otherwise presented to the research administrator. This location may be added to a series of last known locations associated with the user, e.g. stored in a NoSQL database such as the database 118. Storing the results of this reliability assessment as a reliability index of the respondents, together with historical geolocation data, tends to safeguard the accuracy, efficiency and quality of response data collection. The reliability index may be a plurality of reliability assessments across multiple respondents.

Figure 2 is a schematic illustration (not to scale) showing a further system architecture 200 in accordance with an embodiment. The further system architecture 200 is for verifying user location upon task completion. The further system architecture 200 comprises a user mobile application 102, an internal web application 108, a tasks service 110, a dedicated Kafka topic 112, a NoSQL database 118, a task responses service 202, a MySQL database 204, and a task responses view service 206.

Via a further first wireless communications link 210, the research administrator updates a task, e.g. a survey, with the target location and predefined proximity target, sending the data from the internal web application 108 to the tasks service 110.

Via a further second wireless communications link 215, the data obtained via 210 is published to the dedicated Kafka topic 112.

Via a further third wireless communications link 220, the task responses view service 206 consumes the data received by the dedicated Kafka topic 112.

Via a further fourth wireless communications link 225, the data is saved to the NoSQL Database 118.

A user subsequently completes a survey using the mobile application 102 and, via a further fifth wireless communications link 230, the response and location data are submitted to the task responses service 202.

Via a further sixth wireless communications link 235, this data is saved to a relational database, i.e. the MySQL database 204, to allow the task responses service 202 to use it in other user flows.

Via a further seventh wireless communications link 240, the data is also published to the dedicated Kafka topic 112.

Via a further eighth wireless communications link 245, the task responses view service 206 consumes this data.

Via a further ninth wireless communications link 250, the data is saved to the NoSQL Database.

Via a further tenth wireless communications link 255, the research administrator or other user/operator of the internal web application 108 views the user's task responses. Both the location data of the task and the location of task completion are used to inform the research administrator as to whether the task was completed at the correct location. If it was not, the research administrator is able to view and analyse the location discrepancy. The research administrator may accordingly discard or edit a user's task response or information associated therewith.

The person skilled in the art will readily recognise various modifications and changes that may be made to embodiments of the present invention without limitation to the examples and applications illustrated and described herein, and without departing from the scope of the present disclosure.

Apparatus, for implementing the above arrangements, and performing the method steps to be described below, may be provided by configuring or adapting any suitable apparatus, for example one or more computers or other processing apparatus or processors, and/or providing additional modules. The apparatus may comprise a computer, a network of computers, or one or more processors, for implementing instructions and using data, including instructions and data in the form of a computer program or plurality of computer programs stored in or on a machine-readable storage medium such as computer memory, a computer disk, ROM, PROM etc., or any combination of these or other storage media.

It should be noted that certain of the process steps depicted in the flowcharts of Figures 3 to 5 and described below may be omitted or such process steps may be performed in differing order to that presented below and shown in Figures 3 to 5. Furthermore, although all the process steps have, for convenience and ease of understanding, been depicted as discrete temporally-sequential steps, nevertheless some of the process steps may in fact be performed simultaneously or at least overlapping to some extent temporally.

Figure 3 is a process flow chart depicting an embodiment of a method 300 for an instantaneous survey process initiation. This method may require that a contributor be present, or be predicted to be present, at a target location at a specific time. In this embodiment, the target location is an airport, but in other embodiments the target location may be a different location appropriate to the task.

At step s305, a research administrator seeks to run a digital survey amongst people visiting an airport (the target location).

At step s310, the survey is configured by the research administrator, via the internal web application 108, to be displayed (on the user mobile application 102) only to users who are currently within a predefined proximity target to the target location.

At step s315, the application detects those users who are currently within the predefined proximity target, with the goal of asking them to interview consumers coming out of or going into the airport. Step s315 may be executed by the mobile application 102 and/or the internal web application 108.

The research administrator chooses to only display this digital survey to users who are within the predefined proximity target of the airport. The research administrator may assume that users who meet the predefined proximity target are travellers going on or returning from a trip. When a user who is part of the predetermined audience, i.e. the subset of potential respondents who are being considered for this particular survey, falls within the predefined proximity target of this location, the specified survey(s) become available to them to participate in.

