We took a hypothetical US fashion DTC store on Shopify with 100,000 monthly visitors and modeled two email strategies through BFCM. Everything below is a model built on public benchmarks plus our own capture data, not client results, and the assumptions are listed so you can swap in your own numbers.
Strategy one runs a well-built gamified popup from mid-July, converts 9% of the visitors who see it, gives new subscribers a 10% code, warms them with flows, and sends the list a 25% offer during BFCM week. Strategy two runs a basic signup form over the same period, converts 3%, gives the same 10% code, and compensates at BFCM with a 50% offer.
Shared assumptions. 70,000 visitors see the popup monthly after subscriber hiding and frequency caps, AOV is $100, the welcome flow converts 5% of signups before BFCM, 15% of the list churns by late November, and the BFCM campaign converts 3% of the reachable list at 25% off against 5% at 50% off, since deeper offers do pull more redemptions. Repeat purchases and retargeting audiences are ignored, both favor the bigger list, so this is the conservative version of the gap.
Strategy one collects 25,200 emails by BFCM. The welcome flow produces 1,260 first orders at $90 net, which is $113,400 before the sale starts, and the 25% campaign converts 643 of the 21,420 still-reachable addresses at $75 net for another $48,200. Total around $161,600. Strategy two collects 8,400 emails, gets $37,800 from the welcome flow and $17,850 from the 50% offer, and lands around $55,700.
Same traffic, 2.9x revenue gap. Per reachable subscriber during BFCM week the deep discount actually wins, $2.50 against $2.25, because the higher redemption slightly outruns the margin loss. The entire gap comes from list size, which was decided back in July by the capture setup. The discount depth debate that dominates BFCM planning moves the result by cents per subscriber, while the capture rate moves it by a factor of three.
The model has obvious limits. The 5% welcome conversion and the 3% campaign conversion are the assumptions doing the heaviest lifting, and weaker flows narrow the gap. A 9% capture rate is not a given either, in our data it sits between the top 10% and top 3% of ecommerce campaigns, though gamified setups with a working frequency cap reach it regularly. Run the same arithmetic with your own numbers before quoting ours.
If anyone has real cohort data comparing summer-captured and November-captured subscribers through BFCM, that is the part no model replaces.