阅读说明：本技术 用于移动用户行为监测的方法和设备 (Method and apparatus for mobile user behavior monitoring ) 是由 林在亨 约翰·威廉·施默茨 达里尔·马丁 于 2020-02-19 设计创作，主要内容包括：本公开提供了“用于移动用户行为监测的方法和设备”。在内容流期间播放要约,所述要约包括跟踪特性。所述跟踪特性存储在车辆存储器中。响应于存储所述跟踪特性,记录与所述跟踪特性相对应的车辆行驶数据。基于与先前记录的车辆数据的比较,识别出由所述记录的数据指示的车辆行为中的至少一个变化。响应于识别出车辆行为中的所述变化,报告车辆行为中的所述变化、所述记录的数据以及所述要约的标识。(The present disclosure provides "methods and apparatus for mobile user behavior monitoring. An offer is played during the content stream, the offer including the tracking characteristic. The tracking characteristic is stored in a vehicle memory. In response to storing the tracking characteristic, vehicle travel data corresponding to the tracking characteristic is recorded. At least one change in vehicle behavior indicated by the recorded data is identified based on a comparison with previously recorded vehicle data. In response to identifying the change in vehicle behavior, reporting the change in vehicle behavior, the logged data, and the identification of the offer.)

1. A system, comprising:

a processor configured to

Inserting an offer including a tracking characteristic during playback of the media content stream;

storing the tracking characteristic in a vehicle memory;

in response to storing the tracking characteristic, recording vehicle travel data corresponding to the tracking characteristic;

identifying at least one change in user behavior indicated by the recorded data based on a comparison of the vehicle travel data with previously recorded vehicle data; and

in response to identifying a change in vehicle behavior, reporting the change in vehicle behavior, the logged data, and the identification of the offer.

2. The system of claim 1, wherein the processor is further configured to transmit the tracking characteristic to a mobile device in communication with the vehicle.

3. The system of claim 2, wherein the processor is further configured to exchange information with the mobile device to obtain tracking information collected by the mobile device corresponding to the tracking characteristics.

4. The system of claim 1, wherein the tracking characteristic comprises a duration for which tracking should continue.

5. The system of claim 4, wherein the duration is measured in number of trips.

6. The system of claim 1, wherein the tracking characteristics include tracking a docking duration at a docking location associated with the offer.

7. The system of claim 1, wherein the tracking characteristic comprises tracking off-route travel time or distance from a predefined route for reaching a waypoint associated with the offer.

8. A method, comprising:

identifying a dealer located at a vehicle stop position indicated by a vehicle entering a parking state;

determining that the merchant corresponds to the offer within a tracking period defined by data included with an offer previously proposed by the vehicle;

recording data of a type specified by the data included with the offer in relation to the dock; and

reporting the recorded data and the identification of the offer.

9. The method of claim 8, wherein the data related to the docking includes a docking duration.

10. The method of claim 8, wherein the data related to the stop includes an off-route distance traveled from a predefined route for reaching the stop point.

11. The method of claim 8, wherein the tracking period is defined based on a number of vehicle trips.

12. The method of claim 8, further comprising comparing the recorded data to previously observed user data recorded for stops at the merchant to determine a change in user behavior.

13. The method of claim 12, further comprising reporting the determined change.

14. The method of claim 8, further comprising communicating with a user mobile device to determine whether data recorded by the mobile device indicates entry into the merchant.

15. A non-transitory storage medium storing instructions that, when executed by a processor, cause the processor to perform a method comprising:

determining a user stop at a merchant that previously proposed an offer in a car, the stop within a predefined time window, the predefined time window being after the offer is proposed and defined by the offer;

recording user data associated with the stop, the offer defining data to be recorded;

determining a change in previously observed user behavior recorded with respect to a brand associated with the merchant by comparing the recorded user data with previously observed and recorded data; and

reporting the deviation, the deviation including an identification of the offer.

