How Seasonal Trends Affect Ecommerce Traffic

Every November, the timeline of value capture in ecommerce shifts dramatically. The lag between when you spend and when you see the return changes week by week, and if you’re not adjusting your targets to match that, your performance will suffer. We looked at total value capture across attribution windows (1-day click, 7-day click, and 28-day click) for the average brand during four key periods: standard distribution, pre-Black Friday, BFCM weekend, and Cyber Monday to help our brands set appropriate targets and bids. Under normal conditions, about 85% of attributed value is captured within 7 days and the remaining 15% trickles in over 28 days. That’s your baseline delay between ad spend and realized revenue. But in the two weeks before Black Friday, that lag stretches. We see a 47% increase in delayed (28-day) value, meaning a lot more people see your ads, wait, and buy later. This is the longest lag period of the year. If you hold to short-window ROAS goals here, you’ll cut off future conversions before they arrive. Then as we hit BFCM weekend, value capture returns to roughly baseline levels, fast enough that 7-day goals make sense again. By Cyber Monday, it swings the other way. The lag collapses and 28-day contribution drops by 33%, meaning purchases happen now. What this means is that your targets should move with time. Even drawing a distinction between Friday and Monday is important. Early November requires looser efficiency goals and longer payback expectations. BFCM weekend is the time to hold baseline targets. By Cyber Monday, it’s time to tighten your efficiency guardrails. The same dollars you spent in early November might look inefficient on day 7 but outperform by day 28. Reacting too early cuts spend that would have driven your best long-term results. November is the month when the clock on ad performance breaks. Adjust your expectations by week, not just by channel or campaign, and you’ll stay in sync with reality.

Some of the highest leverage impact in data science and marketing this time of year comes from properly handling seasonality. To see why this matters, U.S. e-commerce retail sales are typically 25–35% higher in Q4, reflecting dramatically different customer behavior patterns. But traditional marketing models like synthetic controls, aren't always equipped or trained on the right data to capture this. Even with perfect pre-fit, they can show substantial bias. 𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐡𝐚𝐩𝐩𝐞𝐧𝐬: 𝐬𝐲𝐧𝐭𝐡 𝐢𝐬 𝐮𝐬𝐮𝐚𝐥𝐥𝐲 𝐧𝐨𝐭 𝐩𝐫𝐨𝐩𝐞𝐫𝐥𝐲 𝐭𝐫𝐚𝐢𝐧𝐞𝐝 𝐨𝐧 𝐬𝐞𝐚𝐬𝐨𝐧𝐚𝐥𝐢𝐭𝐲 Synth learns control units weights by matching the pre-treatment path of the treated; if seasonality (e.g., holiday demand) is absent or weak pre-launch, it picks controls that match business-as-usual patterns but not the treated market’s holiday sensitivity. 𝐓𝐡𝐞 𝐩𝐥𝐨𝐭: 𝐧𝐨 𝐫𝐞𝐚𝐥 𝐞𝐟𝐟𝐞𝐜𝐭, 𝐛𝐮𝐭 𝐚 𝐬𝐭𝐚𝐭-𝐬𝐢𝐠 𝐢𝐦𝐩𝐚𝐜𝐭 For this plot, I generated treated and control data with a similar 'business-as-usual' growth trend. Treated units, however, are more sensitive to holiday demand. It's common practice to treat only a small number of potentially unrepresentative markets, making this a highly plausible scenario. Most importantly, there is zero treatment effect. But a synthetic control model shows stat-sig impact. 𝐓𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞: 𝐝𝐚𝐭𝐚-𝐚𝐝𝐚𝐩𝐭𝐢𝐯𝐞 𝐫𝐨𝐛𝐮𝐬𝐭 𝐦𝐞𝐭𝐡𝐨𝐝𝐬 So what should we do to make smarter marketing decisions? 1. Use a longer horizon (at least one full year). 2. Adopt data-adaptive methods that weight more similar periods (e.g., prior-year holidays). Ping us at Causara if you want to chat about causal inference for marketing.

