Overview

The Lowe’s Customer Journey Analytics POC successfully unified Adobe Analytics, store, and classification data into a single cross-channel analytical environment and used that foundation to evaluate two high-priority omnichannel use cases. For Buy Online, Pick Up In Store & Product Return follow-on activity, the team built fulfillment-window analysis, BOPIS identification logic, and segmentation to examine follow-on store behavior, demonstrating that BOPIS orders create a meaningful short-term opportunity for additional purchases while also documenting data gaps around explicit pickup events and accurate return timestamps. For Effectiveness of Buying Guides & Estimator Tools Across Channels, the team established the data model, derived dimensions, and attribution framework needed to connect guide and calculator interactions to digital and in-store conversion, revenue, and time-to-purchase outcomes. Overall, the POC validated both the technical feasibility of Lowe’s cross-channel data unification in CJA and the business value of using that data for merchandising, conversion, and activation decisions.

• Unified digital + store data to track full journey from online order → pickup/return → post-event behavior • Built fulfillment-window analysis (0–2 days) using derived fields and segmentation to isolate pickup impact • Identified incremental in-store purchase behavior post-BOPIS, confirming near-term cross-sell opportunity • Leveraged proxy pickup signal (“I’m here” event) due to missing POS pickup event tracking • Presented attachment opportunity with additional in-store sales of certain categories such as extension cords with trim-a-tree BOPIS orders.

• Established framework to connect guide/tool engagement → cross-channel purchases • Created derived dimensions for guide/calculator usage, enabling granular analysis in CJA • Measured conversion impact across channels (orders, revenue, time-to-purchase) • Applied attribution models to quantify influence of guides on downstream purchase behavior • Demonstrated how those that view refrigerator buying guides have higher Average Order Value (AOV) in the purchase of refrigerators than those that do not view the buying guide and purchase refrigerators

POC confirmed that unified cross-channel data in CJA enables actionable insights for both fulfillment behavior and digital content influence on conversion across digital and store journeys, while surfacing specific data enhancements needed for production scale. • Joined digital and store data using common Identifier • Use cases successfully validated using real Lowe’s data with actionable insights • Complex cross-channel customer journeys analyzed with no code or further Engineering support • Overcame data gaps with dynamic and flexible data solutions • Set clear path to production with enhanced event signals and extended activation use cases