Flexible, integrated marketing and data technology stack accessible through a single-line code implementation

Abstract

A computer-implemented method includes loading, using a browser, a webpage containing a unified (UNI) tag. Using a tag worker of a cloud-based serverless platform that evaluates a host / request from the browser, a partner configuration is sent to the browser to dynamically load a partner-configured client-side scripts, where the partner-configured client-side scripts permit automatic modification of data collection to anonymize users, prevent data from collection, or to collect user identifiers. Using the browser, a call is generated to an event worker of the cloud-based serverless platform. Data about an event is sent by the event worker to an event endpoint. A hypertext transfer protocol (HTTP) endpoint is provided by the event endpoint for the event worker to post to. A validate worker forwards event data to a bucket publish worker or an enrichment worker.

Description

FLEXIBLE, INTEGRATED MARKETING AND DATA TECHNOLOGY STACK ACCESSIBLE THROUGH A SINGLE-LINE CODE IMPLEMENTATIONBACKGROUND

[0001] Online data, marketing and analytics has rapidly changed in the last 20 years. The category has exploded with new vendors, tools, legislation, and regulations. Additionally, operating systems and web browsers continually change how data is stored and accessed. Main tools have become extremely important, complex, and fragile. Accessing valuable / insightful data is often likened to a needle in a haystack. Managing the main tools and using the data requires significant expenses, personnel, and additional tools to continue to make use of the main tools.SUMMARY

[0002] The present disclosure describes a flexible, integrated marketing and data technology stack accessible through a single-line code implementation.

[0003] In an implementation, a computer-implemented method, comprising: loading, using a browser, a webpage containing a unified (UNI) tag; sending, using a CLOUDFLARE (CF) tag worker that evaluates a host / request from the browser, a partner configuration to the browser to dynamically load a partner-configured client-side scripts; generating, using the browser, a call to an event CF worker; sending, by the CF worker, data about an event to an event endpoint; providing, by the event endpoint, a hypertext transfer protocol (HTTP) endpoint for the CF event worker to post to; and forwarding, by a validate worker, event data to a bucket publish worker or an enrichment worker.

[0004] The described subject matter can be implemented using a computer- implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer-implemented system comprising one or more computer memory devices interoperably coupled with one or more computers and having tangible, non-transitory, machine-readable media storing instructions that, when executed by the one or more computers, perform the computer- implemented method / the computer-readable instructions stored on the non-transitory, computer-readable medium.

[0005] The subject matter described in this specification can be implemented to realize, as further described herein, one or more advantages.

[0006] The details of one or more implementations of the subject matter of this specification are set forth in the Detailed Description, the Claims, and the accompanying drawings. Other features, aspects, and advantages of the subject matter will become apparent to those of ordinary skill in the art from the Detailed Description, the Claims, and the accompanying drawings.DESCRIPTION OF DRAWINGS

[0007] FIGS. 1A-1B describe a block diagram, which illustrates an example of a flexible, integrated marketing and data technology stack accessible through a single-line code implementation, according to an implementation of the present disclosure.

[0008] FIGS. 2A-2B describe a block diagram, which illustrates an alternative example of a flexible, integrated marketing and data technology stack accessible through a single-line code implementation as described in FIGS. 1A-1B, according to an implementation of the present disclosure.

[0009] FIG. 3 is a flowchart illustrating an example of a computer-implemented method for providing a flexible, integrated marketing and data technology stack accessible through a single-line code implementation, according to an implementation of the present disclosure.

[0010] FIG. 4 is a block diagram illustrating an example of a computer-implemented system used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures, according to an implementation of the present disclosure.

[0011] Like reference numbers and designations in the various drawings indicate like elements.DETAILED DESCRIPTION

[0012] The following detailed description describes a flexible, integrated marketing and data technology stack accessible through a single-line code implementation and is presented to enable any person skilled in the art to make and use the disclosed subject matter in the context of one or more particular implementations. Various modifications, alterations, and permutations of the disclosed implementations can be made and will be readily apparent to those of ordinary skill in the art, and the general principles defined can be applied to other implementations and applications, without departing from the scope of the present disclosure. In some instances, one or more technical details that are unnecessary to obtain an understanding of the described subject matter and that are within the skill of one of ordinary skill in the art may be omitted so as to not obscure one or more described implementations. The present disclosure is not intended to be limited to the described or illustrated implementations, but to be accorded the widest scope consistent with the described principles and features.

[0013] Online data, marketing and analytics has rapidly changed in the last 20 years. The category has exploded with new vendors, tools, legislation, and regulations. Additionally, operating systems and web browsers continually change how data is stored and accessed. Main tools have become extremely important, complex, and fragile. The complexity, resource requirements, and technical knowledge required to build a modem in-house marketing and data technology stack makes accessing valuable / insightful data extremely difficult, in that it has become increasingly difficult to identify and attribute potential customers for marketing. A lack of a simple-to-use, all-in-one technology platform means that managing the main tools and using the data requires significant expertise, expenses, personnel, and additional tools.

[0014] Unlike most marketing technology platforms, the flexible technical architecture of the described approach permits organizations at any level of complexity in marketing technology and data technology to only add a single line of code (e.g., JAVASCRIPT) to a website to access all functionality of the described approach.

[0015] One platform permits seamlessly integrating and handling tagging and tracking, identification, audience targeting, model creation, and data pipelining needs of an organization. As identity resolution is becoming increasingly complex due to changes in cookie persistence, the described approach of a many-to-many identity resolution model allows multi-level matching where multiple different keys are used. While typically identity resolution is one-to- many, the described approach is one-to-many-to-many-to-one. This can be rerun at anymoment when a new identifier is introduced or a new match identified on previously captured data.

[0016] The approach is operationally efficient and scalable, which combines a multi - instance design with single tenant data and governance. For example, base code can be universally applied to all clients, all identifiers, attributes, rules, and models can be customized for each client using a templating engine, data is single tenant, and code that is provided to a browser is mainly for the purpose of tracking events with other code modified remotely and reducing a file size and amount of resources required by the browser.

[0017] The described approach can provide identity resolution. For example, and in some implementations, a method is provided for setting and persisting unique identifiers, which can be remotely updated as necessary due to regulatory and industry changes and without requiring a client to make code updates. Identifiers are used in a deterministic many-to-many identity model that resolves browser, user-provided, client-provided, and other identifications (IDs) into a single user. A secondary probabilistic identity graph is generated separate to a primary, deterministic graph for identifying potential customer matches. Models are used in conjunction with measurement and retargeting models.

[0018] The approach is also privacy native. Based on browser signals and custom rules, code provided to a browser and downstream data collection automatically adjusts. This functionality occurs immediately and without any direct interaction by a user and can be adjusted throughout a visit duration. In some implementations, types of settings can include: 1) Full: No limitations; 2) Know your Customer: Only collects user IDs; 3) Anonymous: Collects limited generic attributes ignoring things like timestamps, identifiable and pseudo anonymous data points; None: All data is discarded; or 4) Custom. In some implementations, unless a customization is requested by a client, email and phone numbers are shared with the system using various normalization methods and a hash (e.g., a SHA256 or other hash). If a 3rd-party requires plain-text values (e.g., a customer relationship management (CRM) system), the 3rd-party’s code can be temporarily loaded into a browser by the approach’s platform. Once necessary personal identifiable information (PII) has been shared, a userID (UID) can be used to communicate between the approach’s platform and a vendor (if supported).

