KR20220153251A - On-offline marketing optimization method and marketing solution using it - Google Patents

Abstract

According to the present invention, a marketing optimization system triggers an offline marketing action based on online behavior. The system stores a trigger event including conditions for each trigger event. The system also stores captured online behavior. In addition, the system includes an on-offline channel campaign engine configured to determine whether a condition from the captured online behavior is met with respect to the trigger event. If the condition is met, the on-offline channel campaign engine triggers the offline marketing action associated with the trigger event. Moreover, the system also optimizes the trigger event based on analysis of the captured online behavior. According to the present invention, a website trigger optimization system for driving on-offline channel operations is provided.

Description

On-offline marketing optimization method and marketing solution using it {On-offline marketing optimization method and marketing solution using it}

It is about an on-offline channel marketing solution that analyzes online behavior and provides it for use in offline marketing.

Conventional web servers track visitors to their web sites through cookies or through log-ins. For example, many e-commerce sites store unique identifiers in customer databases that are used to identify site visitors. In addition, the database may store information about the behavior of the visitor, such as the pages they visited, the products they viewed, and the actions they took (eg, products purchased, items clicked, etc.).

Some web sites use their visitors' captured behavior to recommend products that the visitor might be interested in purchasing based on products the visitor has previously viewed. This is done while the user is on the web site. However, in addition to recommending a product or providing the user with some other product-related information when the user is on the website, companies often conduct captured actions on non-online channels, referred to as offline channels. not available For example, a company may engage in a mail advertising campaign or a telephone campaign. However, companies cannot target their mail advertising campaigns or phone campaigns based on the online behavior of visitors to a brand's website.

An object of the present invention is to provide an effective marketing solution using a website trigger optimization system that drives on-offline channel operation.

According to one embodiment, the system triggers offline marketing actions based on online behavior. The system includes a variable definer configured to create a variable by creating a graphical user interface that allows a user to enter an expression using a predetermined syntax. The expression includes an online behavior and a condition associated with the online behavior for each variable. The variable definer is configured to store the variable, including the expression. The system also includes a trigger definer and an on-offline cross-channel campaign engine. The trigger definer is configured to generate trigger events using at least one of the stored variables, each trigger event including at least one condition and an offline marketing action. The on-offline channel campaign engine is configured to compare conditions in the trigger event with captured online behavior using a computer system and determine from the comparison whether all conditions are satisfied with respect to at least one of the trigger events. . If all of the above conditions are met with respect to the trigger event, an indication is sent to the application to trigger the offline marketing action.

According to one embodiment, a method for triggering an offline marketing action is based on captured online behavior. The method includes storing captured online behavior received from a browser or web server, generating a variable describing an aspect of the captured online behavior, and triggering an event using at least one of the stored variable. and generating each trigger event includes at least one condition and an offline marketing action. The method comprises comparing conditions in the trigger event with the captured online behavior, determining, by a computer system, from the comparison whether all of the conditions are met with respect to at least one of the trigger events; and and sending an indication to the application to trigger the offline marketing action if all conditions are met with respect to the triggering event.

The method for triggering an offline marketing action may be performed by software consisting of computer instructions stored on a non-transitory computer readable medium. The software, when executed, performs the method by the computer system.

According to the present invention, a website triggered optimization system for driving on-offline channel operations is provided.

Embodiments of the present invention will be described in detail in the following description with reference to the following drawings.
1 shows a system, according to one embodiment.
2A-2C show example screen shots that can be used to enter information to define variables, according to one embodiment.
3 illustrates a method for triggering an offline marketing action, according to one embodiment.
4 illustrates a method for optimizing a trigger event, according to one embodiment.
5 illustrates a computer system that serves as a hardware platform for the systems and methods described herein, according to one embodiment.