Technical Field

The illustrative embodiments relate generally to methods and apparatus for mobile user behavior monitoring.

Background

In-vehicle infotainment systems are capable of providing a wide variety of content. From video to broadcast to streaming audio, these systems can access applications on both the vehicle and the user's mobile device.

Because of safety issues related to driving, automotive manufacturers typically retain some control over when and what content can be played. The manufacturer may also use the vehicle computer to push notifications and other information to the central display.

At the same time, persons providing offers to vehicle occupants may be interested in determining whether those occupants will respond to the offers. However, in general, offer providers have significantly less access to the vehicle computer for information collection purposes than manufacturers.

Disclosure of Invention

In a first illustrative embodiment, a system includes a processor configured to insert an offer including a tracking characteristic during playback of a media content stream. The processor is further configured to record vehicle travel data corresponding to the tracking characteristic and associated with a stored tracking characteristic stored in a vehicle memory. The processor is further configured to identify at least one change in user behavior indicated by the recorded data based on a comparison of the vehicle travel data with previously recorded vehicle data, and report the change in vehicle behavior, the recorded data, and an identification of the offer in response to identifying the change in vehicle behavior.

In a second illustrative embodiment, a method includes identifying a merchant located at a vehicle parking location indicated by a vehicle entering a parked state. The method also includes determining that the merchant corresponds to the offer within a tracking period defined by data included with an offer previously proposed by the vehicle. The method also includes recording data of a type specified by the data included with the offer in relation to the dock, and reporting the recorded data and the identification of the offer.

In a third illustrative embodiment, a non-transitory storage medium stores instructions that, when executed by a processor, cause the processor to perform a method comprising: determining a user stop at a merchant that previously proposed an offer in a car, the stop within a predefined time window that is after the offer is proposed and defined by the offer. The method further includes recording user data associated with the stop, the offer defining data to be recorded. The method also includes determining a change in previously observed user behavior recorded with respect to a brand associated with the merchant by comparing the recorded user data with previously observed and recorded data, and reporting the deviation, the deviation including an identification of the offer.

Drawings

FIG. 1 shows an illustrative vehicle computing system;

FIG. 2 shows an illustrative process for behavior tracing;

FIG. 3 shows an illustrative process for offer-based trace initialization;

FIG. 4 shows an illustrative process for comparative behavioral data collection; and is

Fig. 5 shows an illustrative example of a process for behavior analysis.

Detailed Description

As required, detailed embodiments are disclosed herein; however, it is to be understood that the disclosed embodiments are merely illustrative and may be incorporated in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimized to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the claimed subject matter.

Fig. 1 shows an example block topology of a vehicle-based computing system (VCS)1 for a vehicle 31. A vehicle equipped with a vehicle-based computing system may include a visual front end interface 4 located in the vehicle. The user can also interact with the interface if the interface is provided with, for example, a touch screen. In another illustrative embodiment, the interaction is performed by, for example, pressing a button, a spoken dialog system with automatic speech recognition and speech synthesis.

In the illustrative embodiment 1 shown in FIG. 1, a processor 3 controls at least some portion of the operation of the vehicle-based computing system. A processor 3 provided in the vehicle allows onboard processing of commands and routines. Further, the processor 3 is connected to both the non-persistent storage 5 and the persistent storage 7. In the illustrative embodiment, the non-persistent storage 7 is Random Access Memory (RAM) and the persistent storage 5 is a Hard Disk Drive (HDD) or flash memory. In general, persistent memory 5 may include all forms of memory that maintain data when a computer or other device is powered down. These memories include, but are not limited to, HDDs, Compact Disks (CDs), Digital Video Disks (DVDs), tapes, solid state drives, portable Universal Serial Bus (USB) drives, and any other suitable form of persistent memory.