[0019] Tag monitoring functionality can also be provided. For example, a method is made available for monitoring marketing code (e.g., JavaScript) tags that are present on client’s website, automatically alerting when tags are missing, and synthetically triggering / loading missing tags remotely so that the client’s data is complete.

[0020] The described approach also provides user enrichment functionality. An example includes a non-blocking and asynchronous method for remotely requesting additional information on a user from internal and external sources. Information can be sent back to a user’s device (e.g., a desktop or laptop computer, tablet computer, or mobile computing device) for collection by client tools or stored in a database (e.g., a client-side database).

[0021] No other current technical solution provides privacy customization features or the required simplicity for implementation, flexibility, and adaptability of the described approach. Implementation of products in a same category typically requires multiple months, multiple vendors, and teams with many years of experience. The described approach is easier to integrate and removes a requirement of multiple engineering teams over a course of multiple years to fully build out an in-house solution. Any current solution that can parallel functionality of the described approach need to have at least multiple (usually 3+) 3rd-party vendors and additional resources to accommodate for building out internal tooling and continued maintenance (e.g., multiple platforms and additional internal components to be built (i.e., requires a tag manager + customer data platform (CDP) + audience modeling environment + data warehousing infrastructure + 3rd-party audience and data provider)). The described approach also provides a unified view of customers and data across both marketing and product data sets.

[0022] Also provided are improvements in computer processing and performance (e.g., reductions in overall computational time and / or resources required to perform a task, increased processing power or storage capacity);reduces time and computational resources to complete a transaction; increases data security; automatically updates user interfaces based on dynamic information; improves network / system monitoring, cryptography or security benefits; and automatically transforms data from one format to another.

[0023] The approach is meant to replace data and modeling technology stacks across all industries that interface in a digital space and spans multiple disciplines, including marketing, product, business operations, and analytics. Example applications that the approach may replace or augment can include: tag manager, customer data platform, business intelligence tooling, audience data platforms, data integration platforms, modeling and data science platforms, data management platforms, and mobile and web analytics platforms. A digital based organization should be able to utilize the proposed platform as a single source of truth for data and be able to run all marketing operations, analytics, and modeling completely within the proposed platform.

[0024] FIGS. 1A-1B describe a block diagram as lOOa-lOOb, respectfully, which illustrates an example of a flexible, integrated marketing and data technology stack accessible through a single-line code implementation and an associated process 101, according to an implementation of the present disclosure. Legend 102 provides a key to various technological aspects and a data / communi cation flow of FIGS. 1A-1B.

[0025] A Browser 104 triggers an event and makes a call to an event worker of a cloudbased serverless platform providing networking, security, and developer services (e.g., a CLOUDFLARE (CF) Event Worker of a CF cloud-based serverless platform). The CF Event Worker 106 generates data about an event and sends the data to an Event Endpoint 108. Based on a response, it may set data for enrichment and will set cookies and dispatch events.

[0026] The Browser 104 also loads a page that has a unified (UNI) tag. “UNI” or “unified” is used in the context of one / a single line of code. A CF Tag Worker 110 (or other type of Tag Worker) evaluates a host / request and sends a configuration to dynamically load a partner’s configured client-side scripts (e.g., events or auto-tracking).

[0027] With respect to a client / partner configurations associated with the CF Tag Worker 110: refer to APPENDIX - Exhibit A (results) & Exhibit B (code).• Keys that govern how the platform operates, data is collected, are enriched by external sources, and analyzed.• Single-tenant, multi-instance: These configurations allow multiple clients to set up in hours instead of weeks. The application code is universal, but automatically tuned to a client and each browser.• The instructions include a set of default values that can be merged with custom values.• These instructions act as a fill-in-the-blank and eliminate the need for customization.• To prevent unauthorized usage and tracking: If the client’s tag is loaded from an unauthorized website, an error is returned and all tracking is prevented. This can be disabled in the configuration. In other words, a partner / client configuration can be setup in such a way that only allows the tag to be loaded from pre-defined domains. If the tag is loaded from elsewhere, the server responses with an error message.• The configurations can be re-evaluated on each request, event, visit, or session.• Each configuration has a unique key that is added to every event for version control, change management and auditing. This provides the exact settings that were applied when the event was created ("hash": "edla6ec7789e82e76fd0f3421d9536e2422f0a85").

[0028] This aspect of the described approach is important because other conventional tools rely on custom code to achieve this level of customization and has removed this technical barrier by making everything a configuration native to the platform. This increases performance and reliability.

[0029] The Event Endpoint 108 provides a hypertext transfer protocol (HTTP) for the CF Event Worker 106 to post to, and if enrichment exists for a UID / hostname it will return that data to be passed to a user’s Browser 104.

[0030] With respect to privacy nativeness (CF Tag Worker 108 > CF Event Worker 106 > Event Endpoint 110): refer to APPENDIX - Exhibit A - “privacy”: [{ }]• Allows a customer to collect data in accordance with privacy laws and industry regulations. Default rules are available and can be configured by the client. There is effectively no limit to what data points can be used, but examples include: consent management cookies, do not track application programming interfaces (APIs), and location.• Know Your Customer: a setting where only identity attributes are collected for operations such as the prevention of fraud.• Anonymous: a setting where only aggregated attributes are collected. The approach has an ability to see generic ways traffic generally arrives at a site providing marketers with non-zero insights. Identifiable and pseudo- anonymous attributes are automatically removed (such as, timestamps are truncated to date, internet protocol (IP) address is completely removed, only the hostname (e.g., anexamplehostname.com) is collected instead of a full URL (e.g„ anexamplehostname.com / quote).• Do not track: All data is deleted and nothing is stored.• Full: All tracking in place.

[0031] This aspect of the described approach is important because customers are allowed to still run their business while collecting a minimum amount of allowable data. The Anonymous setting still provides a basic understanding of avenues users use to go to a website, but there is no way to tie it back to a single user.

[0032] With respect to the single line of code implementation (CF Tag Worker 110 >CF Event Worker 106 > Event Endpoint 108): example - “https: / / uni- dev.anexamplehostname.com / uni / vl / tag.js.”• To implement, a client only needs to add a single line of code to their website. All of the configurations and tracking is handled by a server / cloud processor. Any changes or new features are made in the server / cloud environment.• This single line of code allows for privacy controls, automated event, and identity tracking.• NOTE: This does not include setting up a domain for hosting a tag and does not require updates to a website’s code.

[0033] This aspect of the described approach is important because adding code takes a very short period of time (e.g., less than 5 minutes), to implement a similarly capable platform usually takes considerably longer (e.g., no less than 6 months).

[0034] With respect to tag monitoring (CF Tag Worker 110):• Process that determines if tags, JavaScript, pixels, etc. were present on a customer's webpage and if they were successful or unsuccessful. When critical tags are missing, notifications are automatically sent from an online system to users (email, slack, etc.) and other online systems so that the issue can be resolved.• This is different from “monkey patching” because existing browser APIs are not modified, which can lead to errors. The described system creates a string with results for each tracked vendor. The configurations define what needs to be monitored and the result is sent from the user device to the described cloud service on every event.