For simplicity and illustrative purposes, the principles of the present embodiments are described primarily with reference to examples. In the following description, numerous specific details are set forth in order to provide a clear understanding of the present embodiments. However, it will be apparent to those skilled in the art that the present embodiment may be practiced without being limited to these specific details. In some instances, well known methods and constructions have not been described in detail in order not to unnecessarily obscure the present embodiments. Also, different embodiments are described below. The present embodiments can be used or performed together in different combinations.

According to one embodiment, the marketing optimization system is configured to trigger offline marketing actions based on captured online behavior and customizable trigger events. Captured online behavior may include any measurable or trackable event of a visitor to a web site on the Internet. This includes actions performed on a web page, such as the object clicked on, the web page visited, the identification of the visited web page or web site that brought the visitor to the web site, and the search performed on the search engine that identified the web site. It may include the identification of keywords of Once the visitor characteristics are identified, the captured online behavior may include the visitor characteristics.

Offline marketing action includes any action performed outside the website. For example, an offline marketing action may include sending marketing-related information through mail, e-mail, SMS text message, phone call, or other offline channel. The information may include coupons, offers, product information, or other types of marketing information. An offline marketing action may include setting a flag in a database that provides an indication that a condition or set of conditions is met. Note that offline marketing actions may include actions that are not performed over the Internet.

When a trigger event is detected, an associated offline marketing action is performed. A trigger event can include one or more conditions. Conditions can be associated with online behavior that can be detected and tracked. For example, if all conditions for a tracking event are met, a corresponding offline marketing action is triggered.

The marketing optimization system includes a user interface that allows a user to create and store a trigger event, and the trigger event can be changed as the user needs. Thus, trigger events can be customized by the user by allowing the user to define an arbitrary catchable set of events for triggering offline sales and marketing campaign actions. This ability allows marketers to explore many potential events and explore triggers for optimal targeting of marketing. Also, the triggering event is not hard coded into, for example, a web page, so no Information Technology (IT) administrator is required to customize or otherwise change the triggering event. Thus, the marketing optimization system may be off the web site and used to trigger offline marketing actions based on customizable triggers.

The marketing optimization system is also configured to organize raw data about online and offline user behavior through the use of customizable variables that assign semantic meaning to the data. The variables can be used for reporting, analysis and automatic optimization, and to provide triggering of offline marketing actions. One technical aspect of an embodiment provided through the variable definer of the marketing optimization system involves inputting an expression through a user interface using a predetermined syntax and/or format. The expression allows the user to enter data through the user interface to create variables that can be used to define trigger events. Variable definers allow variables and trigger events to be changed on the fly through the use of the formulas, as opposed to being hard-coded into a web page or software. Thus, variables and trigger events can be easily changed in response to feedback from newly captured online behavior, and variables and trigger events can be changed by non-IT personnel responsible for optimizing trigger events. have.

It is also noteworthy that cross-channel marketing campaigns can have relatively high contact costs.

For example, the cost to introduce phone-based marketing can be expensive. According to one embodiment, the marketing optimization system is configured to determine optimal triggering events and optimal triggered marketing actions to maximize sales.

Optimization may consider the cost of an offline marketing action as well as the probability of achieving sales and the value of sales if sales are achieved. Thus, the Marketing Optimization System matches the right trigger event with the correct follow up method to ensure that the trigger event results in an overall contact method that creates more value than cost.

1 illustrates a marketing optimization system 100, according to one embodiment. Online activity 102 is captured from web sites 101a-101n. In one embodiment, scripts and plug-ins are used to capture online behavior 102 . For example, a JAVA script or other type of script is provided within the web page, and the script instructs the web server to store online behavioral events and transmit them to the marketing optimization system 100 . For example, JavaScript on the home page of web site 101a instructs the web server to store the keyword phrases that caused the visitor to visit the web site, the web site the visitor came from, and the actions performed by the visitor on the home page. can do. The plug-in provides additional functions on the web page, and as the functions are performed, data is stored and transmitted to the marketing optimization system 100 as directed by the script. In one example, a visitor to any of the web sites 101a - 101n is assigned an anonymous ID, and the captured online behavior is associated with the ID and stored along with the ID in the marketing optimization system 100, for example in a database 110. do. The ID can later be correlated with customer contact information to provide offline marketing information to the customer associated with the triggering event and the captured online behavior about the customer. Online behavior may also be captured by a web browser and transmitted to a web server or marketing optimization system 100 . Marketing optimization system 100 may also store and retrieve data from data store 140 . Data used by marketing optimization system 100 may be stored in database 110 and/or data store 140 .