The users to whom the survey is available for participation are sent a notification message using a push notification or SMS or email or other channels, to highlight the availability of the survey to them.

Specifically, if the number of users currently at the target location meets the desired number of respondents for the survey, then at step s320a users whose location as determined by advanced geolocation or (if the application is in the mobile device's foreground) basic geolocation matches the exact target location are included in a list to be sent a notification message. Step s320a may be executed by the user location service 104 and/or the task location matching service 114.

Alternatively, if the number of users currently within the predefined proximity target area meets the desired number of respondents, then at step s320b users whose location as determined by advanced geolocation or (if the application is in the mobile device's foreground) basic geolocation matches falls within the predefined proximity target are included in the list to be sent a notification message. Step s320b may be executed by the user location service 104 and/or the task location matching service 114.

At step s320b, it may be the case that the number of users currently at the target location does not meet the desired number of respondents for the survey.

If the number of users within the predefined proximity target area does not meet the desired number, the number of users may be increased by expanding the predefined proximity target and/or increasing marketing and other recruitment measures. Step s315 (and subsequent steps) is then repeated.

At step s325, the users selected in the list are each sent a notification message indicating that the survey is available for completion. Step s325 may be executed by the graph database 106. Users selected in the list are the potential respondents who have been selected from the entire user list according to various selection methods. Primarily, these are the proximity criteria of current and/or historic location, which indicate that the potential respondent has the necessary knowledge to complete the survey. However, there is also the possibility of applying secondary selection criteria such as demographics and/or a potential respondent's historic geolocation profile (thereby allowing a prediction of where a potential respondent may be at a specified time in the future and/or allowing an analysis of the interests of a potential respondent, e.g. if they go to a clothing shop every day they may be considered likely to be very interested in fashion).

The user is then able to, at step s330, participate in the survey and thus become a respondent.

At step s335, the user's geolocation data is captured upon commencement of the survey to provide the research administrator with additional metadata and/or information about the originating location of the user. This allows the research administrator to set one or more definitive criteria for accuracy of response. Step s335 may be executed by the mobile application 102.

At step s340, the respondent's geolocation data is captured at the moment of completion of the survey, thereby to give the research administrator additional metadata and/or information about the closing location of the user. Step s340 may be executed by the mobile application 102.

At step s345, the user's captured geolocation data corresponding to the commencement and completion of the survey is fed back to the research administrator by the mobile application 102, thereby to allow the research administrator to determine the validity of the response given the location in which the response data was provided.

At step s350, an individual respondent reliability assessment for the current survey is calculated based on the captured geolocation data obtained at step s340 which is stored (204). These individual reliability assessments per survey are aggregated in two ways. One is an aggregation for the individual respondent across multiple surveys, providing a reliability index associated with the individual. The other form of aggregation is across all respondents for the current survey, providing an indication of the reliability of the survey results.

Thus, a method 300 is provided for an instantaneous survey process initiation which requires that a contributor be present, or be predicted to be present, at a target location.

Figure 4 is a process flow chart depicting certain steps of an embodiment of a method 400 for a past experience survey process initiation. The method 400 may require that a contributor be present at a target location for a specified period of time. In this embodiment, the target location is once again an airport, but in other embodiments the target location may be a different location appropriate to the task.

At step s405, the research administrator seeks to run a digital survey amongst people who may have visited the airport (the target location) within a specified period of time. Step s405 may be executed by the internal web application 108.

The research administrator assumes that users having a last known location or historical location that match the airport's geocoordinates (target location) within the specified time period are able to offer accurate and original data for the survey because they have been in proximity to the airport.

At step s410, the research administrator sets the predefined proximity target area. In some embodiments, this may be set using historical location data, i.e. using historical geolocation, of users. Step s410 may be executed by the internal web application 108.

At step s415, the research administrator defines the specific period of time in the past within which matching locations are considered to meet the criteria for accuracy. Step s415 may be executed by the internal web application 108.