[0035] This aspect of the described approach is important because changes occur frequently by engineering teams and web browsers that break standard tracking tools. These outages are only noticed a few days later or during manual testing. This system makes the process automatic and real-time.

[0036] A Validate worker 112 looks at event data and ensures the data is valid and forwards the data to a Bucket Publish worker 114 or Enrichment worker 116. The Enrichment worker 116 will receive events. Based on a partner’s configuration, the Enrichment worker 116 will send event to zero-to-many asynchronous Enrichment Processes 118.

[0037] The Enrichment Processes 118 are asynchronous services that receive events from the Enrichment worker 116. Once (and if) they have data to return, they will call an Enrichment Endpoint 120.

[0038] The Enrichment Endpoint 120 will receive results from the Enrichment Process(es) 118. Based on a type and client configuration, the Enrichment Endpoint 120 will either update a state in a database 122 (e.g., REDIS - a source-available, in-memory storage, distributed, in-memory key -value database, cache, and message broker) to call back to a user’s browser or to make a call to a partner’s API 124.

[0039] With respect to enrichments (Validate 112 > Enrichment 116 > Enrichment Process 118> Enrichment Endpoint 120... .):• Process for which data is collected according to criteria. The data is stored in the browser or on the server. Once all of the criteria are met, data from multiple events is compiled into a single event and sent to a 3rd-party or another service (Enrichment Process). This process sends back additional data not part of the initial event.• The result is shared multiple ways according to the configuration: directly to a client service or back to the browser. The customer’s web property can be alerted that a new data point is available for further action.

[0040] This aspect of the described approach is important because the feature is available as part of a single line of code implementation and makes data available to a client in ways that require little engineering resources.

[0041] The Bucket Publish worker 114 sends an event to a pub / sub (asynchronous and scalable messaging service that decouples services producing messages from services processing those messages. Low latency (e.g., 100ms) for services to communicate asynchronously) that a bucket is subscribing in order to write event data into a bucket (e.g., a GOOGLE CLOUD SERVICES Bucket 126). The GCS Bucket 126 is a data lake of events (e.g., in AVRO files that include markers that can be used to split large data sets into subsets suitable for APACHE MAPREDUCE processing).

[0042] Referring to FIG. IB, legend 102 terms mean: “DS / DE” - Data Science / Data Engineering, which - relates to building of models to enrich event / customer data in real time. “MT / BA” - Marketing Technology / Business Analytics - relates to building the analytical models to be shared with the client. “DE / MT” - Data Engineering / Marketing Technology - relates to sending data to the client to store / analyze.

[0043] As files are added to the GCS Bucket 126, a publisher (e.g., GOOGLE BIG QUERY (BQ) PUBLISHER worker 128 is triggered to publish data to a data store (e.g., GOOGLE BIG QUERY 130 using pub / sub. GOOGLE BIG QUERY is a serverless, petabyte scale data store for analytics.

[0044] A Config Endpoint 132 is called by a continuous delivery platform (e.g., CIRCLECI) on deployment to update configuration in BQ 130.

[0045] Business Analytics / Reporting 134 includes, for example, data processing, such as bot flagging, identity stitching, and conversions. For an initial launch, there can be baseline Tableau Reports sent using email and push metrics.

[0046] Data feed 136 sends data to a customer.

[0047] Miscellaneous aspects of the described approach include:• Attribution native (CF Tag Worker 110 > CF Event Worker 106): When a user visits a website, a server processes query parameters, browser headers, and adds unique values to a string. The string automatically renews with each visit and is part of the configurations with different results based on privacy. The string provides a single value that is used for understanding the first visit of a user, the last visit, and all visits in between. This aspect of the described approach is important because normally this data is spread over multiple rows of data and not in a single place. It is created in a way that allows for compliance with the ANONYMOUS privacy setting (i.e., no timestamp and minimal granularity).• Identity resolution & matrix (Browser 104 > CF Tag Worker 110 > CF Event Worker 106): A method for storing and persisting identifiers in the browser that does not rely on device fingerprinting and in accordance with privacy configurations. The matrix creates a many to many relationship where most identity graphs focus on one to many. Upon the Browser 104 making a request to the server, the server checks for the presence of user identifiers. If the request does not include any of the necessary identifiers, the server assigns a backup identifier. When the browser receives the response from the server with the backup identifier, it checks additional locations where the identifier is stored that are not accessible to the server. If an alternative location contains the identifier, the application sets that value for the server to use in the future. If an alternative location does not contain the identifier, it uses the backup identifiersetting the value for the server to use and setting it in the non-server accessible places.

[0048] In some implementations, the described approach can be expanded to work with “agent” devices. As an agent fills out a form on behalf of a customer, the approach collects data. An element (e.g., a button or widget) on an agent GUI screen can allow the agent to automatically request additional data on an application from modeling / enrichment services. This aspect provides a fast way for an agent to access new data sources without much engineering.

[0049] FIGS. 2A-2B describe a block diagram as 200a-200b, respectfully, which illustrates an alternative example of a flexible, integrated marketing and data technology stack accessible through a single-line code implementation as described in FIGS. 1A-1B and an associated process 201, according to an implementation of the present disclosure. Legend 202 provides a key to various technological aspects and a data / communi cation flow of FIGS. 2A- 2B.

[0050] FIG. 3 is a flowchart 300 illustrating an example of a computer-implemented method for providing a flexible, integrated marketing and data technology stack accessible through a single-line code implementation, according to an implementation of the present disclosure. For clarity of presentation, the description that follows generally describes method 300 in the context of the other figures in this description. However, it will be understood that method 300 can be performed, for example, by any system, environment, software, and hardware, or a combination of systems, environments, software, and hardware, as appropriate. In some implementations, various steps of method 300 can be run in parallel, in combination, in loops, or in any order.

[0051] At 302, using a browser, a webpage containing a unified (UNI) tag is loaded. From 302, method 300 proceeds to 304.

[0052] At 304, using a CLOUDFLARE (CF) tag worker that evaluates a host / request from the browser, sending a partner configuration to the browser to dynamically load a partner- configured client-side scripts. From 304, method 300 proceeds to 306.

[0053] At 306, using the browser, generating a call to an event CF worker. From 306, method 300 proceeds to 308.

[0054] At 308, the CF worker sends data about an event to an event endpoint. In some implementations, the CF worker generates the data about an event and based on a response from the event endpoint, the CF worker sets data for enrichment. If enrichment exists for a(UID) / hostname, the event endpoint returns enrichment data to the browser. From 308, method 300 proceeds to 310.

[0055] At 310, the event endpoint provides a hypertext transfer protocol (HTTP) endpoint for the CF event worker to post to. From 310, method 300 proceeds to 312.