Now that the dust has settled on holiday, how did 2025 actually pan out? Short answer: Bigger... Faster... More ai driven than most expected... A few stats that stood out from Adobe's post-season data : - $257.8B spent online from Nov 1 to Dec 31. Up 6.8% YoY. A new e-commerce record. - 25 separate days cleared $4B+ in spend. Up from 18 days last year. Demand was more sustained, not just spiky. - Mobile drove 56.4% of all online transactions. On Christmas Day, mobile hit 66.5%. - Cyber Week delivered $44.2B. Black Friday outgrew Cyber Monday, a sign that deal timing keeps shifting earlier. - Generative AI traffic to retail sites jumped 693% YoY. Still early, but the behavior change is real. - BNPL crossed $20B in spend, with over 80% of BNPL purchases happening on mobile. - Shoppers traded up. Sales of higher-priced items rose 20% vs the rest of the year, especially in electronics and appliances. - Social and influencer channels meaningfully gained share, with social revenue share up 40% YoY. My takeaway... - AI is moving from novelty to shopping utility. - Mobile is the primary commerce surface, full stop. - Payments, discovery, and fulfillment flexibility are now baseline expectations. - Retailers that invested early in experience, performance, and data leverage clearly benefited. 2026 planning should assume this behavior sticks. The question now isn’t if these shifts matter. It’s whether your stack and teams are ready to capitalize on them. #Retail #Ecommerce #DigitalCommerce #HolidayShopping #RetailTrends #AICommerce #MobileCommerce #RetailLeadership

Early holiday shopping doesn't kill Cyber Five momentum. Translation: October shoppers = December converters. 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗺𝗲𝗮𝗻𝘀 𝗳𝗼𝗿 𝗲𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲 𝗯𝗿𝗮𝗻𝗱 𝗲𝗻𝘁𝗿𝗲𝗽𝗿𝗲𝗻𝗲𝘂𝗿𝘀: → 27% start shopping in October (not waiting for Black Friday) → 39% increased purchases due to tariff fears → 47% discover gifts through social media recommendations → 38% self-gift during traditional "gift-giving" events 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗶𝗻𝘀𝗶𝗴𝗵𝘁? We're treating early shopping and Cyber Five as competing forces when they're actually complementary revenue streams. Early October campaigns build brand awareness and fill consideration sets. Cyber Five converts that awareness into transactions. The brands winning this season understand the psychology: consumers want to feel smart about timing AND rewarded for urgency. 𝗦𝗺𝗮𝗿𝘁 𝗺𝗼𝘃𝗲: Layer your strategy instead of choosing sides. Pre-holiday campaigns should focus on discovery and education. Cyber Five campaigns should focus on conversion and scarcity. 𝗕𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: Cyber Five remains the conversion champion, but October through November builds the foundation that makes those conversions possible. The question isn't whether to focus on early shopping OR Cyber Five. It's how to connect them strategically. What's your experience with early holiday campaign performance versus Cyber Five results? 𝗣.𝗦. The data shows 4.3% growth for Cyber Five versus 1.2% for the overall season - the concentrated shopping days still deliver disproportionate results.

