Client Name

Loreal Pakistan

Faculty Advisor

Dr. Mohsin Sadaqat

SBS Thought Leadership Areas

Investment Decision Making

SBS Thought Leadership Area Justification

Our project aligns with the Investment Decision Making thought leadership area by developing category-specific ROI models for six major trade investments within L’Oréal Pakistan’s Professional Product Division. Using simulated data, machine learning, and econometric analysis, we quantified returns for Beauty Advisors, Paid Media, Events, Influencers, POS, and Promotional Gifts. For example, Beauty Advisors showed a consistently high ROI of 15–18x, while Paid Media returns peaked during high-demand seasons. These models provide LOPAK with a rigorous, data-driven framework for marketing budget allocation, advancing evidence-based strategic decisions, and supporting sustainable growth through efficient brand investment practices.

Aligned SDGs

GOAL 9: Industry, Innovation and Infrastructure

Aligned SDGs Justification

It aligns with SDG 9: Industry, Innovation and Infrastructure by introducing data-driven ROI models and advanced analytical tools such as Python-based machine learning and regression analysis. These innovations improve marketing decision-making and infrastructure, shifting from intuition-led planning to evidence-based strategy. For instance, customized ROI models now guide LOPAK’s annual budget planning.

NDA

Yes

Abstract

In this Experiential Learning Project (ELP), we examined the return on investment (ROI) of the brand-building activities of the Professional Product Division (PPD) of L'Oréal Pakistan. The PPD targets high-end, salon-only brands and is in an expanding, competitive beauty industry where marketing investment must be maximized to get the greatest effect. Nevertheless, before this study, the division had not been able to fit a method to the depth of its different brand investment categories in terms of measuring and evaluating their efficiency and effectiveness in a systematic and data-driven manner.

The main aim of the project was to create a program of specified and individual ROI models of the six most important types of trade investment: Beauty Advisors, Event Sponsoring, Gifts with Purchase, Transactional Paid Media, Influencer Marketing, and Point-of-Sale (POS) Animation. The study was done on independently created datasets by secondary research, industry standards, and logical estimates because no proprietary company data was available. Machine learning models of potential statements, Python-based and econometric regressions, along with other advanced analytical instruments, were utilized to recreate probable performance conditions and recommend actions.

The current research can be linked to Sustainable Development Goal 9, as it facilitates sustainable economic growth by maximizing marketing investments in employment, and it encourages innovation through data-based decision-making models in the industry. Despite the constraints associated with data inaccessibility, the project lays the groundwork for a more transparent, accountable, and effective brand investment behavior within the beauty industry in Pakistan.

Document Type

Restricted Access

Document Name for Citation

Experiential Learning Project

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Available for download on Tuesday, June 16, 2026

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