[0056] At 312, a validate worker forwards event data to a bucket publish worker or an enrichment worker. In the case that the event data is received by the enrichment worker, based on the partner configuration, sending, by the enrichment worker, the event data to zero-to-many asynchronous enrichment processes. An enrichment process receives the event data from the enrichment worker. The enrichment process calls an enrichment endpoint with enriched data based on the event data. The enriched data is received from the enrichment process. Based on a type of the enriched data and a client configuration, either: 1) the enrichment endpoint updates a state in an enrichment data database or 2) the enrichment endpoint calls a partner application programming interface.

[0057] In the case that the event data is forwarded to the bucket publish worker, the bucket publish worker sends the event data to a pub / sub for storage in a data lake of events. After 312, method 300 can stop.

[0058] FIG. 4 is a block diagram illustrating an example of a computer-implemented System 400 used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures, according to an implementation of the present disclosure. In the illustrated implementation, computer- implemented system 400 includes a Computer 402 and a Network 430.

[0059] The illustrated Computer 402 is intended to encompass any computing device, such as a server, desktop computer, laptop / notebook computer, wireless data port, smart phone, personal data assistant (PDA), tablet computer, one or more processors within these devices, or a combination of computing devices, including physical or virtual instances of the computing device, or a combination of physical or virtual instances of the computing device. Additionally, the Computer 402 can include an input device, such as a keypad, keyboard, or touch screen, or a combination of input devices that can accept user information, and an output device that conveys information associated with the operation of the Computer 402, including digital data, visual, audio, another type of information, or a combination of types of information, on a graphical-type user interface (UI) (or GUI) or other UI.

[0060] The Computer 402 can serve in a role in a distributed computing system as, for example, a client, network component, a server, or a database or another persistency, or acombination of roles for performing the subject matter described in the present disclosure. The illustrated Computer 402 is communicably coupled with a Network 430. In some implementations, one or more components of the Computer 402 can be configured to operate within an environment, or a combination of environments, including cloud-computing, local, or global.

[0061] At a high level, the Computer 402 is an electronic computing device operable to receive, transmit, process, store, or manage data and information associated with the described subject matter. According to some implementations, the Computer 402 can also include or be communicably coupled with a server, such as an application server, e-mail server, web server, caching server, or streaming data server, or a combination of servers.

[0062] The Computer 402 can receive requests over Network 430 (for example, from a client software application executing on another Computer 402) and respond to the received requests by processing the received requests using a software application or a combination of software applications. In addition, requests can also be sent to the Computer 402 from internal users (for example, from a command console or by another internal access method), external or third-parties, or other entities, individuals, systems, or computers.

[0063] Each of the components of the Computer 402 can communicate using a System Bus 403. In some implementations, any or all of the components of the Computer 402, including hardware, software, or a combination of hardware and software, can interface over the System Bus 403 using an application programming interface (API) 412, a Service Layer 413, or a combination of the API 412 and Service Layer 413. The API 412 can include specifications for routines, data structures, and object classes. The API 412 can be either computer-language independent or dependent and refer to a complete interface, a single function, or even a set of APIs. The Service Layer 413 provides software services to the Computer 402 or other components (whether illustrated or not) that are communicably coupled to the Computer 402. The functionality of the Computer 402 can be accessible for all service consumers using the Service Layer 413. Software services, such as those provided by the Service Layer 413, provide reusable, defined functionalities through a defined interface. For example, the interface can be software written in a computing language (for example JAVA or C++) or a combination of computing languages, and providing data in a particular format (for example, extensible markup language (XML)) or a combination of formats. While illustrated as an integrated component of the Computer 402, alternative implementations can illustrate the API 412 or the Service Layer 413 as stand-alone components in relation to other componentsof the Computer 402 or other components (whether illustrated or not) that are communicably coupled to the Computer 402. Moreover, any or all parts of the API 412 or the Service Layer 413 can be implemented as a child or a sub-module of another software module, enterprise application, or hardware module without departing from the scope of the present disclosure.

[0064] The Computer 402 includes an Interface 404. Although illustrated as a single Interface 404, two or more Interfaces 404 can be used according to particular needs, desires, or particular implementations of the Computer 402. The Interface 404 is used by the Computer 402 for communicating with another computing system (whether illustrated or not) that is communicatively linked to the Network 430 in a distributed environment. Generally, the Interface 404 is operable to communicate with the Network 430 and includes logic encoded in software, hardware, or a combination of software and hardware. More specifically, the Interface 404 can include software supporting one or more communication protocols associated with communications such that the Network 430 or hardware of Interface 404 is operable to communicate physical signals within and outside of the illustrated Computer 402.

[0065] The Computer 402 includes a Processor 405. Although illustrated as a single Processor 405, two or more Processors 405 can be used according to particular needs, desires, or particular implementations of the Computer 402. Generally, the Processor 405 executes instructions and manipulates data to perform the operations of the Computer 402 and any algorithms, methods, functions, processes, flows, and procedures as described in the present disclosure.

[0066] The Computer 402 also includes a Database 406 that can hold data for the Computer 402, another component communicatively linked to the Network 430 (whether illustrated or not), or a combination of the Computer 402 and another component. For example, Database 406 can be an in-memory or conventional database storing data consistent with the present disclosure. In some implementations, Database 406 can be a combination of two or more different database types (for example, a hybrid in-memory and conventional database) according to particular needs, desires, or particular implementations of the Computer 402 and the described functionality. Although illustrated as a single Database 406, two or more databases of similar or differing types can be used according to particular needs, desires, or particular implementations of the Computer 402 and the described functionality. While Database 406 is illustrated as an integral component of the Computer 402, in alternative implementations, Database 406 can be external to the Computer 402. The Database 406 can hold and operate on at least any data type mentioned or any data type consistent with thisdisclosure.

[0067] The Computer 402 also includes a Memory 407 that can hold data for the Computer 402, another component or components communicatively linked to the Network 430 (whether illustrated or not), or a combination of the Computer 402 and another component. Memory 407 can store any data consistent with the present disclosure. In some implementations, Memory 407 can be a combination of two or more different types of memory (for example, a combination of semiconductor and magnetic storage) according to particular needs, desires, or particular implementations of the Computer 402 and the described functionality. Although illustrated as a single Memory 407, two or more Memories 407 or similar or differing types can be used according to particular needs, desires, or particular implementations of the Computer 402 and the described functionality. While Memory 407 is illustrated as an integral component of the Computer 402, in alternative implementations, Memory 407 can be external to the Computer 402.

[0068] The Application 408 is an algorithmic software engine providing functionality according to particular needs, desires, or particular implementations of the Computer 402, particularly with respect to functionality described in the present disclosure. For example, Application 408 can serve as one or more components, modules, or applications. Further, although illustrated as a single Application 408, the Application 408 can be implemented as multiple Applications 408 on the Computer 402. In addition, although illustrated as integral to the Computer 402, in alternative implementations, the Application 408 can be external to the Computer 402.

[0069] The Computer 402 can also include a Power Supply 414. The Power Supply 414 can include a rechargeable or non-rechargeable battery that can be configured to be either user- or non-user-replaceable. In some implementations, the Power Supply 414 can include powerconversion or management circuits (including recharging, standby, or another power management functionality). In some implementations, the Power Supply 414 can include a power plug to allow the Computer 402 to be plugged into a wall socket or another power source to, for example, power the Computer 402 or recharge a rechargeable battery.