The processor 3 is also connected to a number of different inputs allowing a user to interface with the processor 3. In the illustrative embodiment, the microphone 29, auxiliary input 25 (for input 33), USB input 23, GPS input 24, screen 4 (which may be a touch screen display), and bluetooth input 15 are all provided. An input selector 51 is also provided to allow the user to swap between various inputs. The input to both microphone 29 and auxiliary connector 33 is converted from analog to digital by converter 27 before being passed to the processor. Although not shown, many vehicle components and auxiliary components in communication with the processor 3 may use a vehicle network (such as, but not limited to, a CAN bus) to deliver data to and from the processor 3 (or components connected thereto).

The output to the system may include, but is not limited to, a visual display 4 and speakers 13 or stereo system output. The speaker is connected to an amplifier 11 and receives its signal from the processor 3 through a digital-to-analog converter 9. It may also be output along a bi-directional data stream shown at 19 and 21, respectively, to a remote bluetooth device such as a Personal Navigation Device (PND)54 or a USB device such as a vehicular navigation device 60.

In one illustrative embodiment, the system uses the BLUETOOTH transceiver 15 to communicate with a user's Nomadic Device (ND)53 (e.g., cell phone, smart phone, PDA, or any other device having a wireless remote network connection) via antenna 17. The nomadic device 53 can then be used to transfer a signal 59 with a network 61 outside the vehicle 31 through, for example, communication 55 with a cellular tower 57 or a Wi-Fi access point.

Exemplary communication between nomadic device 53 and BLUETOOTH transceiver 15 is represented by signal 14.

Pairing of the nomadic device 53 and the BLUETOOTH transceiver 15 can be instructed through a button 52 or similar input. Thus, the processor 3 is instructed that the onboard BLUETOOTH transceiver 15 will be paired with a nomadic device.

Data may be communicated between the processor 3 and the network 61 using, for example, a data plan, data over voice, or dual tone multi-frequency (DTMF) tones associated with the nomadic device 53. Alternatively, it may be desirable to include an onboard modem 63 having an antenna 18 for cellular transfer 16 of data between the processor 3 and the network 61.

In some embodiments, the modem 63 may establish communication 20 with the tower 57 to communicate with the network 61. By way of non-limiting example, modem 63 may be a USB cellular modem and communication 20 may be cellular communication.

In one illustrative embodiment, the processor 3 is provided with an operating system that includes an Application Programming Interface (API) for communicating with modem application software. The modem application software may access an embedded module or firmware on the BLUETOOTH transceiver 15 to complete wireless communication 14 with a remote BLUETOOTH transceiver, such as the one found in nomadic device 53. Bluetooth is a subset of the IEEE 802 PAN (personal area network) protocol. The IEEE 802 LAN (local area network) protocol includes Wi-Fi and has considerable cross-over functionality with an IEEE 802 PAN. Both are suitable for wireless communication within the vehicle. Another communication format that may be used in the art is the non-standardized consumer IR protocol for free space optical communication.

In another embodiment, the nomadic device 53 includes a modem for audio band or broadband data communication. In a data-over-voice embodiment, a technique known as frequency division multiplexing may be implemented when the owner of the nomadic device can talk over the device while data is being transferred. At other times, when the owner is not using the device, the data transfer may use the entire bandwidth (300 Hz to 3.4kHz in one example). While frequency division multiplexing may be common for analog cellular communications between vehicles and the internet and is still in use, it has been largely replaced by hybrid Code Domain Multiple Access (CDMA), Time Domain Multiple Access (TDMA), Spatial Domain Multiple Access (SDMA) for digital cellular communications. If the user has a data plan associated with the nomadic device, the data plan may allow for broadband transmission and the system may use a much wider bandwidth (speeding up data transfer). In yet another embodiment, nomadic device 53 is replaced with a cellular communication device (not shown) that is installed in vehicle 31. In yet another embodiment, the nomadic device 53 can be a wireless Local Area Network (LAN) device that can communicate through, for example, but not limited to, a Wi-Fi network.

