Test, Tweak, Triumph: How Data-Driven AB Testing Ignited Business Transformation
Client Overview
The client is a leading global online food ordering and delivery platform with operations spanning over 6,000 cities worldwide. The company offers diverse delivery methods and serves millions of customers through its highly scalable digital platform. Headquartered in the USA, the organization has become a household name, connecting restaurants and consumers with seamless, efficient, fast service. The company is committed to providing superior user experience and improving the efficiency of its internal processes through advanced technological solutions.
The Feature That Fell Short: Challenges in Driving Referral Adoption via In-House App
Feature Adoption vs. User Engagement:
While the referral functionality was successfully deployed, user engagement metrics painted a different picture. Employees weren’t interacting with the feature at the expected frequency, indicating a disconnect between feature availability and actual usage behavior.
Assumptions Without Evidence
The team implemented the referral module based on internal brainstorming and assumptions about user preferences. However, without validating these hypotheses through user behavior analysis or testing, the feature failed to address the end users' real pain points.
Lack of Measurable Impact
Post-deployment metrics showed minimal to no improvement in referral numbers. This raised concerns about whether the module’s placement, flow, or communication strategy was effectively designed to motivate users or fit into their workflow.
Inability to Prioritize Enhancements
Numerous enhancement ideas surfaced to improve the referral flow. However, without a mechanism to test these variations at scale, the team lacked clarity on which solution would actually move the needle, hindering timely optimization.
Cracking the Dilemma: A Data-Led Detour to Smarter Sign-Ins
The team transformed guesswork into guided innovation through a precise combination of EDA, hypothesis formulation, and A/B testing, streamlining the sign-in experience to enhance referral engagement.
Diagnosing the Drop-Off with EDA
An exploratory data analysis (EDA) exercise revealed a critical friction point: nearly 50% of users abandoned the process at the sign-in page. The multi-step login acted as a conversion barrier, halting users from accessing the referral module.
Hypothesis Formation Backed by Behavioral Signals
Stakeholders proposed that simplifying the login journey to a single-touch sign-in, via methods like face recognition, passcode entry, or mobile OTP, could increase user flow to the referral section. This formed the foundation for data-backed experimentation.
Validating with Controlled A/B Testing
The team executed a controlled A/B test to avoid biased implementation. Two identical user groups were created - one was exposed to the new one-touch sign-in, and the other retained the existing process. By isolating this variable, the test precisely measured the real impact on referral activity.
Control Group Funnel & Treatment Group Funnel:
Implementing the enhanced sign-in process demonstrably improved user experience, leading to a statistically significant reduction in sign-in page drop-off rates for the treatment group. This improvement correlated with a higher referral rate, indicating that the enhanced sign-in process positively influenced user engagement and acquisition.
Results Delivered: Transforming User Experience into Tangible Business Gains
Significant Boost in Referral Rates
By identifying and resolving the friction points at the sign-in page, clients achieved a remarkable increase in referral rates. This seamless user experience enhanced customer satisfaction and accelerated hiring processes, enabling positions to be filled 30% faster, closing roles an impressive 30 days ahead of schedule compared to initial plans.
Data-Driven Hypothesis Validation
Clients successfully validated their business hypotheses through a cost-effective, data-backed approach that minimized risk and ensured zero disruption to ongoing operations. This strategic testing empowered them with actionable insights grounded in real user behavior.
Informed Decision-Making with Predictive ROI
Access to predictive analytics on the potential ROI from implementing a one-touch login solution equipped clients with the confidence to make well-informed, strategic decisions. This foresight paved the way for smarter investments and optimized digital transformation initiatives.
About Indium
Indium is an Al-driven digital engineering company that helps enterprises build, scale, and innovate with cutting-edge technology. We specialize in custom solutions, ensuring every engagement is tailored to business needs with a relentless customer-first approach. Our expertise spans Generative Al, Product Engineering, Intelligent Automation, Data & Al, Quality Engineering, and Gaming, delivering high-impact solutions that drive real business impact.
With 5,000+ associates globally, we partner with Fortune 500, Global 2000, and leading technology firms across Financial Services, Healthcare, Manufacturing, Retail, and Technology-driving impact in North America, India, the UK, Singapore, Australia, and Japan to keep businesses ahead in an Al-first world.