[0070] There can be any number of Computers 402 associated with, or external to, a computer system containing Computer 402, each Computer 402 communicating over Network 430. Further, the term “client,” “user,” or other appropriate terminology can be used interchangeably, as appropriate, without departing from the scope of the present disclosure.Moreover, the present disclosure contemplates that many users can use one Computer 402, or that one user can use multiple computers 402.

[0071] Described implementations of the subject matter can include one or more features, alone or in combination.

[0072] For example, in a first implementation, a computer-implemented method, comprising: loading, using a browser, a webpage containing a unified (UNI) tag; sending, using a tag worker of a cloud-based serverless platform that evaluates a host / request from the browser, a partner configuration to the browser to dynamically load partner-configured clientside scripts, wherein the partner-configured client-side scripts permit automatic modification of data collection to anonymize users, prevent data from collection, or to collect user identifiers; generating, using the browser, a call to an event worker of the cloud-based serverless platform; sending, by the event worker, data about an event to an event endpoint; providing, by the event endpoint, a hypertext transfer protocol (HTTP) endpoint for the event worker to post to; and forwarding, by a validate worker, event data to a bucket publish worker or an enrichment worker.

[0073] The foregoing and other described implementations can each, optionally, include one or more of the following features:

[0074] A first feature, combinable with any of the following features, comprising: generating, by the event worker, the data about an event; and based on a response from the event endpoint, setting, by the event worker, data for enrichment.

[0075] A second feature, combinable with any of the previous or following features, comprising: if enrichment exists for a userid (UID) / hostname, returning, by the event endpoint, enrichment data to the browser.

[0076] A third feature, combinable with any of the previous or following features, comprising: receiving, by the enrichment worker, the event data; and based on the partner configuration, sending, by the enrichment worker, the event data to zero-to-many asynchronous enrichment processes.

[0077] A fourth feature, combinable with any of the previous or following features, comprising: receiving, by an enrichment process, the event data from the enrichment worker; and calling, by the enrichment process, an enrichment endpoint with enriched data based on the event data.

[0078] A fifth feature, combinable with any of the previous or following features, comprising: receiving, from the enrichment process, the enriched data; and based on a type ofthe enriched data and a client configuration, either: 1) updating, by the enrichment endpoint, a state in an enrichment data database; or 2) calling, by the enrichment endpoint, a partner application programming interface.

[0079] A sixth feature, combinable with any of the previous or following features, comprising: sending, by the bucket publish worker, the event data to a pub / sub for storage in a data lake of events.

[0080] In a second implementation, a non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform one or more operations, comprising: loading, using a browser, a webpage containing a unified (UNI) tag; sending, using a tag worker of a cloud-based serverless platform that evaluates a host / request from the browser, a partner configuration to the browser to dynamically load partner- configured client-side scripts, wherein the partner-configured client-side scripts permit automatic modification of data collection to anonymize users, prevent data from collection, or to collect user identifiers; generating, using the browser, a call to an event worker of the cloudbased serverless platform; sending, by the event worker, data about an event to an event endpoint; providing, by the event endpoint, a hypertext transfer protocol (HTTP) endpoint for the event worker to post to; and forwarding, by a validate worker, event data to a bucket publish worker or an enrichment worker.

[0081] The foregoing and other described implementations can each, optionally, include one or more of the following features:

[0082] A first feature, combinable with any of the following features, comprising: generating, by the event worker, the data about an event; and based on a response from the event endpoint, setting, by the event worker, data for enrichment.

[0083] A second feature, combinable with any of the previous or following features, comprising: if enrichment exists for a userid (UID) / hostname, returning, by the event endpoint, enrichment data to the browser.

[0084] A third feature, combinable with any of the previous or following features, comprising: receiving, by the enrichment worker, the event data; and based on the partner configuration, sending, by the enrichment worker, the event data to zero-to-many asynchronous enrichment processes.

[0085] A fourth feature, combinable with any of the previous or following features, comprising: receiving, by an enrichment process, the event data from the enrichment worker;and calling, by the enrichment process, an enrichment endpoint with enriched data based on the event data.

[0086] A fifth feature, combinable with any of the previous or following features, comprising: receiving, from the enrichment process, the enriched data; and based on a type of the enriched data and a client configuration, either: 1) updating, by the enrichment endpoint, a state in an enrichment data database; or 2) calling, by the enrichment endpoint, a partner application programming interface.

[0087] A sixth feature, combinable with any of the previous or following features, comprising: sending, by the bucket publish worker, the event data to a pub / sub for storage in a data lake of events.

[0088] In a third implementation, a computer-implemented system, comprising: one or more computers; and one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations, comprising: loading, using a browser, a webpage containing a unified (UNI) tag; sending, using a tag worker of a cloud-based serverless platform that evaluates a host / request from the browser, a partner configuration to the browser to dynamically load partner-configured client-side scripts, wherein the partner-configured client-side scripts permit automatic modification of data collection to anonymize users, prevent data from collection, or to collect user identifiers; generating, using the browser, a call to an event worker of the cloudbased serverless platform; sending, by the event worker, data about an event to an event endpoint; providing, by the event endpoint, a hypertext transfer protocol (HTTP) endpoint for the event worker to post to; and forwarding, by a validate worker, event data to a bucket publish worker or an enrichment worker.

[0089] The foregoing and other described implementations can each, optionally, include one or more of the following features:

[0090] A first feature, combinable with any of the following features, comprising: generating, by the event worker, the data about an event; and based on a response from the event endpoint, setting, by the event worker, data for enrichment.

[0091] A second feature, combinable with any of the previous or following features, comprising: if enrichment exists for a userid (UID) / hostname, returning, by the event endpoint, enrichment data to the browser.

[0092] A third feature, combinable with any of the previous or following features, comprising: receiving, by the enrichment worker, the event data; and based on the partner configuration, sending, by the enrichment worker, the event data to zero-to-many asynchronous enrichment processes.

[0093] A fourth feature, combinable with any of the previous or following features, comprising: receiving, by an enrichment process, the event data from the enrichment worker; and calling, by the enrichment process, an enrichment endpoint with enriched data based on the event data.

[0094] A fifth feature, combinable with any of the previous or following features, comprising: receiving, from the enrichment process, the enriched data; and based on a type of the enriched data and a client configuration, either: 1) updating, by the enrichment endpoint, a state in an enrichment data database; or 2) calling, by the enrichment endpoint, a partner application programming interface.

[0095] A sixth feature, combinable with any of the previous or following features, comprising: sending, by the bucket publish worker, the event data to a pub / sub for storage in a data lake of events.

[0096] Implementations of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, in tangibly embodied computer software or firmware, in computer hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Software implementations of the described subject matter can be implemented as one or more computer programs, that is, one or more modules of computer program instructions encoded on a tangible, non-transitory, computer-readable medium for execution by, or to control the operation of, a computer or computer-implemented system. Alternatively, or additionally, the program instructions can be encoded in / on an artificially generated propagated signal, for example, a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to a receiver apparatus for execution by a computer or computer-implemented system. The computer- storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of computer-storage mediums. Configuring one or more computers means that the one or more computers have installed hardware, firmware, or software (or combinations of hardware, firmware, and software) so that when the software is executed by the one or more computers, particular computing operations are performed. The computerstorage medium is not, however, a propagated signal.

