Solutions
What Is Violet
Violet Attribution
Product
Violet Analytics
Violet Advanced Attribution
Violet Conversions
Violet Advisory
Use Cases
By Industry
Digital Fundraising
Fintech
Healthcare
iGaming
Multilocation Services
Nonprofit Membership
Omnichannel Retail
By Business Model
DemandGen
Subscription
Transaction
Plans
Resources
Playbooks
Growth Academy
Case Studies
White Papers
Exactius
exacti.us
Who We Are
We're Hiring
All Dots Connected
What is Violet
Violet Attribution
Solutions
Use Cases
Plans
Resources
Exactius
Log In
Let’s talk
Solutions
What is Violet
Violet Attribution
Violet Conversions
Violet Advisory
Use Cases
By Industry
Digital Fundraising
Fintech
Healthcare
iGaming
Multilocation Services
Nonprofit Membership
Omnichannel Retail
By Business Model
DemandGen
Subscription
Transaction
Resources
Playbooks
Growth Academy
Case Studies
White Papers
Exactius
exacti.us
Who We Are
We're Hiring
All Dots Connected
Exactius LLC.
© All rights reserved, 2024.
Connect with our Senior Advisory Team
Let’s talk
Case Studies
Transactional
B2C
Fashion
High Ticket
Amazon
Finding Efficiency to Expand Digital Investment for Omni-Channel Retailer: Increase Variable Contribution Margin by $14 Million in first 9 Months
Problem Overview
Company Profile
Industry & Footprint
: Leading fashion brand operating across multiple locations in the U.S.
Business Type
: B2C (Business-to-Consumer)
Engagement Channels
: Retail locations, Email, SMS, Phone, and Online
Transaction Size
: $50 to $500 per transaction
Geographical Scope
: Specific locations in the U.S. and key international cities
Inefficient Budget Allocation
Prior-year investment mix was unclear; team needed to determine optimal daily spend per channel.
Sought to balance spending efficiency with key brand objectives (e.g., Women’s Lifestyle).
How to decide investment mix between D2C channels and other channels (like Amazon)
Business Problem
Need for Real-Time Performance Visibility
Struggled to track performance across all platforms, channels, and campaigns in real-time (LC + MTA).
Required optimization down to the fully loaded margin (FLM) at the campaign level.
Segmentation of New vs. Existing Buyers
Needed separate planning and reporting to accurately map activity drivers for each group.
Saw an opportunity to increase activity among existing buyers and better target new customers.
Complexity of Measurement & Reporting
Required Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM) to accurately tie outcomes to investments.
Operational issues (e.g., QA concerns, brand mishaps) lowered confidence in data and performance.
Deployed Solutions:
Comprehensive Data Platform
Real-Time Tracking
: Implemented real-time monitoring for all platforms, channels, and campaigns (LC + MTA).
FLM Optimization
: Enabled day-to-day adjustments in spending based on fully loaded margin data.
Marketing Mix Modeling (MMM) & Multi-Touch Attribution (MTA)
First-Ever MMM
: Conducted 3,000 model iterations with 94% accuracy, incorporating category-level data.
Live MTA Model
: Provided more precise budget allocation insights, especially for top-of-funnel investments.
Differentiated Strategy for New vs. Existing Buyers
Activity Mapping
: Identified unique conversion and engagement drivers for new vs. existing customers.
Improved Engagement
: Focused on boosting activity among existing customers while scaling new customer acquisition.
Key Results & Outcomes
Significant YoY Growth
$13.9M YoY increase in Fully Loaded Variable Contribution Margin over 9 months.