If you’re scaling newsletter growth in Nov/Dec, BE CAREFUL. Here’s a breakdown of 2024 CPL data and what your next 8 weeks will look like: These are four of our high-spending newsletter clients from Q4 2024. Different budgets and audiences, but the same pattern: • October to Early November: stable CPLs • Black Friday to mid-December: CPLs spike 20–50% • Post-Christmas: CPLs drop back down November is the most expensive time of the year to acquire newsletter subscribers. You’re competing with every e-commerce brand pouring millions into ads to hit their holiday sales goals. Their conversion rates GO UP in Q4 - every website visitor is worth more. But your subscribers aren’t magically worth more in November than they were in October. So your unit economics get worse. This DOES NOT mean you should kill all your ad spend. Here’s how I’d use Q4 instead: 1. Pull back your spend Go from scaling to learning. Scaling = maximizing volume at a known efficiency Testing = discovering new creative angles that’ll win when CPMs drop again So in Q4, reduce budgets by 20–50%. Keep enough spending to: • Keep your pixel data fresh • Gather statistically valid results • Maintain delivery for new ad concepts 2. Hunt for “relative winners” inside higher costs Track: • Click-through rate (CTR) • Landing page conversion rate • Cost per qualified subscriber Even if your overall CPL goes up 30%, your best ads may only go up 10%. They’ll have abnormally high CTRs and landing page conversion rates that ‘cancel out’ part of their high CPMs. Those are your relative winners. Come January, CPLs will drop off a cliff. And you’ll be ready with creatives that are ready to crush. 3. Double down on creative testing This is your R&D season. Try new formats that we’re seeing work right now: • Podcast ads • Instagram story mock-ups • Mock-ups of DMs on IG/Twitter 4. Scale after Christmas The best CPL window of the entire year starts from Dec 26 to the end of Jan. Here’s why: • E-commerce advertisers go dark after the holidays • CPMs crash • You have ready-to-go winners tested during Q4 That’s when you scale aggressively, and you’ll often see 20–40% cheaper subscribers without sacrificing quality. Here’s a real example: One of our newsletter clients (1M+ subs) saw CPLs rise ~20% during November and December. But we didn’t panic. Instead, we focused on ad quality, improving CTRs by 50%. When CPMs fell in January, those same creatives became their lowest-cost, highest-quality ads of the year. Two of them are still running today, 13 months later. My team works with the world's largest newsletters. We: 1/ Scale your growth with readers who buy from you and your sponsors 2/ Have an 80% win-rate when going head-to-head against other agencies in an ad account (that is very, very high) Q4 is a great time to pull back spend and make 2 agencies fight it out for you. Give yourself the gift of making more money in 2026… link to chat with me in the comments!

Your Black Friday discount doesn't matter if your listing crashes when traffic spikes. Every year I watch sellers argue about discount depth while their entire Amazon operation collapses under peak traffic. Your competitors are running similar deals. The real difference is whether your Amazon infrastructure can handle the surge without breaking. I've analyzed hundreds of brands through BFCM cycles at MAG managing $1.2Bn in GMV. The pattern is consistent every year. Brands lose massive revenue for reasons that have nothing to do with their discount depth. Listings crawl under peak mobile traffic. Buy Box suppresses mid-morning because account health metrics tanked. PPC campaigns burn through daily budget before most shoppers even start buying. Backend keywords lose indexing under heavy catalog pressure. Black Friday through Cyber Monday puts more stress on Amazon systems than any other period of the year. If your setup isn't stable now, the traffic spike exposes every weak point. This week is your last window to fix the fundamentals. Verify your account health is pristine before complaint volume spikes. Confirm your PPC automation can scale without burning budget too early. Test that your top keywords are actually indexed because what ranks today might not rank Friday. Lock in your FBA restock plan because receiving delays spike hard during peak season. The sellers capturing market share during BFCM aren't debating coupon depth. They're stress testing infrastructure that converts traffic without breaking. What loads fast on your desktop now will crawl on mobile under peak traffic. What converts at current costs won't convert when bids jump and your budget caps out early. The window for technical preparation is closing fast. Test every critical piece of your Amazon operation this week or watch competitors take market share with the same discount you're running.

I was recently asked by a brand we work with why they do best during the summer. The answer isn’t as obvious as you'd think. We have a brand that has its peak season during the summer, which is often the worst time for most ecommerce brands. It’s not a summer-specific product, and the secret to their summer success lies in the cost of advertising inventory. For most brands, conversion rates fluctuate based on the time of year. For example, a brand might average a 3% conversion rate throughout the year, drop to 1.5% during the summer (a 0.5 coefficient), and spike to 6% during the holidays (a 2x coefficient). These ups and downs are common and expected in ecommerce. This particular brand maintains approximately the same conversion rate year-round. During the summer, ad inventory is significantly cheaper compared to Q4. While most brands see a dip in conversions due to seasonal shopping behaviors, this brand leverages the lower ad costs to grow its sales. It's crucial to understand how your brand's conversion rate fluctuates throughout the year. By analyzing these patterns, you can identify opportunities to optimize your ad spend and maximize sales during periods when others might be struggling.