[0097] The term “real-time,” “real time,” “realtime,” “real (fast) time (RFT),” “near(ly) real-time (NRT),” “quasi real-time,” or similar terms (as understood by one of ordinary skill in the art), means that an action and a response are temporally proximate such that an individual perceives the action and the response occurring substantially simultaneously. For example, the time difference for a response to display (or for an initiation of a display) of data following the individual’s action to access the data can be less than 1 millisecond (ms), less than 1 second (s), or less than 5 s. While the requested data need not be displayed (or initiated for display) instantaneously, it is displayed (or initiated for display) without any intentional delay, taking into account processing limitations of a described computing system and time required to, for example, gather, accurately measure, analyze, process, store, or transmit the data.

[0098] The terms “data processing apparatus,” “computer,” “computing device,” or “electronic computer device” (or an equivalent term as understood by one of ordinary skill in the art) refer to data processing hardware and encompass all kinds of apparatuses, devices, and machines for processing data, including by way of example, a programmable processor, a computer, or multiple processors or computers. The computer can also be, or further include special-purpose logic circuitry, for example, a central processing unit (CPU), a field- programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). In some implementations, the computer or computer-implemented system or special-purpose logic circuitry (or a combination of the computer or computer-implemented system and specialpurpose logic circuitry) can be hardware- or software-based (or a combination of both hardware- and software-based). The computer can optionally include code that creates an execution environment for computer programs, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplates the use of a computer or computer-implemented system with an operating system, for example LINUX, UNIX, WINDOWS, MAC OS, ANDROID, or IOS, or a combination of operating systems.

[0099] A computer program, which can also be referred to or described as a program, software, a software application, a unit, a module, a software module, a script, code, or other component can be written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages, and it can be deployed in any form, including, for example, as a stand-alone program, module, component, or subroutine, for use in a computing environment. A computer program can, but need not, correspond to a filein a file system. A program can be stored in a portion of a file that holds other programs or data, for example, one or more scripts stored in a markup language document, in a single file dedicated to the program in question, or in multiple coordinated files, for example, files that store one or more modules, sub-programs, or portions of code. A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

[0100] While portions of the programs illustrated in the various figures can be illustrated as individual components, such as units or modules, that implement described features and functionality using various objects, methods, or other processes, the programs can instead include a number of sub-units, sub-modules, third-party services, components, libraries, and other components, as appropriate. Conversely, the features and functionality of various components can be combined into single components, as appropriate. Thresholds used to make computational determinations can be statically, dynamically, or both statically and dynamically determined.

[0101] Described methods, processes, or logic flows represent one or more examples of functionality consistent with the present disclosure and are not intended to limit the disclosure to the described or illustrated implementations, but to be accorded the widest scope consistent with described principles and features. The described methods, processes, or logic flows can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output data. The methods, processes, or logic flows can also be performed by, and computers can also be implemented as, special-purpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.

[0102] Computers for the execution of a computer program can be based on general or special-purpose microprocessors, both, or another type of CPU. Generally, a CPU will receive instructions and data from and write to a memory. The essential elements of a computer are a CPU, for performing or executing instructions, and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to, receive data from or transfer data to, or both, one or more mass storage devices for storing data, for example, magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, for example, a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable memory storage device, for example, a universal serial bus (USB) flash drive, to name just a few.

[0103] Non-transitory computer-readable media for storing computer program instructions and data can include all forms of permanent / non-permanent or volatile / non- volatile memory, media and memory devices, including by way of example semiconductor memory devices, for example, random access memory (RAM), read-only memory (ROM), phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices; magnetic devices, for example, tape, cartridges, cassettes, internal / removable disks; magneto-optical disks; and optical memory devices, for example, digital versatile / video disc (DVD), compact disc (CD)-ROM, DVD+ / -R, DVD-RAM, DVD-ROM, high-definition / density (HD)-DVD, and BLU-RAY / BLU-RAY DISC (BD), and other optical memory technologies. The memory can store various objects or data, including caches, classes, frameworks, applications, modules, backup data, jobs, web pages, web page templates, data structures, database tables, repositories storing dynamic information, or other appropriate information including any parameters, variables, algorithms, instructions, rules, constraints, or references. Additionally, the memory can include other appropriate data, such as logs, policies, security or access data, or reporting files. The processor and the memory can be supplemented by, or incorporated in, specialpurpose logic circuitry.

[0104] To provide for interaction with a user, implementations of the subject matter described in this specification can be implemented on a computer having a display device, for example, a cathode ray tube (CRT), liquid crystal display (LCD), light emitting diode (LED), or plasma monitor, for displaying information to the user and a keyboard and a pointing device, for example, a mouse, trackball, or trackpad by which the user can provide input to the computer. Input can also be provided to the computer using a touchscreen, such as a tablet computer surface with pressure sensitivity or a multi-touch screen using capacitive or electric sensing. Other types of devices can be used to interact with the user. For example, feedback provided to the user can be any form of sensory feedback (such as, visual, auditory, tactile, or a combination of feedback types). Input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with the user by sending documents to and receiving documents from a client computing device that is used by the user (for example, by sending web pages to a web browser on a user’s mobile computing device in response to requests received from the web browser).

[0105] The term “graphical user interface (GUI) can be used in the singular or the pluralto describe one or more graphical user interfaces and each of the displays of a particular graphical user interface. Therefore, a GUI can represent any graphical user interface, including but not limited to, a web browser, a touch screen, or a command line interface (CLI) that processes information and efficiently presents the information results to the user. In general, a GUI can include a number of user interface (UI) elements, some or all associated with a web browser, such as interactive fields, pull-down lists, and buttons. These and other UI elements can be related to or represent the functions of the web browser.

[0106] Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, for example, as a data server, or that includes a middleware component, for example, an application server, or that includes a front-end component, for example, a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back- end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of wireline or wireless digital data communication (or a combination of data communication), for example, a communication network. Examples of communication networks include a local area network (LAN), a radio access network (RAN), a metropolitan area network (MAN), a wide area network (WAN), Worldwide Interoperability for Microwave Access (WIMAX), a wireless local area network (WLAN) using, for example, 802.1 lx or other protocols, all or a portion of the Internet, another communication network, or a combination of communication networks. The communication network can communicate with, for example, Internet Protocol (IP) packets, frame relay frames, Asynchronous Transfer Mode (ATM) cells, voice, video, data, or other information between network nodes.

[0107] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0108] While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any inventive concept or on the scope of what can be claimed, but rather as descriptions of features that can be specific to particular implementations of particular inventive concepts. Certain features that are described in this specification in the context of separate implementations can also be implemented, in combination, in a single implementation. Conversely, various features that are described in thecontext of a single implementation can also be implemented in multiple implementations, separately, or in any sub-combination. Moreover, although previously described features can be described as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can, in some cases, be excised from the combination, and the claimed combination can be directed to a sub-combination or variation of a subcombination.

