Contents
- Most DTC brands at the $500K--$5M revenue stage know their total revenue.
- This structure runs on Konnektive CRM with custom reporting exports.
- When AFF-01 traffic dropped after February 2024, the attribution system showed exactly which products were affected, the revenue impact by month, and how refund dynamics shifted during the decline.
You set up real-time marketing attribution for DTC by building a structured data layer that tracks every dollar from traffic source to product to transaction type, across time -- then making that data accessible to the person making spend decisions without intermediaries.
What Real Attribution Actually Looks Like
Most DTC brands at the $500K--$5M revenue stage know their total revenue. Some know it by product. Very few can answer: "What is my refund rate on product X from affiliate Y in month Z, split by initial versus rebill?" That level of granularity is the difference between managing a business and guessing at one.
According to a 2024 Rockerbox study, only 18% of DTC brands have attribution systems that track beyond last-click at the channel level. The rest rely on platform-reported ROAS from Meta or Google, which double-counts conversions and provides no cross-channel view.
At Stealth Labz, Michael George Keating built a revenue attribution system that produces 15 structured data exports across 7 attribution dimensions: product, affiliate, campaign, time (monthly across 28 months), transaction type (initial/rebill/refund), currency (USD and ZAR), and payout. The system tracks $1.08M in gross revenue across 38 products, 14 affiliate sources, and 38+ campaigns. Every dollar is traceable from the traffic source that generated it to the product it purchased to the month it occurred in.
The Seven Dimensions
| Dimension | What It Tracks | Why It Matters |
|---|---|---|
| Product | 38 product families, 100+ SKU variants | Revenue by SKU, not just by brand |
| Affiliate | 14 tracked source IDs | Know which traffic sources are profitable |
| Campaign | 38+ funnels | Attribute revenue to the specific funnel that converted |
| Time | Monthly, 28 months | Trend analysis, seasonality, cohort tracking |
| Transaction type | Initial, rebill, refund | Understand the quality of revenue, not just volume |
| Currency | ZAR and USD | Multi-geography operations tracked separately |
| Payout | Per offer, per source | True cost of traffic by source and product |
This structure runs on Konnektive CRM with custom reporting exports. The 15 structured views are repeatable queries against the production transaction database -- not one-time extracts. New months, new products, and new affiliates flow into the same attribution structure automatically.
What This Changes in Practice
When AFF-01 traffic dropped after February 2024, the attribution system showed exactly which products were affected, the revenue impact by month, and how refund dynamics shifted during the decline. When PRD-03 broke out to $101K net in five months starting August 2025, the system tracked which affiliates drove the volume and what the rebill/refund splits looked like at each stage.
The implementation path: start with server-side tracking (pixels and S2S postbacks). Connect your CRM as the source of truth for transaction data. Build structured exports by product, source, and time. Layer in initial/rebill/refund splits. The infrastructure cost is minimal compared to the decision quality it produces.
Related: What KPIs Matter Most for DTC Performance Marketing?
References
- Rockerbox (2024). "State of DTC Attribution." Multi-touch attribution adoption across DTC brands.
- Keating, M.G. (2026). "Case Study: The Revenue Attribution System." Stealth Labz. Read case study
- Keating, M.G. (2026). "The Compounding Execution Method: Complete Technical Documentation." Stealth Labz. Browse papers