The marketing optimization system 100 includes a trigger definer 115 , a variable definer 116 , a trigger optimizer 117 , an on-offline channel campaign engine 111 and a user interface 112 . Trigger definer 115 and variable definer 116 create and store trigger events 103 and variables 104 in database 110 and/or data store 140, as described in detail below. The trigger definer 115 and the variable definer 116 allow information about trigger events 103 and variables 104 to be provided and customized by the user through the user interface 112, and trigger events to be optimized. . User interface 112 may be an online interface that allows a user to log into marketing optimization system 110 and enter and customize trigger events 103 and variables 104 . Other information may be entered by the user and presented to the user via the user interface 112 . Note that FIG. 1 depicts trigger events 103 and variables 104 received by system 100 . However, as described herein, it may include information about trigger events 103 and variables 104, which information is used by trigger definer 115 and variable definer 116 to A trigger event (103) and a variable (104) are created.

Each trigger event 103 may include one or more conditions and one or more offline marketing actions. Conditions must be met to trigger the corresponding offline marketing action identified in the trigger event. Examples of conditions within a trigger event would include a customer clicking on an object for a particular product, a customer not purchasing a product, and a customer leaving the website without making a purchase and not returning to the website within 24 hours. can An example of an offline marketing action for this condition would be to call or text a customer with an offer related to a product that has not been purchased. An additional condition may be added to the trigger event to ensure that only customers who enter the site from a branded client keyword phrase from Google are included in the offline campaign presenting the offer.

Another example of a trigger event is related to subsequent sales. For example, the condition is that the user has purchased a particular product online, but has not purchased any accessories for that product within two weeks of the product's delivery date. An offline marketing action in response to such a trigger event may include sending the customer an offer or coupon on the accessory. It will be clear to one skilled in the art that these are only some examples of trigger events and other types of conditions and offline marketing actions may be included in trigger events.

The marketing optimization system organizes raw data about online and offline user behavior through the use of customizable variables 104 that assign semantic meaning to the data. Variable 104 can be used for reporting, analysis and automatic optimization, and to provide triggering of offline marketing actions. Variables can be used in trigger events (103).

The on-offline channel campaign engine 111 determines whether all conditions are met for each triggering event by any visitor to web sites 101a-101n. If all conditions are met with respect to the triggering event, the on-offline channel campaign engine 111 triggers the offline marketing action, shown at 113 , identified by the triggering event.

For example, the on-offline channel campaign engine 111 queries the database 110 to determine whether the captured online behavior 102 for each visitor includes all conditions relating to any of the triggering events 103. do. The captured online behavior 102 may be associated with a unique ID for each visitor. The offline marketing action identified by the trigger event is triggered if all conditions are met, for example by a single visitor. A unique ID can be matched with customer contact information to identify a customer (eg, a web site visitor with all matching conditions) and send him or her promotional information, or perform other offline marketing actions on the customer.

Triggering an offline marketing action may include sending to the application 120 a list of visitors that are determined to meet all conditions for the triggering event. The list may be transmitted in real time upon all conditions being satisfied or may be transmitted on a periodic basis, eg hourly or daily. Application 120 may be an external system that performs offline marketing actions. Application 120 may be used by marketing personnel to perform offline marketing actions, such as telephone marketing campaigns. Figure 1 shows applications 120 connected to customers 130a-130f via offline channels 121a-121d. The offline channels 121a to 121d may include phone calls, postal mail, e-mails, and text messages. An offline marketing action such as sending promotional information through the offline channels 121a to 121d may be performed through the offline channels 121a to 121d.

