Powering Target’s DriveUp
How Scalable Data Engineering Turned a Pilot Program into a Core Fulfillment Channel
Problem Statement
Target launched a new fulfillment method called Drive Up, allowing guests to stay in their vehicles while team members delivered online orders directly to their car. This innovation enhanced convenience and reduced friction in the pickup process.
To ensure the long-term success of Drive Up, Target needed visibility into how guests were engaging with the feature and how it influenced metrics like revenue, wait time, and lifetime value (LTV).
Situation
With Drive Up rolling out across stores, we needed to turn raw app-level data from both iOS and Android into structured insights. This required ingesting and transforming behavioral and transactional data into a scalable reporting framework within Target’s Hadoop ecosystem.
Once that foundation was in place, we could build dashboards in Domo to track performance metrics—such as total revenue, order volume, and guest wait times—and support continuous experimentation around fulfillment and checkout flows.
Summary
Target built the data infrastructure behind its Drive Up fulfillment program to enable real-time performance tracking and rapid optimization as the service scaled from 50 to over 1,800 stores. By transforming raw app data into a centralized reporting platform and supporting A/B testing, the team uncovered key guest behavior insights that helped Drive Up become a high-performing, guest-loved feature with Net Promoter Scores consistently above 90.
Key Results
- Scalable Insights: A Hadoop-based data platform enabled scalable, daily reporting on DriveUp performance across 1,800+ stores.
- Improved Adoption: By addressing guest awareness and optimizing top-of-funnel engagement, we accelerated adoption across markets.
- Outstanding Guest Experience: Thanks to process refinements and consistently fast fulfillment (averaging under 2 minutes), Drive Up achieved 90+ Net Promoter Scores (NPS) and became a core pillar of Target’s retail strategy.
Solution
Data Platform Development
I designed and implemented a daily Oozie workflow in the Hadoop cluster to aggregate and transform app data into analytics-ready tables. This workflow consisted of 14 SQL scripts, each responsible for parsing and calculating key performance indicators across the guest journey.
The resulting data pipelines fed into Domo, enabling the creation of clear, actionable dashboards. These dashboards were reviewed weekly by product, fulfillment, and operations teams to identify areas of friction and opportunities for optimization.
Experimentation and Optimization
To improve conversion and experience, we launched a structured A/B testing plan focused on various parts of the guest experience—particularly around the checkout and fulfillment flows. Early tests revealed drop-off during the consideration phase, where guests showed interest in Drive Up but reverted to home shipping or in-store pickup.
By analyzing top-of-funnel behavior, we uncovered a key friction point: lack of guest awareness. In response, we launched additional in-store messaging and encouraged team members to visibly use the Drive Up service during peak hours to build guest familiarity.
Results
As the Drive Up program expanded from an initial 50-store pilot to over 1,800 locations nationwide, one of the most critical insights emerged around guest awareness. Early reporting and A/B testing showed that adoption was slower than expected. A deeper analysis revealed significant drop-off during the consideration phase—guests would explore the Drive Up option but often abandon it in favor of shipping or in-store pickup, largely due to confusion or uncertainty about how the service worked.
To address this, we introduced targeted in-store messaging and encouraged Team Members to visibly use and demonstrate the service during peak hours, making the experience more tangible and trustworthy for potential users. This increase in visibility, combined with consistently low wait times of two minutes or less, transformed the guest experience. As a result, Drive Up began earning Net Promoter Scores (NPS) above 90 and has since become a signature element of Target’s fulfillment strategy.