The Challenge
V Shred is one of the largest digital fitness brands in the U.S., selling workout programs, supplements, and coaching packages through aggressive direct-response advertising across Meta, Google, YouTube, and more. They were spending tens of millions per year on paid acquisition across multiple funnels — each with its own checkout flow, product mix, and revenue model.
The problem was visibility. Customer data lived in silos across ad platforms, e-commerce systems, subscription billing, and CRM tools. The same person could buy a supplement through one funnel, sign up for coaching through another, and show up as two completely different customers. There was no way to connect those identities, which meant no way to calculate what a customer was actually worth.
Without accurate lifetime value data, the marketing team was optimizing spend based on front-end metrics — cost per acquisition and first-purchase ROAS — while blind to which channels and funnels were producing customers that stuck around and bought more. At their ad spend levels, even small misallocations meant millions in wasted budget.
The Solution
We built a unified data platform on Snowflake that pulled every source system into a single warehouse, resolved customer identities across all of them, and surfaced the LTV insights the marketing team needed to allocate spend with precision.
What we delivered:
- Identity stitching engine using RudderStack to resolve millions of customer records across ad platforms, checkout systems, subscription billing, and CRM — creating one canonical profile per person regardless of how many funnels they touched
- LTV models by cohort, funnel, and product so the marketing team could see not just what a customer paid today, but what they'd be worth over 30, 60, and 90+ days by acquisition source
- Automated data pipelines via Fivetran pulling from every ad platform, payment processor, and operational system into Snowflake on a daily cadence
- Attribution modeling connecting ad clicks to downstream purchases across multiple checkout flows and product lines, closing the gap between spend and revenue
- Spend optimization dashboards showing funnel-level profitability, blended and channel-specific ROAS, and customer acquisition cost by segment
- Data stack consolidation replacing a patchwork of manual exports and disconnected tools with a governed, automated warehouse that the entire organization could trust
The Results
- Millions of customer records resolved into unified profiles, giving the team a true picture of customer behavior across every touchpoint for the first time
- LTV questions that used to take a full day of manual analysis could be answered in hours from a single dashboard
- Marketing team shifted budget from high-volume, low-LTV channels to acquisition sources that produced customers with higher repeat purchase rates and longer retention
- Attribution gaps closed — orders that previously couldn't be traced back to a campaign were now connected to their original ad source
- Data infrastructure went from fragile manual processes to automated, daily-refreshed pipelines the business could rely on without engineering support
- The unified data platform became the foundation for every strategic decision around ad spend, product launches, and customer segmentation