Triggers 113 may include additional information about each customer regarding how the offline marketing campaign should be executed. For example, trigger 113 may identify an offer to be presented and a channel to use to contact the customer.

Further, after the campaign is executed, response data about each customer may be provided to the marketing optimization system 100 or application 120 to enable subsequent offers and communications.

Data store 140 may be connected to marketing optimization system 100 . Data store 140 may contain customer data and other information provided by systems external to marketing optimization system 100 . For example, data store 140 may store a customer ID and associated customer contact information, which, as noted above, is correlated with a unique ID that identifies the captured online behavior for each customer.

In one embodiment, data store 140 stores purchases made and other successful sales results for each customer using the customer ID. Captured online behavior 102 and purchases (eg, online and in-store) and other business information (eg, customer interest in products, preferences regarding demographics, etc.) from other systems may be collected and stored in data store 140. have. Another system may include a data capture system 150 that provides purchase and sale information 151 to a data store 140 . Data capture system 150 may include an accounting system or other conventional system for tracking sales related information. Other systems may also include a trial system that provides trial feedback 161 associated with trial trigger events and marketing actions that were successful or unsuccessful in triggering sales. Although experimentation system 160 is shown in FIG. 1 as a system external to marketing optimization system 100 , experimentation system 160 may be part of marketing optimization system 100 instead of or in addition to an external experimentation system.

The experimentation system 160 performs controlled experiments on one or more web sites 101a - 101n so that different visitors receive different offers and different experiences. These online experiments are coordinated with multivariate experiments taking place offline by including the appropriate variables in a list generated by the marketing optimization system 100 that identifies customers to be targeted by offline marketing actions. Variables may identify changes in offers made for different customers or other changes in offline marketing actions that may change with respect to different customers. Data store 140 stores information about coordinated online and offline trials, including variables and affected customers, and receives and stores results of trials. The result includes the result of a changed offline marketing action, such as associated with a subsequent purchase. These results may be used by the marketing optimization system 100 and other systems as feedback to control experiments to automatically determine the best website content, best triggers, best offers, best customer contact rules, etc. to increase sales. . Accordingly, the marketing optimization system 100 implements offline marketing actions and online experiences (eg, altered web pages or other altered online content) that are determined to be most successful in generating sales, thereby combining online and offline content and actions to increase sales. configured to optimize itself.

For example, the marketing optimization system is used for experiments to test different trigger events and conditions and to test different triggered online and offline marketing actions for test groups. Trigger events can be captured online actions and can be defined by a number of conditions that need to be met to trigger online and/or offline marketing actions with respect to different test groups.

A test group may be a different set of users/people with the same set of predetermined graphics. In a simple example, an experiment is designed to test the response to a marketing action regarding luxury vehicles in relation to men over 40 with an income over $150,000. Three sets of users with these characteristics are identified. The condition may be clicking on one or more predetermined keywords used in a search engine and a specific URL within the search results. One trial group may receive mail advertisements, another trial group may receive email advertisements, and a third trial group may receive phone calls containing promotional information.

Responses from each group are measured to determine which marketing actions are most effective in eliciting customer responses. Also, revenue can be measured as a result of different actions. Various experiments can be run with different demographics and different products to identify the most effective marketing actions, and then these actions can be implemented. Also, different conditions or sets of conditions for triggering events and different types of promotions can be evaluated empirically. Also, different online experiences can be provided to different test groups by changing the web page for each test group and then capturing the test group's online behavior.

The experiments provide a mechanism to obtain feedback and evaluate performance to determine the most effective trigger events and marketing actions to increase sales or achieve other sales goals, in a controlled environment. In addition, the experiment is implemented quickly and easily through customizable trigger events.