In one embodiment, incoming data may pass through the nomadic device 53 via a data-over-voice or data-plan, through the onboard BLUETOOTH transceiver 15, and into the vehicle's internal processor 3. For example, in the case of certain temporary data, the data may be stored on the HDD 7 or other storage medium until such time as the data is no longer needed.

Additional sources that may interface with the vehicle include a personal navigation device 54 having, for example, a USB connection 56 and/or an antenna 58, a vehicular navigation device 60 having a USB 62 or other connection, an onboard GPS device 24, or a remote navigation system (not shown) having connectivity to a network 61.

Further, the processor 3 may communicate with various other auxiliary devices 65. These devices may be connected through a wireless connection 67 or a wired connection 69 (e.g., USB). The auxiliary devices 65 may include, but are not limited to, personal media players, wireless health devices, portable computers, and the like.

In addition, or alternatively, the processor 3 may connect to the vehicle-based wireless router 73 using, for example, a Wi-Fi (IEEE 802.11)71 transceiver. This may allow processor 3 to connect to remote networks within range of local router 73.

In addition to having the exemplary processes performed by a vehicle computing system located in the vehicle 31, in certain embodiments, the exemplary processes may also be performed by a computing system in communication with the vehicle computing system. Such systems may include, but are not limited to, a wireless device 53 (such as, but not limited to, a mobile telephone) or a remote computing system (such as, and not limited to, a server on a remote network 61) connected through the wireless device 53 or the vehicle modem 63. Such systems may be collectively referred to as vehicle-related computing systems (VACS). In some embodiments, specific components of the VACS may perform specific portions of the process depending on the particular implementation of the system. By way of example and not limitation, if a process has a step of sending or receiving information with a paired wireless device 53, it is likely that the wireless device 53 is not performing the portion of the process because the wireless device will not be sending and receiving information with itself. One of ordinary skill in the art will appreciate when it is inappropriate to apply a particular VACS to a given solution.

In each of the illustrative embodiments discussed herein, an illustrative, non-limiting example of a process that may be performed by a computing system is shown. With respect to each process, the computing system performing the process may, for the limited purpose of performing the process, become configured as a special purpose processor to perform the process. All processes need not be performed in their entirety and are understood to be examples of the types of processes that may be performed to implement the elements of the present invention. Additional steps may be added or removed from the exemplary process as desired.

With respect to the illustrative embodiments described in the figures that show illustrative process flows, it should be noted that a general purpose processor may be temporarily enabled as a special purpose processor in order to perform some or all of the exemplary methods shown in these figures. When executing code that provides instructions to perform some or all of the steps of the method, the processor may temporarily repurpose as a special purpose processor until the method is completed. In another example, firmware functioning in accordance with a preconfigured processor may, to the extent appropriate, cause the processor to act as a dedicated processor provided to perform the method or some reasonable variation of the method.

A vehicle manufacturer may write software that is installed to a vehicle. Thus, the manufacturer may control what information is displayed by the vehicle, and possibly, what information is presented to the vehicle occupants and when.

The content stream is a series of media content that may be presented to the occupants of the vehicle. As used herein, an offer is a presentation of media content for acceptance by a recipient for promotion of a product, service, or event. The recipient may be, for example, a vehicle occupant. Software installed to the vehicle may be programmed to replace or insert offers in the content stream. In some cases, the manufacturer may cooperate with the content provider to provide the manufacturer with information about when offers should be inserted into the content stream, as well as options as to what information should be inserted into the content stream.

The manufacturer is in the only location for monitoring user behavior after the offer because in many cases the user will require a vehicle (e.g., their own vehicle) to fulfill the offer. For example, if a user hears an offer about food and then drives to a corresponding restaurant, the vehicle is a good source of information about the trip. The vehicle may not only provide the fact that the user is traveling to the restaurant, but the vehicle may track whether the user has deviated from the route, how long the user has traveled, how far the user has deviated from the route, and the like. In addition, the manufacturer may download advertisements from a particular carrier that provides 5G services as another source of potential pluggable advertisements.

