Analyzing the Customer Journey through Data Analytics

Abstract

The quantitative content analysis identified five underlying themesof thecustomer journey, namely, service satisfaction, failure and recovery, co-creation, customer response, channels and technologicaldisruption.Theresults sectionreviewed anddiscussedeach themeand its sub-themes in turn. The review identified important gaps in the literature related to the key stages of a customer journey. Customer Journey Mapping (CJM) is pivotal for understanding and enhancing customer experiences across touchpoints. The integration of real-time data analytics into CJM has transformed this traditionally static tool into a dynamic framework capable of tracking and optimizing customer interactions. This paper explores the methodologies, tools, and benefits of combining real-time data analytics with CJM. The discussionincludesacomprehensivereviewofrelatedliterature,implementationstrategies, challenges, and future directions. This paper argues that real-time data analytics enhances CJM by enabling continuous adaptation to customer behaviour’s, resulting in improved customer satisfaction and business performance.Understanding and enhancing customer experiences has emerged as a central focus for businesses seeking to remain competitive in today’s dynamic market landscape. Customer Journey Mapping (CJM), a widely used methodology, provides a structured approach to visualizing the customer\'s interactions across various touchpoints with a business.Thecustomerjourneyisbecomingmorecomplexduetodigitizationofbusinessprocesses, broadening the gap between the proposed journey and the journey that is actuallyexperiencedbycustomers.CustomerJourneyAnalytics(CJA)aimstodetectandanalyse pain points in the journey in order to improve the customer experience. This study proposes an extended version of the Customer Journey Mapping (CJM) model, to measure the impact of different types of touchpoints along the customer journey on customer experience, and to applyprocessminingtogain more insightinthegap betweenproposed and actualjourneys.Moreover,thismodelisusedtodevelopdedicatedCJAbasedonprocessminingtechniques.Acasestudyone-commerceappliestheCJM-modelinpracticeandshowshow thecombinationofprocessminingtechniquescananswertheanalysisquestionsthatarisein customerjourneymanagement.Thisresearchcontributestobothacademicdiscourseand managerial practice by offering actionable insights into how brands can ethically and effectively engage with digital consumers. It underscores the necessity for marketers tobalancetechnologicalinnovationwithconsumertrustandtransparency.Ultimately,thisstudy provides a robust framework for understanding the digital consumer psyche and offersstrategicrecommendationsfornavigatingtherapidlyevolvinglandscapeofsocialmedia marketing.

Introduction

Customer Journey Analytics (CJA) is a data-driven process that tracks and analyzes every customer interaction across multiple channels over time. It goes beyond simple journey mapping to assess how each interaction influences customer behavior and decision-making, helping businesses optimize the customer experience and improve satisfaction, engagement, and loyalty.

Key Concepts

• Customer Journey Map: A visual representation (like a flowchart) of customer interactions and touchpoints with a brand.

• Analytics Layer: Adds metrics like customer satisfaction (CSAT), effort scores, and behavioral data to analyze what drives customer actions.

• Goals:

  • Identify and resolve pain points

  • Optimize marketing and service touchpoints

  • Increase customer satisfaction, conversion rates, and retention

Modern Challenges & Opportunities

• The rise of digital platforms, smartphones, and social media has fragmented customer journeys.

• Customers now engage with brands across multiple devices and channels, and can easily switch to competitors or publicly share their experiences.

• Brands no longer fully control the communication; customers play an active role in shaping brand perception.

Benefits of CJA

• Personalized experiences and proactive service

• Real-time decision-making and optimization

• Better understanding of high-value customers

• Stronger alignment between business operations and customer needs

Steps to Measure Customer Journeys

1. Create Journey Maps

2. Identify Data Needs

3. Analyze Customer Behavior Data

Definition

Customer journey analytics transforms raw data into actionable insights about how customers interact with a brand. It aims to create a unified view of the customer to improve acquisition, retention, and loyalty.

Literature Review Findings

• Reviewed 147 academic papers (up to May 2020)

• Identified five core themes:

  1. Service Satisfaction

  2. Failure and Recovery

  3. Customer Response

  4. Co-creation

  5. Channel and Technological Disruption

• Found that while customer journey research has grown rapidly, it remains theoretically fragmented.

• Suggested more systematic integration and attention to gaps across pre-purchase, purchase, and post-purchase stages.

Recommendations for Organizations

To fully benefit from customer journey analytics, companies should:

• Invest in high-quality, integrated data systems

• Build a data-driven culture

• Stay compliant with data privacy laws

• Continuously adapt to evolving customer behavior and technology

Conclusion

Thecustomerjourneyhasbeengainingattentionfrombothacademiaandpractitionersover thepastdecade.Thecustomerjourneyliteraturehasbeengrowingatarapidrate,especially in the last three and a half years, when more than half of the retrieved literature was published. However, the literature has appeared as incoherent due to its diverse theoretical background.Therefore,thisstream-basedsystematicreviewhasattemptedtoaggregateand integrate the currentbodyof knowledge by should be inserted a randomness in the analysis ofacquireddata.Thisinsertsafactorofuncertaintythatmayaffecttheresultsofthemodels. A method called traditional collaborative filtering recommendation algorithm is useful to compromisebothdesiredaccuracyandprivacyofdata.Thebenefitofloosingabigworkforce fromthisfieldandexploitinginothermorecreativeaspectsleavespromisesfortheindustry Analysing the customer journey through data analytics offers powerful benefits, from enhanced customer experiences to improved conversion rates and increased customer loyalty.Whendoneeffectively,itallowsorganizationstobetterunderstandcustomerneeds, optimize marketing strategies, and align internal processes with customer expectations. Tofullyrealizethesebenefits,organizationsmust: • Investinhigh-quality,integrateddatasystems. • Fosteradata-drivenculture. • Ensurecompliancewithevolvingdataprivacylaws. • Continuouslyadapttochangesin customerbehaviourandtechnological advancements. Inaworldwherecustomerjourneysarebecomingincreasinglyfragmentedanddynamic,data analytics is not just a tool—it\'s a strategic imperative

References

[1] Richardson, \"Using customer journey maps to improve customer experience,\" Harvard Business Review, 2010. [2] K.N.LemonandP.C.Verhoef,\"Understandingcustomerexperiencethroughoutthe customer journey,\" Journal of Marketing, vol. 80, no. 6, pp. 69–96, 2016. [3] B.J.PineandJ.H.Gilmore,TheExperienceEconomy,HarvardBusinessReviewPress,2011. [4] McKinsey&Company,\"Digitaltransformationincustomerjourneys,\"2020.[Online]. Available: [5] https://www.mckinsey.comForrester Research, \"Real-time analytics and the future of customer experience,\" 2020. [Online]. Available: https://www.forrester.com [6] Amplitude,\"Driving customerengagementthroughreal-timejourneymapping,\"2021. [Online]. Available: https://www.amplitude.com [7] Apache Kafka Documentation, \"Streaming data for customer analytics,\" 2022. [Online]. Available: https://kafka.apache.org [8] Tableau,\"Real-timeanalyticsforcustomerexperience,\"2021.[Online].Available:https://www.tableau.com [9] PwC,\"Real-timehealthcareanalytics:Improvingpatientjourneys,\"2021.[Online].Available: https://www.pwc.com [10] Accenture,\"Telecommunicationstrends:EnhancingCXwithreal-timedata,\"2022. [Online]. Available: https://www.accenture.com [11] Salesforce,\"Overcomingdatasilosincustomerjourneymapping,\"2021.[Online].Available: https://www.salesforce.com

Copyright

Copyright © 2025 Priyanka Kushwaha. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.