At step s420, the application detects those users who have, during the specific period of time in the past, been within the predefined proximity target area. Step s420 may be executed by the task location matching service 114 If the number of users who have, during the specific period of time in the past, been within the predefined proximity target area meets the desired number of respondents for the survey, then at step s425a those users are included in a list to be sent a notification message. Step s425a may be executed by the user location service 104 and/or the task location matching service 114.

Alternatively, if the number of users who have, during the specific period of time in the past, been within the predefined proximity target area does not meet the desired number of respondents, then at step s42513 the size of the predefined proximity target area is increased and/or marketing efforts are made to increase the correct number of suitable potential respondents. Step s42513 may be executed by the user location service 104 and/or the task location matching service 114.At step s430, the users selected in the list are each sent a notification message indicating that the survey is available for completion. Step s430 may be executed by the graph database 106. Users selected in the list are the potential respondents who have been selected from the entire user list according to various selection methods. Primarily, these are the proximity criteria of current and/or historic location, which indicate that the potential respondent has the necessary knowledge to complete the survey. However, there is also the possibility of applying secondary selection criteria such as demographics and/or a potential respondent's historic geolocation profile (thereby allowing a prediction of where a potential respondent may be at a specified time in the future and/or allowing an analysis of the interests of a potential respondent, e.g. if they go to a clothing shop every day they may be considered likely to be very interested in fashion).

The user is then able to, at step s435, participate in the survey and thus become a respondent. Step s435 may be executed by the mobile application 102.

At step s440, the user's geolocation data is captured upon commencement of the survey to provide the research administrator with additional metadata and/or information about the originating location of the user. This allows the research administrator to set one or more definitive criteria for accuracy of response. Step s440 may be executed by the mobile application 102.

At step s445, the respondent's geolocation data is captured at the moment of completion of the survey, thereby to give the research administrator additional metadata and/or information about the closing location of the user. Step s445 may be executed by the mobile application 102.

At step s450, the user's captured geolocation data corresponding to the commencement and completion of the survey is fed back to the research administrator by the mobile application 102, thereby to allow the research administrator to better understand how far away the respondent is from the airport and whether the distance may pose accuracy or originality concerns to the response data.

At step s455, a respondent reliability assessment is calculated based on the captured geolocation data obtained at step s450. The calculating the respondent reliability assessment may be executed by the task responses service 202. The respondent reliability index may be subsequently stored. The storing of the respondent reliability index may be executed by the MySQL database 204.

Thus, a method 400 is provided for a past experience survey process initiation which requires that a contributor be present at a target location for a specified period of time.

Advantageously, using the historical geolocation data of users in accordance with embodiments of the present invention allows them to be hyper-targeted by the research administrator in a manner which has hitherto not been available, and results in both significantly better matching of surveys to users and higher-quality data in surveys. The historical data collected about participating users is used in three main ways.

Firstly, the historical geolocation data is used to delimit a broad online audience to a smaller audience size. Online surveys by their nature are constrained by the granularity of targeting available to research administrators. Research administrators typically have to target audiences using their location based on an IP address. This tends to be broad in execution, meaning research administrators must either filter down results or limit distribution to in-person survey channels for location-dependent surveys. By contrast, hyper-targeting of a finer granularity selection according to the present invention tends to result in higher quality surveys conducted by the required number of contributors.

Secondly, the historical geolocation data tends to help a research administrator validate the accuracy and originality of response data provided by the user. According to embodiments of the present invention, the research administrator may use the number of times a user's geolocation data matches a target area as a proxy to validate the quality of data provided. For example, it may be assumed that users with a more frequent match to the target area have a higher probability of being knowledgeable about the research subject area.

Thirdly, historical geolocation data may be used by the survey researcher to predict the likelihood of a user completing a survey. In this case the researcher sets the parameters appropriately in order to obtain the desired target number of responses.

Figure 515 a process flow chart depicting certain steps of an embodiment of a method 500 for a targeted survey process initiation showing the research administrator's candidate selection process for a hyper-targeted survey. The method SOO may therefore be considered a method for hyper-targeted survey process initiation.

At step s505, the research administrator defines potential respondents or the survey according to a primary criteria related to location.

