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Optimization

Seasonal Optimization with Eevy AI

10 min read

Customer behavior changes dramatically during peak shopping seasons. Black Friday shoppers are more deal-focused and browse faster. Holiday shoppers are more gift-oriented and value social proof about product quality for recipients. Summer shoppers may browse more leisurely. Your review sections need to adapt.

This guide covers how the genetic algorithm handles seasonal shifts, what you should do before peak periods, and how to maximize performance during high-traffic events.

How the Algorithm Adapts to Seasonal Traffic

The genetic algorithm continuously adjusts based on current visitor behavior, which naturally shifts with seasons. During high-traffic periods like Black Friday, generations complete faster (more data per unit of time), which means the algorithm can evolve more quickly. It may surface different winning layouts during peak periods — for example, a concise review carousel that loads fast and conveys trust quickly might outperform a detailed review grid during Black Friday, when shoppers are in a hurry.

Pre-Season Preparation

Two to four weeks before a major shopping event: 1. Ensure review collection is running — fresh reviews during the season signal an active, popular store. 2. Check section placement — make sure review sections are visible above the fold on product pages (especially mobile). 3. Add a review summary section if you do not have one — quick-scan social proof is critical when shoppers are browsing fast. 4. Consider adding a highlighted review to your homepage. 5. Do not reset the algorithm right before a peak period — let it carry its existing learnings into the season.

During Peak Periods: What to Monitor

During Black Friday, Cyber Monday, or holiday peaks, check your dashboard daily: RPV trend — is it rising with increased traffic? Section load times — high traffic can slow third-party scripts; Eevy AI sections are served from a CDN but monitor anyway. Generation progress — generations may complete in 1-2 days during peak traffic. New reviews — if review collection is active, you may see a surge in new reviews that the algorithm can leverage immediately.

Post-Season Analysis

After a peak period, review your seasonal data: compare RPV during the event to your baseline. The genetic algorithm likely found different optimal layouts during the peak — review what they were. If a layout performed exceptionally well during Black Friday, note its configuration for next year's preparation. Also check if any new reviews collected during the peak are particularly compelling — these might be worth featuring as highlighted reviews.

Year-Round Seasonal Awareness

Seasonality is not just about Black Friday. Consider: Back-to-school (August-September), Valentine's Day, Mother's/Father's Day, and any category-specific seasons (swimwear in spring, coats in fall). The genetic algorithm handles these transitions automatically, but you can help by ensuring relevant reviews are available. If you sell seasonal products, make sure those products have reviews before their peak season begins.

Wrapping Up

The beauty of genetic optimization is that it adapts to seasonal shifts without manual intervention. Your role is to prepare (ensure sections are in place, reviews are flowing, and the algorithm has had time to learn) and then let the system do its work. After each season, review the data to refine your strategy for next time.

Ready to optimize your social proof?

Install Eevy AI, import your reviews, and let the genetic algorithm find the layouts that convert best for your store.

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