[0109] Particular implementations of the subject matter have been described. Other implementations, alterations, and permutations of the described implementations are within the scope of the following claims as will be apparent to those skilled in the art. While operations are depicted in the drawings or claims in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed (some operations can be considered optional), to achieve desirable results. In certain circumstances, multitasking or parallel processing (or a combination of multitasking and parallel processing) can be advantageous and performed as deemed appropriate.

[0110] The separation or integration of various system modules and components in the previously described implementations should not be understood as requiring such separation or integration in all implementations, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0111] Accordingly, the previously described example implementations do not define or constrain the present disclosure. Other changes, substitutions, and alterations are also possible without departing from the scope of the present disclosure.

[0112] Furthermore, any claimed implementation is considered to be applicable to at least a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer system comprising a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method or the instructions stored on the non- transitory, computer-readable medium.

[0113] APPENDIX

[0114] EXHIBIT A: Example of a Final Configuration{"analytics": {"attribution": {"custom": {"active": false},"standard": {"active": true}},"conversions": [{"countld": "event_id","eventType": "page_view","friendlyName" : "bestowlabs-dev","name": "conversionO","operation": "equals","value": "https: / / uni-dev.bestowlabs.com / test / bestowlabs-dev.html"},{"countld": "event_id","eventType": "custom","friendlyName" : "all_test_events","name": "conversionl","operation": "contains","value": "test"},{"countld": "event_id","eventType": "custom","friendlyName" : "all_wait_2_events","name": "conversion2","operation": "equals","value": "test_wait_2"},{"countld": "event_id","eventType": "page_view","friendlyName": "all_tests","name": "conversions","operation": "contains","value": " / test"},{"countld": "event_id","eventType": "page_view","friendlyName" : "all_tests","name": "conversion4","operation": "contains","value": " / test"}],"reporting": {"channelLogic": "case when event ev name is not null then 'direct' end as channel output","sessionTimeoutWindow": 30,"validQuery StringParams": "source|campaign|clid|term|medium|channel"}},"client": {"allowDebugLogging": true,"autotracking": {"defaultldentityData": {"city": ["city"],"dob": ["birth","bday","bdate","bmonth","byear","dob"],"email": ["email"],"firstName": ["firstname","fn","fname","givenname","forename"],"gender": ["male","boy","man","female","girl","woman"],"lastName": ["lastname","In","Iname","surname","sname","familyname"],"month": ["month","mo","mnth","dobm"],"name": ["name","fullname"],"phone": ["phone","mobile","contact","tel"],"state": ["state","province"],"username": ["username"],"year": ["year","doby"],"zipCode": ["zip","zipCode","pincode","pcode","postalcode","postcode"]},"enabled": true,"events": {"change": {"data": {"checked": "checked","id": "id","name": "name","type": "type","value": "value"},"targetList": ["#auto-track-me input"]}},"flags": {"dataset": true,"debug": true,"event": true,"hash": true,"identify": true,"normalize": true,"validate" : true},"identities": {"email": {"algo": "SHA-256","salt": "dev.bestowlabs"},"phone": {"algo": "SHA-256","salt": "dev.bestowlabs"}}},"cookies": {"browserld": {"name": "uni_bid"},"campaignTracker": {"name": "uni_ct"},"serverld": {"name": "uni_sid"}},"domains": [{"autoTrackingScriptUrl": " / / uni-dev.bestowlabs.com / scripts / uni.at.vl.20240228- OOl.js","checker": {},"cookieDomain" : "uni-dev.bestowlabs.com","default": true,"eventEndpoint": " / / uni-dev. bestowlabs.com / uni / vl / event","mainScriptUrl": " / / uni-dev.bestowlabs. com / scripts / default-script.vl.20240311-OOl.js}],"fallbackldRules" : [{"key": "uni_uuid","location": "qs-referrer","operation": "exists","type": "uuid"}],"localStoragePrefix": "uni_ls","pageViewOnLoad" : true,"privacy": [{"key": "DNT","location": "header","operation": "equals","type": "DNT","value": " 1"},{"key": "sec-gpc","location": "header","operation": "exists","type": "DNT"}]},"hash":nedla6ec7789e82e76fd0fi421d9536e2422fi)a85","name" : "uni-dev-bestowlabs-com","server": {"allowlist": {"domains": ["uni-dev.bestowlabs.com"]},"env": "dev","uniEndpoint": "https: / / us-westl-bstw-qa-martech.cloudfunctions.net / dev- bestowlabs-uni-endpoint""version": "vl"}

[0115] EXHIBIT B: Example of a Configuration Definition export type PartnerConfig = Readonly<Required<PartnerConfigProperties> & { client: ClientConfig server: ServerConfig analytics: AnalyticsConfigexport type PartnerConfigOverride = PartnerConfigProperties & { client: Omit<Partial<ClientConfig>, 'autotracking' | 'domains'> & { autotracking: Partial<AutoTrackingOptions>, domains: DomainOptionsf] } server: ServerConfig analytics: Partial<AnalyticsConfig>} export interface BasePartnerConfig { client: Omit<ClientConfig, 'domains' | 'autotracking'> & { autotracking: BaseAutoTrackingOptions } analytics: Omit<AnalyticsConfig, 'conversions^} export interface CookiePropertyOptions { name: string props?: { [key: string]: string | null }} export interface DomainOptions { checker: RegExp cookieDomain: string mainScriptUrl: string / / url of the script to be loaded autoTrackingScriptUrl: string / / url of the script to be loaded for autotracking eventEndpoint: string / / endpoint to send events to default?: boolean} export interface FallbackldRule { location: 'header' | 'cookie' | 'querystring' | 'qs-referrer' key: string type: 'uuid' | 'externalld' value? : string | undefined operation: 'equals' | 'contains' | 'exists'} export interface ConversionOptions { countld: string eventType: 'page_view' | 'custom' | 'identity' | 'id' dataPath?: string friendlyName: string name: string operation: 'contains' | 'equals' | 'exists' value: string} export interface AttributionOptions { custom: {active: boolean lookBackwindow?: number type?: 'all' | 'first'} standard: { active: boolean}} export interface ReportingOptions { channelLogic: string sessionTimeoutWindow: number validQueryStringParams: string} export interface AnalyticsConfig { attribution: AttributionOptions conversions: ConversionOptionsf] reporting: ReportingOptions} export interface ExcludeListOptions { querystringCheck?: RegExp pathCheck?: RegExp} export interface AllowListOptions { domains: stringf] querystringCheck?: RegExp pathCheck?: RegExp} export interface ServerConfig { env: string excludeList?: ExcludeListOptions allowlist: AllowListOptions uniEndpoint: string} export interface PartnerConfigProperties { version: string name: string hash?: string} export interface CampaignKeyOptions { full?: stringf] anon?: stringf]}export interface CookieOptions { serverld: CookiePropertyOptions browserld: CookiePropertyOptions campaignTracker: CookiePropertyOptions} export interface PrivacyRule { location: 'header' | 'cookie' | 'querystring' | 'qs-referrer' key: string type: 'DNT' | 'KYC | 'ANON' value? : string | undefined operation: 'equals' | 'contains' | 'exists'} export interface TagOptions {[key: string]: any'meta-pixel'?: any'google-ads'?: any'google-analytics'?: any'stackadapt'?: any'commission-junction'?: any} export interface AutoTrackingFlags { debug: boolean event: boolean identify: boolean validate: boolean normalize: boolean hash: boolean dataset: boolean} export interface AutoTrackingEvent { targetList: stringf] data: {[key: string]: string}} export interface AutoTrackingidentity { algo: Hash Algo salt?: string} export interface AutoTrackingOptions { enabled: boolean flags?: AutoTrackingFlagsdefaultldentityData: { [key: string]: stringf] } events?: { [key: string]: AutoTrackingEvent } identities?: { [key: string]: AutoTrackingidentity }} export type BaseAutoTrackingOptions = Omit<AutoTrackingOptions, 'events' | 'identities'> export interface ClientConfig { campaignKeys? : CampaignKeyOptions fallbackldRules? : FallbackIdRule[] cookies: CookieOptions local StoragePrefix: string / / prefix for local storage domains: DomainOptions[] privacy: Privacy Rule[] pageViewOnLoad: boolean / / trigger page view on load allowDebugLogging: boolean / / allow debug logging (browser console logging) tags?: TagOptions / / tags to be loaded autotracking: AutoTrackingOptions} export enum HashAlgo {SHA1 = 'SHA-1',SHA256 = 'SHA-256',SHA384 = 'SHA-384',SHA512 = 'SHA-512'} export type ConfigMap = Map<string, PartnerConfig>