At step s510, the research administrator optionally further defines the potential respondents using secondary selection criteria such as demographics and/or a potential respondent's historic geolocation profile, allowing a prediction of where a potential respondent may be at a specified time in the future and/or allowing an analysis of the interests of a potential respondent. The combination of a potential respondent's historic geolocation with other demographic and behavioural attributes of the said respondent gives the research administrator an additional layer of insight to which they can make selection criteria. For instance, if according to historical geolocation data, a potential respondent frequently enters clothing shops, they are probably very interested in fashion. When combined with demographic factors such as their age, an assessment can be made as to what type of fashion they potentially are interested in.

At step s515, the research administrator further decides if, on the basis of the survey requirements and number of respondents required, whether filtering by behavioural attributes is preferable or appropriate for the hyper-targeting. Behavioural attributes may include the use of trackable behaviours such as activity levels on the application and/or participation in one or multiple previous surveys.

If filtering by behavioural attributes is deemed preferable or appropriate, the research administrator identifies, at step s520, users with appropriate behavioural attributes for the given survey. Step s520 may be executed by the internal web application 108.

If filtering by behavioural attributes is not deemed preferable or appropriate, the research administrator aggregates, at step s535, a final list of potential respondents to receive the survey invite notification. Step s535 may be executed by the graph database 106.

Following step s520, at step s525 the research administrator further decides, on the basis of the survey requirements and number of respondents required, whether filtering by psychographic attributes is preferable or appropriate for the hyper-targeting. Psychographic parameters include but are not limited to data on lifestyle, habits and patterns provided by the user in past surveys.

If filtering by psychographic attributes is deemed preferable or appropriate, the research administrator identifies, at step s530, users with appropriate psychographic attributes for the given survey. Step s530 may be executed by the internal web application 108.

If filtering by psychographic attributes is not deemed preferable or appropriate, the research administrator moves on to aggregating, at step s535, a final list of potential respondents to receive the survey invite notification.

Following step s530, the research administrator moves on to aggregating, at step s535, a final list of users to receive the survey invite notification.

Thus, a method 500 is provided for a targeted, or hyper-targeted, survey process initiation.

Thus, hyper-targeted surveys as illustrated in Figure 5, i.e. surveys distributed based on a set of parameters beyond instant geolocation, including the use of a combination of demographic parameters involving who the user logs in as on the app based on previously supplied information by the user, such as age, gender, location, device type, income level, occupation, education, behavioural parameters involving the use of trackable behaviours such as activity levels on the application, participation in one or multiple previous surveys, and psychographic parameters including but not limited to data on lifestyle, habits, patterns provided by the user in past surveys, are provided. Geolocation data of survey respondents may be used provide a prediction of tasks that will be available and suitable as part of the respondents' daily routine.

It should be noted that the above-mentioned methods and apparatus illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative arrangements without departing from the scope of the appended claims. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim, "a" or "an" does not exclude a plurality, and a single processor or other unit may fulfil the functions of several units recited in the claims. Any reference signs in the claims shall not be construed so as to limit their scope.

The described methods and apparatus may be practiced in other specific forms. The described methods and apparatus are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Further aspects of the invention are provided by the subject matter of the following clauses: 1. A method of hyper-targeted localization of mobile devices, comprising the steps of defining a target location, defining a proximity target with reference to said target location, populating a first set of mobile devices with a first plurality of mobile devices selected from a superset of mobile devices, said selection being effected on the basis of said proximity target, pushing a first notification message to the mobile devices within said first set of mobile devices, populating a second set of mobile devices with a second plurality of mobile devices, depending on responses received to said first notification message, pushing a second notification message to each mobile device in said second set of mobile devices and storing the geolocation of each mobile device in said second set of mobile devices, depending on responses received from each mobile device in said second set of mobile devices to said second notification message, capturing the geolocation of each mobile device in said second set of mobile devices.

2. A method of hyper-targeted localization of mobile devices, comprising the steps of defining a target location, defining a proximity target with reference to said target location, defining a time period, defining a proximity target with reference to said target location, populating a first set of mobile devices with a first plurality of mobile devices selected from a superset of mobile devices, said selection being effected on the basis of said proximity target and said time period, pushing a first notification message to the mobile devices within said first set of mobile devices, populating a second set of mobile devices with a second plurality of mobile devices, depending on responses received to said first notification message, pushing a second notification message to each mobile device in said second set of mobile devices and storing the geolocation of each mobile device in said second set of mobile devices, depending on responses received from each mobile device in said second set of mobile devices to said second notification message, capturing the geolocation of each mobile device in said second set of mobile devices.

