eISSN: 3087-4084 editor@aimjournals.com
All Journals
Submit your article

International Journal of Management and Business Development

Open Access Peer Review International
Open Access

CAC Payback Period Optimization Through Automated Cohort Analysis

DOI https://doi.org/10.55640/ijmbd-v02i10-02
PDF
Anjali Kale 1 ,
4 Ennov Solutions Inc – Software Solutions for Life Sciences, USA

Abstract

The Customer Acquisition Cost (CAC) Payback Period is one of the key indicators in determining the effectiveness of marketing strategies and sales, especially in Software-as-a-Service (SaaS) and other subscription business models. The existing methods of CAC payback analysis are usually based on aggregate data that does not correct to temporal and behaviour heterogeneity of cohorts of customers. The study presents an automated and machine learning capable framework of cohort analysis which could be used to optimize the CAC Payback Period. The strategy to be proposed will utilize the concept of temporal segmentation, behavioural track, and predictive modelling to link the costs of an acquisition with the revenue inflow more closely in real time. In several SaaS datasets that have been tested empirically, cohort-based insights cause the payback period to shrink, increased customer lifetime value (CLTV), and increased marketing return on investment (ROI). The theoretical frames, the methodology of the implementation, international best practices and strategic challenges are provided in the paper, with explanations offering a complete handbook to practitioners and researchers who want to enhance the efficiency of their marketing by utilizing the information on customer groups.

Keywords

Customer Acquisition Cost (CAC), CAC Payback Period, Cohort Analysis, SaaS Metrics, Customer Retention, Marketing ROI, Subscription Models, Machine Learning, Customer Lifetime Value (CLTV)

References

📄 H. Chen, V. Kumar, and V. Mittal, “Customer Lifetime Value: Measurement and Strategic Implications,” Journal of Marketing, vol. 85, no. 1, pp. 49–69, 2021, doi: 10.1177/0022242920961359.
📄 A. Croll and B. Yoskovitz, Lean Analytics: Use Data to Build a Better Startup Faster. Sebastopol, CA, USA: O’Reilly Media, 2013.
📄 P. S. Fader and B. G. S. Hardie, “Probability Models for Customer-Base Analysis,” Journal of Interactive Marketing, vol. 23, no. 1, pp. 61–69, 2009, doi: 10.1016/j.intmar.2008.10.005.
📄 KeyBanc Capital Markets, SaaS Survey Results: Annual Private SaaS Company Survey, 2023.
📄 D. L. Rogers, The Digital Transformation Playbook: Rethink Your Business for the Digital Age. New York, NY, USA: Columbia University Press, 2020.
📄 P. D. Berger, N. Eechambadi, M. George, D. R. Lehmann, R. Rizley, and R. Venkatesan, “From Customer Lifetime Value to Shareholder Value: Theory, Empirical Evidence, and Issues for Future Research,” Journal of Service Research, vol. 9, no. 2, pp. 134–155, 2006, doi: 10.1177/1094670506293580.
📄 S. Gupta and D. R. Lehmann, “Customers as Assets,” Journal of Interactive Marketing, vol. 17, no. 1, pp. 9–24, 2003, doi: 10.1002/dir.10045.
📄 V. Kumar and W. Reinartz, Customer Relationship Management: Concept, Strategy, and Tools, 3rd ed. Cham, Switzerland: Springer, 2018.
📄 A. Tashakkori and C. Teddlie, SAGE Handbook of Mixed Methods in Social & Behavioral Research, 2nd ed. Thousand Oaks, CA, USA: SAGE Publications, 2010.
📄 P. S. Fader and B. G. S. Hardie, “Customer-Base Valuation in a Contractual Setting: The Perils of Ignoring Heterogeneity,” Marketing Science, vol. 28, no. 3, pp. 363–375, 2009.
📄 Bain & Company, The SaaS Playbook: Optimizing for Growth and Retention, Bain Report, 2021.
📄 How to Use Cohort Analysis to Improve Customer Retention, Harvard Business Review, 2023.
📄 ProfitWell, Metrics That Matter: CAC Payback Period Optimization, 2022.
📄 Amplitude, “Real-Time Cohort Analysis for SaaS Growth,” Amplitude Blog, 2023.
📄 GDPR.eu, Understanding GDPR Compliance in Analytics, 2024.
📄 Bain & Company, Beyond NPS: Customer Loyalty Analytics in the Digital Era. [Online]. Available: https://www.bain.com
📄 S. Chatterjee, N. P. Rana, K. Tamilmani, and D. Sharma, “The next generation of marketing: How artificial intelligence is transforming the marketing landscape,” Journal of Business Research, vol. 120, pp. 474–485, 2020, doi: 10.1016/j.jbusres.2020.03.032.
📄 KeyBanc Capital Markets, SaaS Survey Results, 2022. [Online]. Available: https://www.key.com
📄 D. McCarthy, P. Fader, and B. Hardie, “Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data,” Journal of Marketing, vol. 81, no. 1, pp. 17–35, 2017, doi: 10.1509/jm.15.0412.
📄 P. Voigt and A. von dem Bussche, The EU General Data Protection Regulation (GDPR): A Practical Guide. Cham, Switzerland: Springer, 2017.

Most read articles by the same author(s)

1 2 > >>