It is difficult for the offer provider to know whether the user responds to the offer, how fast the user responds, or how the user behavior may follow the offer. Furthermore, information about a single user may not provide particularly useful insight, as any given behavior may be due to a variety of factors.

On the other hand, by using the illustrative embodiments and the like, improved insight into the effectiveness of an offer may be obtained since a local fleet of vehicles may be tracked and insight into group behavior may be determined. Further, those vehicles may offer multiple offers to the same supplier, and may determine which appears most effective in changing behavior. Moreover, since the vehicle has additional driving information, and the user's "normal" driving behavior can also be observed, it is an excellent source of advance information about the user's driving habits and changes in those habits. As a team, a local fleet (in this example, no special relationship other than locality) may represent many useful data points on how to adjust for a given offer behavior.

By tracking behavior over longer periods of time (days, trips, weeks, hours, etc.) and by providing the ability to deliver various offers to the same vendor at approximately the same time in one place, the illustrative embodiments improve the ability of the vendor to test offers, determine the validity of offers, determine specific behavioral changes caused by offers, and dynamically adapt offers to those that appear most effective. The novel, rare, and atypical examples and concepts described herein represent potential improvements that may be realized through the use of those examples, concepts, and the like.

Fig. 2 shows an illustrative process for behavior tracking that may be performed by the vehicle processor 3. In this illustrative example, the vehicle processor 3 (and/or a phone application executing on the vehicle communication enabled mobile device 59) tracks user behavior to create a user reference profile. This data may be anonymized with respect to the user identity and may also be securely maintained by the manufacturer and inaccessible to any external party.

For example, the manufacturer may monitor user behavior before and after the offer and inform the advertiser about team-based observability changes based only on the monitoring (e.g., offer a causes 20% of the people to increase one additional visit to the supplier, and offer B causes 27% of the people to behave the same). This allows the manufacturer to act as a "secure" intermediary for people who do not want to share their personal behavior data directly as a controller of the vehicle data bus.

The behavior change, discussed in more detail below, may be measured by observing user behavior (via vehicle behavior) and comparing behavior for a period of time after the offer with behavior recorded before the offer was made. For example, if the offer includes a statement that the offeror's merchant location now includes live Wi-Fi, the offeror may want to track whether the user has stayed live longer during the visit to the merchant after the offer was offered as compared to the stay during the user's visit to the merchant before the offer was offered (which may indicate Wi-Fi usage). The offers themselves may include data defining the type and duration of data (e.g., number of trips, number of days, or other time parameter) to be tracked/compared for which tracking should be performed for a given offer.

In the example of fig. 2, the vehicle may detect when the vehicle is parked (out of the road network) and/or parked at step 201. Parking may represent drive-through behavior and parking may represent access to the supplier. There are many other reasons that a vehicle may be parked or stopped, and it is noted that a vehicle may ignore a stopping point while on a road network. However, even off the road, a parking lot may be relevant to many things, so the process may determine at step 203 whether there are one or more merchants associated with the parking lot or parking location. This may be accomplished by a variety of techniques including, for example, locating local merchant addresses, assigning addresses to vehicles based on location, and a variety of other cross-referencing techniques. If there is no supplier or merchant associated with the stop location, the vehicle may ignore the stop at step 205.

If one or more merchants are located near the waypoint, the vehicle may record those merchants at step 207. If the vehicle can communicate with the mobile device, the vehicle can further use the mobile device to determine which of the merchants the user has visited, as the device can track the user's walking progress and report back to the vehicle. This may help, although not necessarily, refine the profile of user behavior.