3. A system operable to hyper-target mobile devices, comprising means for defining a target location, means for defining a proximity target with reference to said target location, means for populating a first set of mobile devices with a first plurality of mobile devices selected from a superset of mobile devices, said selection being effected on the basis of said proximity target, means for pushing a first notification message to the mobile devices within said first set of mobile devices, means for populating a second set of mobile devices with a second plurality of mobile devices, depending on responses received to said first notification message, means for pushing a second notification message to each mobile device in said second set of mobile devices and storing the geolocation of each mobile device in said second set of mobile devices, means operable to capture the geolocation of each mobile device in said second set of mobile devices, depending on responses received from each mobile device in said second set of mobile devices to said second notification message.

4. A system operable to hyper-target mobile devices, comprising means for defining a target location, means for defining a proximity target with reference to said target location, means for defining a time period, means for defining a proximity target with reference to said target location, means for populating a first set of mobile devices with a first plurality of mobile devices selected from a superset of mobile devices, said selection being effected on the basis of said proximity target and said time period, means for pushing a first notification message to the mobile devices within said first set of mobile devices, means for populating a second set of mobile devices with a second plurality of mobile devices, depending on responses received to said first notification message, means for pushing a second notification message to each mobile device in said second set of mobile devices and storing the geolocation of each mobile device in said second set of mobile devices, means operable to capture the geolocation of each mobile device in said second set of mobile devices, depending on responses received from each mobile device in said second set of mobile devices to said second notification message.

