Adaptive Marketing: Redefining Personal Care Industry Tactics
Wenzel Vaughn P Pestaño | Ruth L. Legaspi
Discipline: Marketing
Abstract:
The COVID-19 pandemic disrupted consumer behavior and
changed the market landscape across all industries – retail
or business-to-business. This study specifically focuses on
the personal care industry, which the pandemic has
challenged to adapt its business model, marketing strategies, and
action plans to retain the customers' evolving dispositions and
behavior in the changing post-pandemic milieu. The primary
objective was to identify actionable segments within the customer
base and tailor marketing strategies to enhance engagement and
retention.
Using historical data (2020-2023), the researchers applied data mining
techniques and statistical analysis. K-means clustering segmented
customers, while the Apriori algorithm identified upselling
opportunities. Optimization techniques determined the best actions
for each segment to improve revenue. The effectiveness of the
strategy and action plans was evaluated by comparing control and
treatment groups through conversion rates.
Key findings included a 0.71 silhouette score for clustering quality,
27% conversion rate for adaptive marketing strategies, 35.7%
upselling frequency, a 7.91% increase in average order value (AOV),
and a 25% reduction in monthly cancellation rates. This project
highlighted the importance of updating customer segments and
refining marketing strategies to boost engagement, retention, and
business outcomes. These insights provide a foundation for the company to strengthen
its market position, increase customer loyalty, and drive sustained
growth in the clustering quality, conversion rate, upselling frequency,
average order value, and cancellation rates.
References:
- Act-On. (2017, October 10). What is adaptive marketing? (and why marketers should adapt). Act-On. https://act-on.com/learn/blog/why-the-best-marketing-is-adaptive-marketing/
- Adepoju, U. (2023, September 15). Maximizing Customer Value: The Power of Upselling in E-commerce - FigPii blog. FigPii blog. https://www.figpii.com/blog/upselling-vs-cross-selling
- Barrera, F., Segura, M., & Maroto, C. (2024). Multiple criteria decision support system for customer segmentation using a sorting outranking method. Expert Systems with Applications, 238, 122310. https://doi.org/https://doi.org/10.1016/j.eswa.2023.122310
- Bottero, M., D’Alpaos, C., & Oppio, A. (2019). Ranking of Adaptive Reuse Strategies for Abandoned Industrial Heritage in Vulnerable Contexts: A Multiple Criteria Decision Aiding Approach. Sustainability, 11(3). https://doi.org/10.3390/su11030785
- Liu, D., Tang, Z., & Cai, Y. (2022). A Hybrid Model for China’s Soybean Spot Price Prediction by Integrating CEEMDAN with Fuzzy Entropy Clustering and CNN-GRU-Attention. Sustainability, 14 (23). https://doi.org/10.3390/su142315522
- MacDonald, J. (2024, March 14). 7 types of customers and how to convert each of them https://www.linkedin.com/pulse/7-types-customers-how-convert-each-them-jon-macdonald-ivfue
- Maeda, C. (2020, February 20). Increase your conversion rate by 20% using tailored landing pages for your digital marketing campaigns. https://www.linkedin.com/pulse/increase-your-conversion-rate-20-using-tailored-landing-carl-maeda/
- Martín, M., Jiménez-Martín, A., Mateos, A., & Hernández, J. Z. (2021). Improving A/B testing on the basis of possibilistic Reward Methods: a Numerical analysis. Symmetry, 13(11), 2175. https://doi.org/10.3390/sym13112175.
- Minor, D. O. (2018). Implementing a Surgical Pathway to Reduce Operating Room Cancellation Rates.(Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/4562
- Olubiyi et al. (2021). Application of linear programming to profit maximization in water production. Research Gate. https://doi.org/10.9790/5728-1703013541.
- Xie, H. (2021). Research and case analysis of Apriori Algorithm based on mining Frequent Item-Sets. Open Journal of Social Sciences, 09(04), 458–468. https://doi.org/10.4236/jss.2021.94034