Client Name

Foodpanda

Faculty Advisor

Irfan Ahmed

SBS Thought Leadership Areas

Behavioural Studies

SBS Thought Leadership Area Justification

This project falls under the IBA-SBS thought leadership area of Behavioral Studies, as it centers on understanding how consumers respond to promotional stimuli such as discounts, vouchers, and incentives across various customer segments — particularly based on geography.

The core of the project is grounded in behavioral pricing and consumer response analysis. By examining how customers in different cities react to varying levels of discounts (e.g., low vs. high discount %), and how these responses translate into user-paid GMV, the project generates empirical evidence of price sensitivity, loyalty behavior, and promotional fatigue. Through the creation of behavioral indicators — such as GMV per PKR of discount and discount-to-GMV ratio — the analysis highlights the non-uniform nature of customer reactions across Pakistan, validating the need for region-specific promotional strategies.

The survey conducted by our team identified real time preference promotion, payment, loyalty behaviors and steps to capture back churned customers. The insights that we gained enriched our analysis and helped us identify psychological drivers behind the ordering pattern of the customers.

This work supports the broader SBS mission of advancing human behavior research, particularly in applied business contexts. While this project relies on transactional and economic signals rather than biometric tools, it contributes to the growing body of data-driven behavioral research. It complements initiatives like the Rashid Abdullah Consumer Neuroscience Lab and strengthens IBA-SBS’s reputation as a pioneer in using advanced methods to decode customer behavior and decision-making in real-world markets.

Aligned SDGs

GOAL 9: Industry, Innovation and Infrastructure

Aligned SDGs Justification

This project aligns strongly with Sustainable Development Goal (SDG) 9: Industry, Innovation, and Infrastructure, which emphasizes the need for inclusive and sustainable industrial development, resilient infrastructure, and the promotion of innovation. As Pakistan’s digital economy continues to grow, food delivery platforms like Foodpanda play a critical role in reshaping how urban populations consume goods and services. However, with rising operational costs and increased customer acquisition challenges, innovation in data-driven decision-making becomes essential.

Our ELP project contributes to SDG 9 by leveraging predictive analytics and behavioral segmentation to enhance the efficiency of business operations in the food delivery industry. Specifically, we:

  • Analyzed how infrastructure (digital platforms) and localized business strategies interact, enabling smarter discount allocation across different cities.
  • Enabled cost-effective customer re-engagement, reducing marketing waste and making promotions more targeted and sustainable.

Furthermore, the project supports the idea of digitally inclusive innovation. By analyzing customer behavior in both Tier 1 cities (like Karachi and Lahore) and emerging urban areas, the model allows Foodpanda to tailor its promotional infrastructure to underserved markets more effectively.

In the long term, this type of localized and data-backed decision-making can:

  • Improve the viability of digital services across Pakistan,
  • Support SME restaurants by driving demand where it's needed most,
  • And promote responsible resource use — in this case, marketing and discount budgets.

Thus, the project not only fulfills an immediate commercial purpose but also contributes toward broader national and global goals of innovation-led, inclusive digital growth.

The project also makes a significant contribution to SDG 12: Responsible Consumption and Production because it helps to optimize the expenditure of the resources spent on promotions. Using the input of voucher usability, marketing costs, and customer reactiveness, the research establishes trends of over-discounting and marketing inefficiencies, particularly in some customer type and geographic locations. The project is prompting Foodpanda to optimize resource allocation by recommending refined voucher targeting, behavior-based incentives and scaling back marketing burn in low-performing regions. This means that the promotions will reach the correct users at the appropriate time with little or no waste of financial resources at any given moment. This kind of practice advances a more sustainable business style one that ensures sufficient customer interactions without negatively impacting business processes in the long term.

NDA

Yes

Abstract

We conducted this ELP in collaboration with Foodpanda’s Data Analytics and FP&A teams. The goal of this project is to evaluate the impact caused by discounts, promotions, and vouchers on the behavior of the customer. The aim of this project is to increase dependence on data-driven strategies in the food delivery industry to increase order frequency, reduce discount burn, and improve user retention.

We analyze the order-placement behavior of digital and cash-paying customers based on transaction data of one of the most popular food delivery platforms. The aim is to determine the effect of payment modes on average order value, ordering frequency and use of discounts. Following extensive data cleaning and transformation, it was observed that digital customers tend to spend higher per order, apply vouchers more often and exhibit higher variances in ordering quantity. Such tendencies were corroborated with visualizations that are easy to interpret such as KDE plots, box plots and bar charts. There were more cash customers, but the digital customers demonstrated high-value behavior. The report suggests the best practices and suggestions specifically on where to run promotions, and how to intelligently use discounts to increase platform profitability and enjoyability overall.

Our methodology included a survey to collect additional behavioral insights from the users of Foodpanda within the age group of 20-26. responses gathered from the survey provided further clarity on payment method behavior, discount preference, motivational triggers and how to gain back churned customers. The survey revealed that the majority of the users would order more if given better discounts. The most preferred discounts were vouchers and restaurant-specific deals. Cash on delivery is still the dominant payment method, though many respondents showed willingness to shift to digital options if incentivized

Our team conducted an analysis of historical customer data throughout Pakistan to study behavioral patterns segmented by subscriber type, payment method, day of the week, and geographic location. The data included GMV that is user paid amount, payment method, geographic location, revenue erosion, marketing burn, subscriber type, customer code, and day of the week.

Document Type

Restricted Access

Document Name for Citation

Experiential Learning Project

Notes

none.

Download

Available for download on Sunday, June 16, 2030

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