Claims

CLAIMS1. A method for targeted distribution of tasks amongst mobile devices in a network, the method comprising: defining a target location for a task to be completed; defining a target area encompassing the target location; determining, by an apparatus in the network, one or more mobile devices within the network that are currently, or have been within a particular time period in the past, located at the target location or within the target area; sending, from the apparatus, to the determined one or more mobile devices, a notification that the task is available for completion; receiving, by the apparatus, from each mobile device of the one or more mobile devices, first information associated with a first location of that mobile device, the first location being a location of that mobile device at a time of commencement of the task using that mobile device; and/or receiving, by the apparatus, from each mobile device of the one or more mobile devices, second information associated with a second location of that mobile device, the second location being a location of that mobile device at a time of completion of the task using that mobile device.
2. The method of claim 1, wherein the determining one or more mobile devices comprises detecting that the one or more mobile devices within the network are currently located at the target location or are within the target area.
3. The method of any of claims 1 or 2, further comprising defining a time period for completion of the task, wherein a historical geolocation profile of a mobile device is used to predict whether the mobile device will be in the target location or target area during the defined time period for carrying out the task.
4. The method of any preceding claim, wherein the determining one or more mobile devices comprises determining that the one or more mobile devices within the network have been located at the target location or within the target area during a predefined time period.
5. The method of any preceding claim, wherein the task comprises a survey that is to be completed.
6. The method of any preceding claim, further comprising capturing data associated with the completion of the task.
7. The method of claim 6 when dependent upon claim 5, wherein the data associated with the completion of the task includes a response to the survey.
8. The method of any preceding claim, further comprising calculating an individual respondent's reliability index based on captured geolocation data, at least one of the first and/or second information, and/or a historical geolocation profile of the mobile device, the reliability index being indicative of a quality of the completion of the task.
9. The method of any preceding claim, wherein: the method further comprises determining, by the apparatus, that a number of the one or more mobile devices that are currently, or have been within the particular time period in the past, located at the target location is greater than or equal to a first threshold number of mobile devices; and the notification is sent to the determined one or more mobile devices responsive to the determination that the number of the one or more mobile devices that are currently, or have been within the particular time period in the past, located at the target location is greater than or equal to the first threshold number of mobile devices.
10. The method of any of claims 1 to 8, wherein: the method further comprises determining, by the apparatus, that a number of the one or more mobile devices that are currently, or have been within the particular time period in the past, located at the target location is less than a first threshold number of mobile devices; responsive to determining that the number of the one or more mobile devices that are currently, or have been within the particular time period in the past, located at the target location is less than the first threshold number of mobile devices, determining one or more additional mobile devices that are currently, or have been within the particular time period in the past, within the target area but not at the target location, such that the number of mobile devices that are currently, or have been within the particular time period in the past, located at the target location and the number of additional mobile devices is greater than or equal to the first threshold number of mobile devices; and the notification is sent to the determined one or more mobile devices responsive to the determination that the number of mobile devices that are currently, or have been within the particular time period in the past, located at the target location and the number of additional mobile devices is greater than or equal to the first threshold number of mobile devices.
11. An apparatus of a mobile network, the apparatus comprising: a receiver; a transmitter; and a processor; wherein the receiver, the transmitter, and the processor are arranged to cause the apparatus to: obtain a target location for a task to be completed; obtain a target area encompassing the target location; determine one or more mobile devices within the network that are currently, or have been within a particular time period in the past, located at the target location or within the geographical area; send, to the one or more mobile devices, notification that the task is available for completion; receive from each mobile device of the one or more mobile devices, first information associated with a first location of that mobile device, the first location being a location of that mobile device at a time of commencement of the task using that mobile device; and receive from each mobile device of the one or more mobile devices, second information associated with a second location of that mobile device, the second location being a location of that mobile device at a time of completion of the task using that mobile device.
12. A system for targeted distribution of tasks amongst mobile devices, the system comprising: the apparatus of claim 11; and one or more mobile devices; wherein each mobile device is arranged to: receive the notification from the apparatus that the task is available for completion; responsive to commencement of the task using that mobile device, send, to the apparatus, the first information corresponding to that mobile device; and responsive to completion of the task using that mobile device, send, to the apparatus, the second information corresponding to that mobile device.
13. A method for targeted distribution of tasks amongst mobile devices in a network, the method comprising: defining, by an apparatus of the network, a target location for a task to be completed; defining, by the apparatus, a target area encompassing the target location; populating, by the apparatus, a first set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located at the target location; determining, by the apparatus, whether the first set of mobile devices includes of a number of mobile devices greater than or equal to a threshold number of mobile devices; and if the first set of mobile devices includes a number of mobile devices greater than or equal to the threshold number of mobile devices: sending, from the apparatus to each mobile device of the first set of mobile devices, a notification that the task is available for completion; or if the first set of mobile devices includes of a number of mobile devices less than the threshold number of mobile devices: populating, by the apparatus, a second set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located within the target area; and sending, from the apparatus to each mobile device of the second set of mobile devices, a notification that the task is available for completion.
14. The method of claim 13, further comprising: completing, by each mobile device of the first set of mobile devices, the task; and capturing, by the apparatus, information associated with a location of each mobile device of the first set of mobile devices at a time corresponding to commencement and/or completion of the task.
15. The method of claim 13 or 14, further comprising: completing, by each mobile device of the second set of mobile devices, the task; and capturing, by the apparatus, information associated with a location of each mobile device of the second set of mobile devices at a time corresponding to commencement and/or completion of the task.
16. An apparatus of a mobile network, the apparatus comprising: a receiver; a transmitter; and a processor; wherein the receiver the transmitter and the processor are arranged to cause the apparatus to: define a target location for a task to be completed; define a target area encompassing the target location; populate a first set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located at the target location; determine whether the first set of mobile devices includes a number of mobile devices greater than or equal to a threshold number of mobile devices; and if the first set of mobile devices includes a number of mobile devices greater than or equal to the threshold number of mobile devices: send to each mobile device of the first set of mobile devices, a notification that the task is available for completion; or if the first set of mobile devices includes a number of mobile devices less than the threshold number of mobile devices: populate a second set of mobile devices in the network including devices which are currently, or have been within a particular time period in the past, located within the target area; and send to each mobile device of the second set of mobile devices, a notification that the task is available for completion.
17. A program or plurality of programs arranged such that when executed by a computer system or one or more processors it/they cause the computer system or the one or more processors to operate in accordance with the method of any of claims 1 to 10 or 13 to 15.
18. A machine-readable storage medium storing a program or at least one of the plurality of programs according to claim 17.