Experimentation may include determining an experiment trigger event for each incoming website visitor. A set of variables to be tested is identified and implemented within the trigger event for the test. The system determines whether an offline marketing action will be triggered by detecting a state change regarding a variable within the trigger event. For example, if the system determines that a change in status has occurred with respect to all event variables within a trigger event assigned to a given visitor, the system triggers additional (on-offline channels) campaigns to include the visitor. Performance data such as sales from additional (on-offline channels) campaigns are analyzed along with trigger event/variable selection to determine the (optimal) set of variables to track for every (non-experimental) visitor, which is the maximum of successful follow-up. The goal is to make the most efficient use of the high outbound contact costs inherent in such campaigns by targeting outbound contact campaigns to visitors with a probability.

Trigger optimizer 117 uses information from systems 150 and 160 to identify trigger events and marketing actions to implement. For example, based on feedback regarding the success of the triggered offline marketing action (eg, whether a purchase was made), the trigger definer 115 can send notifications about specific offline marketing actions to trigger on different customers to increase sales. You can make an informed decision. This may include triggering different offline marketing actions than those specified in the trigger event that was determined to be successful for a particular customer or group of customers with similar characteristics.

In addition to optimizing offline marketing actions, trigger optimizer 117 may also define trigger events based on analysis of data from systems 150 and 160 . The analysis may identify trigger events for different users that are determined to be most likely to result in revenue. Trigger optimizer 117 can also identify trigger events and offline marketing actions that ensure that trigger events can result in an overall contact style that creates more value than cost. Trigger optimizer 117 may also generate recommendations to users via user interface 112 to customize trigger events to include offline marketing actions determined to be successful.

In one example, a trigger event is triggered with respect to customer 130a based on customer 130a's online behavior and conditions of the triggering event. A corresponding offline marketing action is performed, which in this example sends a coupon offer to customer 130a via SMS text and then calls customer 130a to remind customer of the coupon offer if a purchase is not made within a predetermined time period. will be. Customer 130a makes a store purchase or online purchase using the coupon after the call. Data store 140 stores all information about the transaction, including offline marketing actions performed (ie, SMS texts and follow-up calls with coupon offers) and results of offline marketing actions (ie, purchases). Based on feedback regarding the success of the triggered offline marketing action (eg, whether a purchase was made), the trigger definer 115 determines the specific offline marketing action to trigger on different customers to increase sales. can make a decision This may include triggering offline marketing actions other than those specified in trigger events that have been determined to be successful for specific customers or groups of customers with similar characteristics. This may also include recommending to the user via the user interface 112 to customize the trigger event to include the offline marketing action determined to be successful. Such an offline marketing action may be implemented.

As previously described, variable definer 116 may be used to create variables that give semantic meaning to raw data about online and offline user behavior stored in data store 140 . The variable definer 116 may use the user interface 112 to allow a user to create a variable defining a base event from collected data. 2A-2C show screen shots 201-203 that may be generated by variable definer 116 via user interface 112 to allow a user to define variables that contain basic events. Screenshot 201 of FIG. 2A is where the user begins the process of defining a new variable. A variable name is entered, in this example "Mobile Searcher". Additionally, filtering and editor options can be selected.

Screenshot 202 of FIG. 2B shows the information that can be entered regarding the new variable. A variable function can be selected, in this example "Boolean". Also, expressions describing variables can be entered in the expression section 211 . An operation describing the underlying event can be entered into the expression. Examples of operations that can be entered are shown as possible operations 210 . “Facts” of possible operation 210 may refer to a user's captured actions or actions. The captured action is stored, for example, in data store 140 .

"Facts-After" can be used to identify any captured action performed after a certain event has occurred, whereby the event can be expressed in an expression. Similarly, “Facts?Before” can be used to identify any captured action performed before a given event occurs, whereby the event can be expressed in an expression. "Facts-Matching-Regex" can be used to identify actions associated with a string.

"Find-All-Facts-With-Value" can be used to identify specific actions associated with values. "Find-Coincident-Facts" is used to identify concurrent actions, such as actions performed together or in brief succession.

“Remove-Duplicate-Facts” may be used to remove duplicate stored actions for the same user from the data store 140 . For example, the same action on a user may have been captured by two different systems and stored in a data store, and one may be removed.

