Retailers that lock merchandising decisions six months ahead of the holidays risk missing what customers actually want during concentrated shopping windows. Angara, an online jewelry retailer, used just-in-time manufacturing, richer product content and close monitoring of referral traffic to flex production and merchandising through the Cyber 5 — the five-day stretch from Thanksgiving through Cyber Monday — after seeing rapid shifts in buyer preferences during the 2025 peak season.

Why flexibility matters for peak windows

Angara’s CEO Ankur Daga told Digital Commerce 360 that the company’s main lesson from the 2025 holiday season was how quickly customer preferences can change in a compressed period. Traditional jewelers commonly set inventory and assortment months in advance; by the time demand becomes clear, the opportunity to meet it may have passed.

For Angara, that reinforced relying on near-real-time demand signals. Because the company controls its supply chain and manufactures just in time, it avoids large amounts of finished inventory and can shift priorities — for example, increasing production of a particular gemstone, shape or carat size that gains traction during the Cyber 5.

How Angara operationalizes responsiveness

Preparation for peak season, Daga said, isn’t only about finished goods. It includes ensuring manufacturing capacity, technology robustness and redundancy so systems and production can “flex with demand.” Angara reported category patterns during the Cyber 5: a higher share of lab-grown gemstone purchases, more stones above one carat, and increased popularity of shapes such as oval and emerald cuts.

Angara’s operational advantage rests on three linked abilities: fast production changes, clear presentation of choice, and immediate measurement of what resonates. That combination lets the retailer watch which designs and attributes customers respond to and then adapt production and merchandising quickly — rather than pushing lower-quality cost cuts to hit an arbitrary price point.

Merchandising and conversion tactics

To raise conversion and average order value, Angara gives customers structured customization across metals, gemstones, stone quality and the option of natural versus lab-grown stones. The aim is to let shoppers trade up or down based on what matters to them, without degrading perceived quality.

Angara is also investing in richer product pages and educational content to support the extensive research buyers do before purchasing fine jewelry. Daga cited a 500% year-over-year increase in traffic from the retailer’s top three AI referral sources, indicating that AI-driven discovery channels are growing in importance for product discovery.

Industry context: Angara ranks No. 363 in Digital Commerce 360’s Top 1000 Database and No. 192 in the publication’s AI Rankings.

Practical takeaways for retailers

  • Shorten the loop between demand signals and production where feasible. Owning supply-chain steps or tightening vendor relationships reduces lead-time risk during concentrated peaks.
  • Prioritize manufacturing capacity, system redundancy and clear operational ownership so production can pivot quickly when a trend emerges.
  • Design product pages for researched purchases: richer content and education can improve conversion without sacrificing product integrity.
  • Offer structured, well-communicated choice. Customization can increase AOV, but only if options are presented so customers can compare trade-offs quickly.
  • Test AI-driven referral channels before peak season and measure their contribution to discovery and conversion.

Angara’s results reflect its specific business model and category dynamics. Still, the broader lesson for retailers competing in compressed shopping windows is clear: where demand can be observed in near real time, the ability to adapt — across production, merchandising and channels — can be a decisive operational advantage.

Next steps for retail teams: map current lead times, stress-test production and tech redundancy, prioritize product content updates, and run early experiments on AI-driven discovery channels so you can respond to what customers actually choose during the Cyber 5.