Only 14% of Draco Diamond’s site visitors are repeat users, yet those returning shoppers account for 78% of the retailer’s sales. That imbalance has dictated the brand’s commercial choices: modest, tightly timed discounts; visible competitor pricing; and an early focus on discovery in AI-powered answer engines before adding paid advertising. For marketers handling high-consideration products, Draco’s setup is a compact case study in converting research-driven traffic into durable revenue.

Small, rotating discounts that protect the brand

Rather than broad seasonal sales or headline-grabbing markdowns, Draco runs a curated “Founder Pricing” collection. Every two weeks the brand places four SKUs in the collection, stocks five units of each, and reduces prices by roughly 5%–12%.

That range is intentional. In categories where price communicates value and provenance, deep percentage discounts can undermine credibility—especially for items that already carry high list prices. Draco’s limited reductions aim to nudge deliberative shoppers without creating the skepticism that a large, one-off markdown can trigger.

Pricing transparency to support consideration

Draco lists comparable prices from other merchants on product pages, a move the founder frames as uncommon in jewelry. Publishing competitor prices gives researching shoppers clearer context and reduces the friction of cross-site comparison.

McMartin also says Draco operates on much thinner margins than some traditional jewelers, accepting lower markup to present a clearer, more defensible pricing proposition while remaining profitable.

Start with AEO, add ads later

Draco launched in early 2025 and postponed paid advertising until spring 2026. In the interim the team prioritized answer engine optimization (AEO)—optimizing how agentic AI systems surface product answers and recommendations—so the brand could capture research-stage demand without heavy ad spend.

After establishing organic discovery, Draco introduced ads and reports a consistent return on ad spend above 7%. According to the founder, that sequence created a steady acquisition engine: organic visibility pulled in deliberative shoppers, and paid channels scaled that baseline efficiently.

Practical takeaways for marketers

For teams selling high-ticket or deliberative products, several tactical principles emerge from Draco’s approach:

  • Match discount depth to your brand signal. Modest, time-limited markdowns can convert without damaging perceived value—especially when baseline prices are already substantial.
  • Use scarcity and rotation rather than blanket discounts. Limiting quantities and rotating offers concentrates demand while preserving an upscale image.
  • Make comparison easy. Publishing comparable merchant prices reduces research friction and can improve organic discovery for shoppers cross-referencing options.
  • Prioritize discovery channels for long journeys. For complex purchases, optimizing for answer-engine and AI recommendation placements may be a more efficient first step than immediate heavy paid acquisition.
  • Measure retention economics. If returning visitors drive a disproportionate share of revenue, invest in first-party signals and remarketing to increase lifetime value.

Note: the article’s details rely on the founder’s accounts and internal metrics; independent verification of margins, traffic composition and long-term ROAS was not provided in the source.

How to test this in your business

Marketers who want to experiment with Draco’s levers should run tightly scoped tests: try small, time-limited discounts on a rotating set of SKUs; surface competitor price comparisons on a subset of product pages; and run discovery experiments that prioritize answer-engine placements or content likely to be picked up by agentic AI. Track conversion by cohort (new vs returning), margin impact, and where the purchase decision completed (organic answer placement vs paid channel). That combination of signals will show whether the model scales for your category without degrading brand value.

What to watch next: watch how agentic AI adoption shifts organic traffic composition for high-consideration categories and whether competitors adopt low-percentage markdowns at scale—because if they do, the trade-off between discounting and perceived value will become a broader category test rather than a single-brand tactic.