PacSun Combines Intelligent Data Onboarding and Modeling with Universal Data Activation
“Reactor provides near real-time centralized customer insights which can help PacSun marketing and operations create better customer experience. Reactor has been key to PacSun unlocking value from our data.”
The company
- Company profile
- $900M
- Industry
- Fashion Apparel
- Website
- pacsun.com
Data stack
- Pipeline & Transformation
- Reactor
- Destination
- GCP BigQuery
- Data Sources
- Salesforce Commerce Cloud (SFCC), LiveRamp, Merkle, GA4, Manhattan Active Omni, Gladly, Cordial, Yotpo, Dynamic Yield, Meta, TikTok
- Business Intelligence
- Sigma
Overview
PacSun relies on the intelligent data pipeline, Reactor, to better understand and serve their customers by unifying and modeling data for advanced, real-time decision making across marketing, merchandising and operations. Reactor extracts disparate marketing and operations event data and unifies, defines, and transforms that data to helping them balance compelling customer experiences with contribution profits and customer lifetime value (CLV).
Challenge
PacSun is dedicated to delivering an exclusive collection of the most relevant brands and styles to a community of inspired youth. They need to collect customer profile and event data for their various brands in real-time and unify it with data sets across marketing, merchandising, customer experience and finance. PacSun needed unified data and advanced data models to inform better retail decisions, improve shopper experiences and increase customer lifetime profits. Brands often lean on marketing tools like Customer Data Platforms to drive customer experience, while key operations data like shipping costs or available inventory remains siloed, causing retailers to lose profit on sales.
Solution
Reactor creates business-ready data from all of PacSun’s systems and applications and lands it in GCP BigQuery. PacSun’s marketing and customer teams now have the ability to fully transform, govern, and activate data through campaign automation to better engage and serve PacSun customers.
Impact
What changed for PacSun.
Shopper Profiles
21.6M Shopper Profiles
Customer Lifetime Value
11% CLV Increase (YoY)
Customer Acquisition Cost
-9.5% Reduction in CAC (YoY)
Repeat Purchaser
15% Repeat Purchaser CLV Increase (YoY)
PacSun use cases
How they put Reactor to work.
- 01
Support dynamic customer attributes including marketing engagement across paid, social, email and messaging campaigns
- 02
Profile and segment named and anonymous shoppers and build awareness of complex subscription membership and loyalty programs
- 03
Align customer profiles and segments with post-conversion retail considerations including merchandising calendar and discount promotions, cancellations and returns, order and shipment routing, fulfillment and shipping latency, inventory availability by location, and variable costs of doorstep delivery
- 04
Track shopper behavior and value across omnichannel operations
- 05
Drive digital marketing campaigns to shopper segment profitability targets
- 06
Optimize assortment, promotions, and fulfillment for customer engagement and CLV
- 07
Increase CLV with insights into complex membership and subscription programs
- 08
Optimize customer engagement and retention programs for profitability
- 09
Analyze operational root cause drivers and detractors of shopper lifetime value
- 10
Push customer profile and segment data to downstream applications
- 11
Leapfrog slow and expensive data warehouse buildout projects