The expression shown in section 211 includes a "Facts-Matching-Regex" operation. This operation is being used to identify the action associated with the string "mobile", which action is defined as "<SearchedFor>". A "<SearchedFor>" action refers to a user action performing a search on a web site. The expression above can also return a value. For example, the variable will have a value of 1 if the user performs a search on a web site that contains "mobile". Otherwise, the value is zero.

The equations shown in FIG. 2B are an example of one or more technical aspects of this embodiment. The expression allows the user to input data through the user interface to create variables that can be used to define trigger events. Variable definers allow variables and trigger events to be changed directly through the use of expressions, as opposed to being hard-coded into a web page or software. Thus, variables and trigger events can be easily changed in response to feedback from newly captured online behavior, and variables and trigger events can be changed by non-IT personnel responsible for optimizing the trigger event.

2C shows a screen shot 203 displaying the properties of the “mobile searcher” variable after it has been created. The formula type, filtering range and formula are shown. Additionally, the property may identify any marketing campaign for which the variable is used and variable dependencies such as "<SearchedFor>".

After variables are created, they may be stored in database 110 and/or data store 140 . Some of the variables can be used for report generation and other operations, and some of the variables can be used for trigger events. Variables that can return values can be used for triggering events. For example, the variable “mobile searcher” may return a value of 1 or 0 depending on whether or not a search including “mobile” is performed. Variables and values can be used as conditions within trigger events to trigger offline marketing actions. For example, if the "mobile searcher" variable returns a value of 1 and the user performing the search is known to have purchased a mobile phone data plan, triggering a text message describing the new data plan to be sent to the user. Including trigger events can be defined.

Trigger definer 115 can be used to create trigger events similar to creating variables using the screenshots described above. For example, the trigger definer 115 allows a user to input an expression describing a trigger event through the user interface 112 . Trigger events are stored in database 110 and/or data store 140 .

3 illustrates a method 300 for triggering an offline marketing action, according to one embodiment. The method 300 and other steps described herein may be described with respect to FIG. 1 for purposes of illustration and not limitation, and may be performed in other systems.

At step 301 , the captured online behavior is stored, for example, in data store 140 . Captured online behavior includes information received from the user's web browser, web server, data capture system 150 and/or data capture system 160.

can do.

At step 302, variable definer 116 creates variables that describe aspects of the captured online behavior. Variable definer 116 may create a variable by generating a graphical user interface that allows a user to enter an expression using a predetermined syntax. 2A to 2C show examples of screen shots for inputting formulas for defining variables and other information. Variables can identify one or more online actions and can contain one or more conditions that can be used in trigger events.

At step 303, variable definer 115 generates a trigger event using at least one of the generated variables. Each trigger event may include at least one condition and an offline marketing action. Trigger events can be created using a graphical user interface and expressions, similar to creating variables.

At step 304, the on-offline channel campaign engine 111 compares the conditions in the trigger event to the captured online behavior. For example, the on-offline channel campaign engine 111 may determine whether a condition within a trigger event is met. If the condition identifies an action performed by the user or a property of the user, then the condition is met if the user performs that action or if the user's property matches an attribute in the trigger event.

If all conditions as determined in step 305 are met with respect to the triggering event, then in step 306 the offline marketing action within the triggering event is executed. Step 306 may be performed with respect to any triggering event for which its condition is met. If all conditions are met with respect to the trigger event, action may include sending an indication to the application 120 to trigger the offline marketing action. Method 300 may be repeated if no trigger event is triggered. Method 300 may be repeated periodically or continuously.

4 illustrates a method 400 for optimizing a trigger event according to one embodiment. One or more steps of method 400 may be performed by trigger event optimizer 117 . At step 401, the cost of performing offline marketing on the trigger event is determined. Costs can be determined from external systems and administrators. For example, the cost of performing a follow-up call origination may include employee costs, service fees, and the like. The cost may be provided to the marketing optimization system 100 by an external system or may be determined from cost information provided to the marketing optimization system 100 .