Further, there may be reasons to ignore or remove data, such as when a user is working at a location associated with a waypoint, for example. For example, if the vehicle determines at step 209 that the user is at work, the vehicle may discard data related to the particular merchant at which the user is at work and possibly any other merchants associated with the waypoint at step 211.

User behavior and vehicle behavior may help determine where the user is working, even if the user never shares this information directly. For example, if the vehicle is parked at a site for 6 to 9 hours a day for five days a week, it may be reasonably assumed that the driver of the vehicle is working at that location. Once any suitable adjustments have been made to the data, the vehicle may upload the data to associate with the vehicle or user profile at step 217. Again, the user profile may or may not have associated demographic information and may also be anonymous or non-anonymous.

Fig. 3 shows an illustrative process for offer-based tracking initialization, which may be performed by, for example, the vehicle processor 3. In this example, at step 301, the vehicle manufacturer may insert the offer into the content stream, or simply display the offer on the vehicle host unit (or play through the vehicle audio). The offer may have certain characteristics associated with it that define tracking data for the offer. Different types of offers may have different tracking parameters associated with them depending on the type of behavior they are designed to induce. For example, certain offers may be designed to create immediate behavioral changes (e.g., food offers), but may also request tracking for several days to see if there is a net change in behavior. On the other hand, offers for new cars or other expensive items may require several days, weeks, or even months of tracking to determine how the user responds.

In one example, the manufacturer may track a common set of behavior parameters for certain offers over a predefined period of time, and in other examples, the offers themselves may specify the tracking parameters (e.g., time, type of behavior, duration of stops, off-route travel, etc.). In examples where the offer includes tracking characteristics, the vehicle may record characteristics for tracking user behavior at step 303. This may include locally recording the characteristics on the vehicle and pushing the characteristics to the application of the mobile phone 53 in communication with the vehicle (if in communication is determined at step 307) at step 311. The mobile phone 53 may continuously track the data while outside the vehicle or according to tracking characteristics, and the vehicle may obtain this information from the mobile phone 53 at the appropriate time when the vehicle is in communication with the device.

The vehicle may also set tracking parameters at step 305, which may be related to tracking characteristics associated with the offer. Since the vehicle may play hundreds of offers per week, each offer may have various tracking characteristics set up with it, and any behavior corresponding to those characteristics may be tracked by the vehicle at step 309.

For example, on a given route, a user may stop at a grocery store, which may be tracked based on the grocery store's offer (e.g., the stop point and duration may be tracked). The vehicle may then have a planned route to the driver's workplace, but may deviate by 10 minutes or 2 miles to obtain food, which may be tracked according to food offer (e.g., stop points, deviations, and time of day may be tracked), and then may continue to travel and complete the route. Each offer (grocery store and food) may already have a corresponding tracking parameter associated with it that specifies what is to be tracked. In other examples, the vehicle may track a fixed set of data, and the characteristics may simply specify how long the tracking should occur.

As the vehicle travels during the time period associated with each offer (which may be measured by, for example, time units or number of trips), when the vehicle parks or parks at the destination or location, the vehicle may compare this information to the providers associated with the various offers tracked at step 313. That is, if no particular vendor is provided with the offer to be tracked, the docking data may be processed to track normal user behavior. Normal user behavior may be tracked such that there is a basis for comparison when a given offer requests a change in user behavior in response to the offer.

When the given parameter/characteristic time period expires at step 315, the vehicle may then remove any duplicate data at step 317. The duplicate data includes data corresponding to data repeatedly tracked by, for example, the mobile device and the vehicle. The vehicle may then send the results to a reporting server or offer provider at step 319. The vehicle may also report, at 319, that data or data representations were collected that deviate from previously observed behavior, either periodically or at any time.

Fig. 4 shows an illustrative process for comparative behavioral data collection, which may be performed by, for example, the vehicle processor 3. For example, the illustrative process may be performed any time docking data is detected. If the vehicle detects a parked or parked condition at step 401, the vehicle may again determine any merchants associated with the parking at step 403.

