Digital Advertising Traffic Operation: Machine Learning for Process Discovery

📝 Abstract

In a Web Advertising Traffic Operation it’s necessary to manage the day-to-day trafficking, pacing and optimization of digital and paid social campaigns. The data analyst on Traffic Operation can not only quickly provide answers but also speaks the language of the Process Manager and visually displays the discovered process problems. In order to solve a growing number of complaints in the customer service process, the weaknesses in the process itself must be identified and communicated to the department. With the help of Process Mining for the CRM data it is possible to identify unwanted loops and delays in the process. With this paper we propose a process discovery based on Machine Learning technique to automatically discover variations and detect at first glance what the problem is, and undertake corrective measures.

💡 Analysis

In a Web Advertising Traffic Operation it’s necessary to manage the day-to-day trafficking, pacing and optimization of digital and paid social campaigns. The data analyst on Traffic Operation can not only quickly provide answers but also speaks the language of the Process Manager and visually displays the discovered process problems. In order to solve a growing number of complaints in the customer service process, the weaknesses in the process itself must be identified and communicated to the department. With the help of Process Mining for the CRM data it is possible to identify unwanted loops and delays in the process. With this paper we propose a process discovery based on Machine Learning technique to automatically discover variations and detect at first glance what the problem is, and undertake corrective measures.

📄 Content

Digital Advertising Traffic Operation: Machine Learning for Process Discovery

Massimiliano Dal Mas me @ maxdalmas.com     ABSTRACT In a Web Advertising Traffic Operation it’s necessary to manage the day-to-day trafficking, pacing and optimization of digital and paid social campaigns. The data analyst on Traffic Operation can not only quickly provide answers but also speaks the language of the Process Manager and visually displays the discovered process problems. In order to solve a growing number of complaints in the customer service process, the weaknesses in the process itself must be identified and communicated to the department. With the help of Process Mining for the CRM data it is possible to identify unwanted loops and delays in the process. With this paper we propose a process discovery based on Machine Learning technique to automatically discover variations and detect at first glance what the problem is, and undertake corrective measures.

Keywords: Process Mining, Business process management, Declarative process models, Digital Advertising, Online Advertising, Trafficking, Adv Operations Management, Mixed Integer Linear Programming (MILP), Optimization, Scheduling, Stakeholders, Project Management, End-To-End management, Campaign Workflow, Analytical Skills, People management skills, Relationships, CRM, Operations, Ad Platforms, Creative delivery, Campaign Performance, KPIs

INTRODUCTION
In a Web Advertising Traffic Operation it’s necessary to ensure quick and accurate trafficking of campaigns, campaign performance optimizations, troubleshooting, and reporting. Ensure that campaigns launch on time and are fully executed according to the insertion order. [1] To deliver digital campaigns it’s necessary _______  If you have read this paper and wish to be included in a mailing list (or other means of communication) that I maintain on the subject, than send e-mail to: me @ maxdalmas.com to ensure quick and accurate trafficking
of campaigns, campaign performance optimisations, troubleshooting, and reporting and that campaigns launch on time and are fully executed according to the insertion orders. Different processes are involving different activities with advertisers, agencies, and publishers to oversee proper implementation of campaigns (ad tags, beacons, reporting discrepancies, click tracking, etc.) with the retail client as the technical digital media expert. Moreover it is necessary to maintain proactive communications on account status across multiple account stakeholders
including Account Managers, Sales Managers, Senior Management and customer contacts ensuring immediate and direct feedback to both internal and external stakeholders where necessary monitor and improve customer satisfaction as it relates to successful campaign management. Usually Traffic Managers create document on operations best practices policies and procedures, including an I/O trafficking SLA but trafficking is an ongoing process. Unlike products, processes are less tangible. Processes may only exist in the minds of people and it is difficult to “materialize processes”. In this paper we define a process mining techniques for the trafficking aim to discover, monitor and improve real processes by extracting knowledge from event logs.
We define a technique that automatically discover a process model from event data on a Traffic Office.

THE BASIC IDEA Processes can be defined from human behavior partly controlled by procedures and/or information systems. Normative or descriptive models may be used to document processes. But, these models are human- made artifacts that could not necessarily say much about the “real” process performed. As a result, there may be a disconnection between model and reality. Moreover, the people involved in a process are typically unable to understand the corresponding process model and cannot easily see what is actually going on (especially if the products are services or data).

Process Mining Process mining combines process models and event data in various novel ways. As a result, one can find out what people and organizations really do. For example, process models can be automatically discovered from event data. Compliance can be checked by confronting models with event data. Loops can be uncovered by replaying timed events on discovered or normative models. Hence, process mining can be used to identify and understand loops, bottlenecks, inefficiencies, deviations, and risks.

Machine Learning for Process Mining As part of Artificial Intelligence we can define Machine Learning as the field that “gives computers the ability to learn without being explicitly programmed” [2]. The field of Machine Learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in th

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