It's that time of year again... Before the peak shopping period we have one huge retail event coming up - ‘Back to School’. Here are the biggest back-to-school trends according to Deloitte, Sensormatic, Ankura, and National Retail Federation, and my take on what this means for retail and eCommerce brands. 🎒 Amongst parent back-to-school (BTS) shoppers, 61% agree that their children influence them to spend more. ↪ Targeting parents isn’t enough. eCom businesses are also targeting Gen Alpha and Gen Z with age-appropriate marketing strategies. 🎒 86% of consumers still have at least half of their back-to-school purchases left to complete at the end of August. ↪ 50% of parents also shop for themselves whilst shopping for their children in this time period. These parents are likely to spend 1.4x more than those who don’t. 🎒 For 84% of BTS shoppers, price is the no. 1 factor in influencing shoppers where to buy. 67% will shift to a cheaper brand if the preferred brand is more expensive. ↪ Based on the above, price sensitivity is important. With so many small items to purchase, a strong brand won’t always prevent someone from choosing a cheaper product elsewhere. 🎒 September 1st isn’t the last day of back-to-school season. Far from it. There are purchases made within this category further in to the year which gives eCom businesses plenty of time to leverage the back-to-school event to target shoppers. Back-to-school is sometimes like the final dress rehearsal before the upcoming peak shopping season for many eCommerce businesses. Now is the time to make it count and test new strategies. #ecommerce

👀 Q3 2024: INDUSTRY TRENDS & INSIGHTS Q3 is a crucial period for #ecommerce brands, fueled by events like Prime Day, back-to-school shopping, and early holiday promotions. This year, our Q3 industry report highlighted a clear trend: Customers continue to seek lower prices, while brands face challenges in maximizing the effectiveness of their retail media investments. But despite increasing inventory and advertising costs in Q3, sales growth remained strong. 💪 Here are my takeaways from our Q3 report: 📈 Cross-category sales growth: Brands experienced strong YoY growth across categories, largely driven by seasonal demand and tentpole events like Prime Day. 📦 Rising inventory costs: Increasing cost of goods sold (COGS) is squeezing margins, even with stable pricing. ⬇️ Declining advertising impact: Increased ad spending boosted visibility, but ROAS declined with steady CPCs–indicating mix shift to lower ASP items. ✔️ Improved operational efficiency: Record-high fill rates and optimized supply chains are improving operational efficiency to meet demand for anticipated seasonal spikes and events. 💡 Category insights: Health & Personal Care, Grocery & Pet Products maintained stable pricing, with consumer shifts toward cost-effective products. Want the full story and deeper insights from your category? Download the full report now: https://hubs.li/Q02WQgnx0

25% 𝗼𝗳 𝗲𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝗶𝗻 𝗡𝗼𝘃 𝗮𝗻𝗱 𝗗𝗲𝗰. 𝗦𝗲𝗿𝗶𝗼𝘂𝘀𝗹𝘆. Shoppers may browse early, but they spend late. Everyone talks about holiday shopping creeping earlier, but the numbers tell a different story. In 2024, nearly a quarter of all ecommerce revenue happened in just two months: November and December. So what actually works? 1. Messages perform better during BFCM, with more revenue per send. 2. Discounts drive conversions, but only when tailored to AOV. 3. Early shoppers often pay more than those who wait. The best brands hold back. They tease, test, and save their strongest offers for peak season. And when it's time to discount, they do it strategically: → Low-AOV folks converted at around 33% off → High-AOV folks only needed about 15% off The takeaway? Tier your offers. Protect your margins. Match the buyer, not the calendar. Personalization by AOV, purchase history, and intent isn't just smart. It's necessary. November and December is the main event. Plan like it. Drop me a DM. I’ll show you how the best brands are doing it.