Then, in this example, the vehicle may check the stored offer data at step 405 to determine whether any offers tracked for it correspond to merchants determined to be relevant to the parking location. This may include, for example, communicating with the user's mobile device to determine whether the device's recorded location or other data indicates that the user actually entered the merchant. If many merchants (e.g., shopping malls or retail stores) may be associated with a waypoint, this ancillary information may help narrow the range of the particular merchant that the user enters.

If the merchant corresponds to an offer for which tracking is enabled, and/or if the user enters the merchant (if secondary communication with the mobile device is enabled and used), the vehicle may associate any detected behavior with the user or the vehicle at step 407.

The data collected by the vehicle may be compared to previously observed user behavior for the same merchant (or brand) or for one type of merchandise. For example, the user may have traveled 10 minutes off the route to reach the merchant, and historically, the user may only travel 3 minutes off the route on average to obtain similar goods or access the brand. The change may be observed based on the comparison and may be due to the user hearing the offer. Thus, the change or deviation and brand or offer may be reported to a central server for processing as it may tend to indicate the effectiveness of the offer for that particular user. In the aggregate (among a group of users), this data may indicate that it is more likely to be due to observable changes in the behavior of the offer if observed among a certain percentage of the people receiving the offer.

Fig. 5 shows an illustrative example of a process for behavior analysis. This process may be performed by the vehicle processor 3 or, for example, by a remote server (remote from the vehicle) on the remote network 61. This shows some illustrative factors that may be considered when evaluating changes in behavior caused by an offer. Since the vehicle is able to track both normal behavior (behavior not associated with a tracking period after the offer) as well as behavior occurring during an offer-specified period (or a period associated with the offer if the standard tracking period is specified by the manufacturer). The offer may include metadata specifying a tracking time period, and parameters defining the type of data to track changes. Some suppliers may be indifferent, for example, how far the user has traveled off the route, but may be more concerned about how long the user has spent at one location. Others may be concerned whether they may attract the user to off-course locations, but may not be as relevant as how long the user spends at their location.

The illustrated example illustrates the types of changes that can be tracked, but is not limited to these types. The vehicle may receive the tracking data at step 501 and determine at step 503 whether the behavior is associated with a tracking period defined by the offer. If the data is not associated with any particular tracking, the vehicle may record the data as normal or standard user behavior and store a profile about the user or vehicle at step 505.

On the other hand, if the data is associated with a tracked offer, the vehicle may determine any number of deviations from standard behavior (represented by the increments in the figure). In this example, the process may determine an increment in access frequency at step 507 by comparing how frequently the vehicle is parked at a given location or a location associated with a brand during the tracking period with previously observed and recorded normal behavior, for example. This particular data point may need to track multiple stops at one location during the tracking period so that a fair comparison of access frequencies can be observed.

At step 509, the vehicle may also determine a deviation in duration between the stop at the location and a standard stop at the merchant, the brand or merchant being associated with a particular type of merchandise. This may include measuring the duration of one or more stops during the tracking period and comparing it to the average duration of previously observed and recorded standard stops, and comparing the measured duration to the longest recorded standard stop and/or time range, e.g., representing the recorded standard stop.

At step 511, the vehicle may also determine how long since the offer was heard, which may be used as an indicator of the effectiveness of the offer, since the longer the user has heard the offer, the less likely the behavior is to be affected by the offer (particularly for goods that are repeatedly purchased, such as fuel and food).

At step 513, if purchase data is available, the vehicle may additionally determine a change in payout. This may require communication with an on-board purchasing system and/or a mobile device purchasing or payment system included in the tracked vehicle and may also require user approval (as all data may be collected). At 515, any and all changes from previously observed and recorded standard behavior indicated by data tracked outside the ad tracking window may be reported by the vehicle.

