Predicting Next Touch Point In A Customer Journey: A Use Case In Telecommunication

Author(s):  
Marwan Hassani ◽  
Stefan Habets

Customer journey analysis is rapidly increasing in popularity, as it is essential for companies to understand how their customers think and behave. Recent studies investigate how customers traverse their journeys and how they can be improved for the future. However, those researches only focus on improving the process for future customers by analyzing the historical data. This research focuses on helping the current customer immediately, by analyzing if it is possible to predict what the customer will do next and accordingly take proactive steps. We propose a model to predict the customer's next contact type (touch point). At first we will analyze the customer journey data by applying process mining techniques. We will use these insights then together with the historical data of accumulated customer journeys to train several classifiers. The winning of those classifiers, namely XGBoost, is used to perform a prediction on a customer's journey while the journey is still active. We show on three different real datasets coming from interactions between a telecommunication company and its customers that we always beat a baseline classifier thanks to our thorough pre-processing of the data.

Author(s):  
Marvin Drewel ◽  
Leon Özcan ◽  
Jürgen Gausemeier ◽  
Roman Dumitrescu

AbstractHardly any other area has as much disruptive potential as digital platforms in the course of digitalization. After serious changes have already taken place in the B2C sector with platforms such as Amazon and Airbnb, the B2B sector is on the threshold to the so-called platform economy. In mechanical engineering, pioneers like GE (PREDIX) and Claas (365FarmNet) are trying to get their hands on the act. This is hardly a promising option for small and medium-sized companies, as only a few large companies will survive. Small and medium-sized enterprises (SMEs) are already facing the threat of losing direct consumer contact and becoming exchangeable executers. In order to prevent this, it is important to anticipate at an early stage which strategic options exist for the future platform economy and which adjustments to the product program should already be initiated today. Basically, medium-sized companies in particular lack a strategy for an advantageous entry into the future platform economy.The paper presents different approaches to master the challenges of participating in the platform economy by using platform patterns. Platform patterns represent proven principles of already existing platforms. We show how we derived a catalogue with 37 identified platform patterns. The catalogue has a generic design and can be customized for a specific use case. The versatility of the catalogue is underlined by three possible applications: (1) platform ideation, (2) platform development, and (3) platform characterization.


2021 ◽  
Vol 11 (11) ◽  
pp. 4751
Author(s):  
Jorge-Félix Rodríguez-Quintero ◽  
Alexander Sánchez-Díaz ◽  
Leonel Iriarte-Navarro ◽  
Alejandro Maté ◽  
Manuel Marco-Such ◽  
...  

Among the knowledge areas in which process mining has had an impact, the audit domain is particularly striking. Traditionally, audits seek evidence in a data sample that allows making inferences about a population. Mistakes are usually committed when generalizing the results and anomalies; therefore, they appear in unprocessed sets; however, there are some efforts to address these limitations using process-mining-based approaches for fraud detection. To the best of our knowledge, no fraud audit method exists that combines process mining techniques and visual analytics to identify relevant patterns. This paper presents a fraud audit approach based on the combination of process mining techniques and visual analytics. The main advantages are: (i) a method is included that guides the use of the visual capabilities of process mining to detect fraud data patterns during an audit; (ii) the approach can be generalized to any business domain; (iii) well-known process mining techniques are used (dotted chart, trace alignment, fuzzy miner…). The techniques were selected by a group of experts and were extended to enable filtering for contextual analysis, to handle levels of process abstraction, and to facilitate implementation in the area of fraud audits. Based on the proposed approach, we developed a software solution that is currently being used in the financial sector as well as in the telecommunications and hospitality sectors. Finally, for demonstration purposes, we present a real hotel management use case in which we detected suspected fraud behaviors, thus validating the effectiveness of the approach.


2018 ◽  
Vol 7 (3) ◽  
pp. 13-21
Author(s):  
Tamunosiki V. Ogan

An analysis of the principles of democracy was carried out. The objective was to delineate the extent to which the Nigerian state is democratic and how its current democratic ideals could impact on its future existence as a state. The method adopted for the study was that of content analysis, which involved conceptual and historical analyses of textual data. It was discovered from historical data that the Nigerian state runs a system of government, which promotes internal colonialism of the minority groups by the major ones. This political imbalance was shown to create social and political tension, where the peripheral groups were hostile to the core regions. It was recommended in the study that if the Nigerian state is to subsist in the future, then it has to restructure its political institutions to promote true federalism as well as imbibe and practice standard democratic ideals.Keywords: Democratic ideal, Nigeria, Hope, Future


2019 ◽  
Author(s):  
Shintia Mustika ◽  
Doni Marlius

Bank are financial institutions that play a role in supporting economic development in a region, where the activitiesof raising funds and channeling funds in the form of loans or lending is a from of money circulation to stabilize the economy. The purpose of this study was to conduct an analysis of the level of bank financial health of the PT. Bank Perkreditan Rakyat (BPR) Batang Palangki, for the years 2014-2018. Historical data is taken from bank financial reports that have been published. Analysis of bank financial soundness using the CAMEL method (Capital, Assets, Management, Earning, Liquidity). The results showed that the 2014-2018 PT. BPR Batang Palangki financial health level showed a healthy category, where the average value of the CAR ratio was 28,66%, the KAP ratio was 1,15%, the NPM ratio was 24,88%, the ROA ratio was 3,38%, BOPO ratio of 74,83%, and LDR ratio of 56,30%. It is expected that in the in the future BPR Batang Palangki can continue to maintained according to the provisions that apply.


This chapter looks at the extent to which the semantic-based process mining approach of this book supports the conceptual analysis of the events logs and resultant models. Qualitatively, the chapter leverages the use case study of the research learning process domain to determine how the proposed method support the discovery, monitoring, and enhancement of the real-time processes through the abstraction levels of analysis. Also, the chapter quantitatively assesses the level of accuracy of the classification process to predict behaviours of unobserved instances within the underlying knowledge base. Overall, the work looks at the implications of the semantic-based approach, validation of the classification results, and their influence compared to other existing benchmark techniques/algorithms used for process mining.


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