Claims

CLAIMSWhat is claimed is:

1. A computer-implemented method, comprising: loading, using a browser, a webpage containing a unified (UNI) tag; sending, using a tag worker of a cloud-based serverless platform that evaluates a host / request from the browser, a partner configuration to the browser to dynamically load partner-configured client-side scripts, wherein the partner-configured client-side scripts permit automatic modification of data collection to anonymize users, prevent data from collection, or to collect user identifiers; generating, using the browser, a call to an event worker of the cloud-based serverless platform; sending, by the event worker, data about an event to an event endpoint; providing, by the event endpoint, a hypertext transfer protocol (HTTP) endpoint for the event worker to post to; and forwarding, by a validate worker, event data to a bucket publish worker or an enrichment worker.

2. The computer-implemented method of claim 1, comprising: generating, by the event worker, the data about an event; and based on a response from the event endpoint, setting, by the event worker, data for enrichment.

3. The computer-implemented method of claim 1, comprising: if enrichment exists for a userid (UID) / hostname, returning, by the event endpoint, enrichment data to the browser.

4. The computer-implemented method of claim 1, comprising: receiving, by the enrichment worker, the event data; and based on the partner configuration, sending, by the enrichment worker, the event data to zero-to-many asynchronous enrichment processes.

5. The computer-implemented method of claim 4, comprising:receiving, by an enrichment process, the event data from the enrichment worker; and calling, by the enrichment process, an enrichment endpoint with enriched data based on the event data.

6. The computer-implemented method of claim 5, comprising: receiving, from the enrichment process, the enriched data; and based on a type of the enriched data and a client configuration, either:1) updating, by the enrichment endpoint, a state in an enrichment data database; or2) calling, by the enrichment endpoint, a partner application programming interface.

7. The computer-implemented method of claim 1, comprising: sending, by the bucket publish worker, the event data to a pub / sub for storage in a data lake of events.

8. A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform one or more operations, comprising: loading, using a browser, a webpage containing a unified (UNI) tag; sending, using a tag worker of a cloud-based serverless platform that evaluates a host / request from the browser, a partner configuration to the browser to dynamically load partner-configured client-side scripts, wherein the partner-configured client-side scripts permit automatic modification of data collection to anonymize users, prevent data from collection, or to collect user identifiers; generating, using the browser, a call to an event worker of the cloud-based serverless platform; sending, by the event worker, data about an event to an event endpoint; providing, by the event endpoint, a hypertext transfer protocol (HTTP) endpoint for the event worker to post to; and forwarding, by a validate worker, event data to a bucket publish worker or an enrichment worker.

9. The non-transitory, computer-readable medium of claim 8, comprising: generating, by the event worker, the data about an event; and based on a response from the event endpoint, setting, by the event worker, data for enrichment.

10. The non-transitory, computer-readable medium of claim 8, comprising: if enrichment exists for a userid (UID) / hostname, returning, by the event endpoint, enrichment data to the browser.

11. The non-transitory, computer-readable medium of claim 8, comprising: receiving, by the enrichment worker, the event data; and based on the partner configuration, sending, by the enrichment worker, the event data to zero-to-many asynchronous enrichment processes.

12. The non-transitory, computer-readable medium of claim 11, comprising: receiving, by an enrichment process, the event data from the enrichment worker; andcalling, by the enrichment process, an enrichment endpoint with enriched data based on the event data.

13. The non-transitory, computer-readable medium of claim 12, comprising: receiving, from the enrichment process, the enriched data; and based on a type of the enriched data and a client configuration, either:1) updating, by the enrichment endpoint, a state in an enrichment data database; or2) calling, by the enrichment endpoint, a partner application programming interface.

14. The non-transitory, computer-readable medium of claim 8, comprising: sending, by the bucket publish worker, the event data to a pub / sub for storage in a data lake of events.

15. A computer-implemented system, comprising: one or more computers; and one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations, comprising: loading, using a browser, a webpage containing a unified (UNI) tag; sending, using a tag worker of a cloud-based serverless platform that evaluates a host / request from the browser, a partner configuration to the browser to dynamically load partner-configured client-side scripts, wherein the partner-configured client-side scripts permit automatic modification of data collection to anonymize users, prevent data from collection, or to collect user identifiers; generating, using the browser, a call to an event worker of the cloud-based serverless platform; sending, by the event worker, data about an event to an event endpoint; providing, by the event endpoint, a hypertext transfer protocol (HTTP) endpoint for the event worker to post to; and forwarding, by a validate worker, event data to a bucket publish worker or an enrichment worker.

16. The computer-implemented system of claim 15, comprising: generating, by the event worker, the data about an event; and based on a response from the event endpoint, setting, by the event worker, data for enrichment.

17. The computer-implemented system of claim 15, comprising: if enrichment exists for a userid (UID) / hostname, returning, by the event endpoint, enrichment data to the browser.

18. The computer-implemented system of claim 15, comprising: receiving, by the enrichment worker, the event data; and based on the partner configuration, sending, by the enrichment worker, the event data to zero-to-many asynchronous enrichment processes.

19. The computer-implemented system of claim 18, comprising: receiving, by an enrichment process, the event data from the enrichment worker; and calling, by the enrichment process, an enrichment endpoint with enriched data based on the event data.

20. The computer-implemented system of claim 19, comprising: receiving, from the enrichment process, the enriched data; and based on a type of the enriched data and a client configuration, either:1) updating, by the enrichment endpoint, a state in an enrichment data database; or2) calling, by the enrichment endpoint, a partner application programming interface.

21. The computer-implemented system of claim 15, comprising: sending, by the bucket publish worker, the event data to a pub / sub for storage in a data lake of events.

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