The offer provider may also have an incentive to set the appropriate time window for offer tracking to avoid attributing standard user behavior to the offer. That is, an excessively long time window may result in the tracking behavior no longer reflecting that the offer has been heard. In other examples, a manufacturer may impose limitations on when data may be tracked, what data may be tracked, and for how long.

The illustrative embodiments allow improved observation of user behavior via vehicle tracking after an offer is placed. Since the vehicle is able to determine both the fact that the offer was made and the driving behavior after the offer, it can observe how the user behavior changes for a period of time after the offer. Further, the vehicle may track behavior data for hundreds of offers at a time, and the aggregation of this data may provide an improved snapshot of how certain offers affect group behavior over time.

While exemplary embodiments are described above, these embodiments are not intended to describe all possible forms of the invention. Rather, the words used in the specification are words of description rather than limitation, and it is understood that various changes may be made without departing from the spirit and scope of the invention. Additionally, the features of the various implementing embodiments may be combined in a logical manner to produce contextually suitable variations of the embodiments described herein.

According to the invention, a system is provided having: a processor configured to insert an offer including a tracking characteristic during playback of a media content stream; storing the tracking characteristic in a vehicle memory; in response to storing the tracking characteristic, recording vehicle travel data corresponding to the tracking characteristic; identifying at least one change in user behavior indicated by the recorded data based on a comparison of the vehicle travel data with previously recorded vehicle data; and in response to identifying a change in vehicle behavior, reporting the change in vehicle behavior, the logged data, and the identification of the offer.

According to one embodiment, the processor is further configured to transmit the tracking characteristic to a mobile device in communication with the vehicle.

According to one embodiment, the processor is further configured to exchange information with the mobile device to obtain tracking information collected by the mobile device corresponding to the tracking characteristics.

According to one embodiment, the tracking characteristic comprises a duration for which the tracking should last.

According to one embodiment, the duration is measured in number of strokes.

According to one embodiment, the tracking characteristic includes tracking a docking duration at a docking location associated with the offer.

According to one embodiment, the tracking characteristic comprises tracking a off-route travel time or distance from a predefined route for reaching a stop associated with the offer.

According to the invention, a method comprises: identifying a dealer located at a vehicle stop position indicated by a vehicle entering a parking state; determining that the merchant corresponds to the offer within a tracking period defined by data included with an offer previously proposed by the vehicle; recording data of a type specified by the data included with the offer in relation to the dock; and reporting the recorded data and the identification of the offer.

According to one embodiment, the data related to the docking includes a docking duration.

According to one embodiment, the data relating to the stop comprises a distance off-course traveled from a predefined route for reaching the stop point.

According to one embodiment, the tracking period is defined based on a number of vehicle trips.

According to one embodiment, the invention also features comparing the recorded data to previously observed user data recorded for a stop at the merchant to determine a change in user behavior.

According to one embodiment, the invention also features reporting the determined change.

According to one embodiment, the invention also features communicating with a user mobile device to determine whether data recorded by the mobile device indicates entry into a merchant.

According to the present invention, a non-transitory storage medium stores instructions that, when executed by a processor, cause the processor to perform a method comprising: determining a user stop at a merchant that previously proposed an offer in a car, the stop within a predefined time window, the predefined time window being after the offer is proposed and defined by the offer; recording user data associated with the stop, the offer defining data to be recorded; determining a change in previously observed user behavior recorded in relation to a brand associated with the merchant by comparing the recorded user data to previously observed and recorded data; and reporting the deviation, the deviation including an identification of the offer.

According to one embodiment, the change comprises an increase in frequency of access of the vehicle to the brand over a predefined period of time.

According to one embodiment, the change comprises an increase in the duration of time the vehicle spends at the stopping point.

According to one embodiment, the change comprises an increase in the amount of money spent by the vehicle occupant at the merchant.

According to one embodiment, the reporting further comprises reporting a duration since the offer was offered.

According to one embodiment, the time window is defined based on a number of vehicle trips.