At step 402, the probability of achieving sales in response to executing an offline marketing action is determined. Probabilities may be determined from the results of experiments performed by experimentation system 160 and/or may be determined from analysis of sales history data in response to offline marketing. Conventional statistical analysis can be used to determine probabilities.

In step 403, the value of potential sales is determined. Value can be profit from sales, or another sales measure or combination of sales measures can be used to determine value. Examples of revenue metrics for determining value may include customer acquisition, up-sell potential, profit, and the like.

At step 404, the trigger optimizer 117 determines whether to change the trigger event based on cost, probability and value. This may include multiplying the value by the probability or otherwise weighting the value based on the probability and comparing the result to the cost. If the cost exceeds the value, the triggering event can be changed at step 405 . Other statistical analyzes can be used to compare cost to value. Changing the triggering event in step 405 may include using a different condition or other offline marketing action in the triggering event. The selection of a change may be based on an analysis that considers the same factors such as cost, probability and value. It should be noted that the optimization in method 400 can be performed on an existing trigger event or when creating a new trigger event. Additionally, method 400 may be repeated periodically or continuously.

One or more steps of the methods described herein, other steps described herein, and one or more components of the systems described herein may include non-transitory computer readable data storage, such as memory and/or other tangible data storage. It may be implemented as computer code stored on a medium and executed on a computer system, for example, by a processor, application-specific integrated circuit (ASIC), or other controller. A computer readable medium may have non-transitory properties. The code may exist as software program(s) consisting of source code, object code, executable code, or program instructions in another format. Examples of computer readable media include conventional computer system RAM, read only memory (ROM), erasable, programmable ROM (EPROM), electrically erasable, programmable ROM (EEPROM), hard drive, and flash memory.

5 shows a hardware platform of a computer system 500 that can be used to execute computer code that realizes the steps and functions described above. Computer system 500 may be a hardware platform for one or more of the components of system 100. Computer system 500 includes a processor 502 that can implement or execute software instructions to perform some or all of the methods, functions and other steps described herein. Commands and data from processor 502 are communicated over communication bus 504 . Computer system 500 also includes main memory 503, such as random access memory (RAM), in which software and data for processor 502 may reside during run time, and which may be non-volatile and may store software and data. It includes a secondary data store 508 to store. Memory and data storage are examples of computer readable storage media. Computer system 500 may include one or more input/output devices 510 such as a keyboard, mouse, display, and the like. Computer system 500 may include a network interface 512 for connecting to a network. It will be apparent to those skilled in the art that other known electronic components may be added to or substituted for computer system 500.

Although this embodiment has been described with reference to examples, those skilled in the art will be able to make various changes to the described embodiment without departing from the scope of the claimed embodiment. For example, optimization performed by the system may be used to optimize trigger events for non-marketing events.

100: marketing optimization system
110: database
120: application
130a-130f: customer
140: data storage
150: data capture system
160: experimental system

Claims (3)

A system for triggering one or more offline marketing actions based on online behavior, comprising: a variable definer configured to create a variable by creating a graphical user interface that allows a user to enter an expression using a predetermined syntax; compare conditions within the trigger event to captured online behavior using a trigger definer configured to generate trigger events using at least one of the stored variables, and if all of the conditions relate to at least one of the trigger events An on-offline marketing optimization method configured to determine from the comparison whether or not all of the above conditions are satisfied, and to trigger the offline marketing action by sending an instruction to an application when all the above conditions are satisfied with respect to the at least one trigger event, and a marketing solution using the same According to claim 1,
a trigger event optimizer configured to optimize the at least one trigger event based on a cost of performing the offline marketing action and a probability of achieving sales in response to executing the offline marketing action with respect to the at least one trigger event. A more inclusive system. According to claim 2,
wherein the trigger event optimizer is further configured to determine whether to change the at least one trigger event based on the cost, the probability, and the value of revenue.

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