This is the biggest Black Friday SOP we've ever built. Everything we learned last Black Friday is in it. So are all the SOPs we run the agency on. One doc. It works for any niche and any revenue level. If you run Google Ads for an ecom store, this is your playbook from now until January. Every client we manage already has it. Now it's your turn. What's inside: 📅 Key dates, who does what, and why you start in October, not November 📈 How fast to raise budgets. Phase 1, phase 2, the days before BF and the peak days 🎯 What to do with your target ROAS on BF weekend. Which move to pick, and when to go back to normal 🚫 Why we never use Seasonality Adjustments for BFCM 💸 Why the highest ROAS is the wrong goal on BF, and how to find the profit sweet spot 🛒 Feed and Merchant Center prep. Sale prices, promotions, and what you must NOT touch 🏷️ Which offers actually work. Margin floor first, then the offer type. Real examples inside ⚙️ The backend checklist. Supplier, payments, chargebacks, cash, support, email flows, tracking 🔥 BF weekend live. What we watch every hour, when we act, when we keep our hands off 🎄 After BF. Cyber Monday to Christmas, shipping cutoffs, January Nothing is held back. It's the exact process our team runs for our clients. How to get it: 1️⃣ Be a Premium member 2️⃣ Leave a review for the Lab. Takes 30 seconds. Already left one? Skip this step. 3️⃣ Comment "BF" below We'll send it to you. Reviews go here: https://www.skool.com/google-ads-ecom/about Phase 1 of the budget ramp starts mid-October. Stores that win Black Friday are set up weeks before it. Don't start on 20 November. Let's make this the best Q4 yet 🚀

New resource for premium members! Q4 is where your year gets made or lost. Most stores work that out in November. Too late. So we stopped guessing and built the season. Two full books. 👇 📊 What sits behind it - +200 of our own client accounts. Fashion and Home Decor - 7 months of real shopping data per account. August through February. The actual AW season, not a forecast. - +100 accounts in a fixed year over year cohort, so we can prove a peak repeated instead of hoping it did. - 35 categories scored. Product titles read in 8 languages. - 94% of fashion revenue and 97% of home decor revenue classified into a category. Nothing hand waved. - Every single category laid over Google search demand, month by month. 🎯 What's inside both books → The Season at a Glance: every category placed by how big it is and how long it stays hot → The Five Big Bets for the niche → The Master Timeline: what to upload, and the LAST safe day to upload it → How Long Each Trend Burns: some run 7 months, some run 1 → Season Headwinds: what kills the season, so you see it before it hits you → The Category Playbook: the actual play, category by category → What the outside world predicts, checked against what we actually sold 😳 Three things in there that will annoy you → One fashion category is 29.4% of all fashion revenue on its own. Demand index 100. Stays hot for 6 months. Most stores treat it as one line out of twenty. → Christmas Sweaters. Everyone's Q4 plan. They run for exactly 1 month and they are 0.7% of revenue. You're building a quarter around a rounding error. → In home decor, 84% of the money is lighting. Not cushions. Not wall art. Lighting. And the biggest one of all stays hot for 5 months. ⏰ Why this matters this week Proper PMax learning takes about six weeks. Google says the same thing: get ready at least six weeks before peak. It's already September. Count six weeks forward. Your Q4 upload deadline is this month. Every date in the report is the LAST safe day. Not the ideal day.

We're running €50/day on Google Ads (PMax) for 153 products in the lighting niche (higher AOV, high-ticket). We resell existing brands, so pricing is competitive but margins are a bit tighter. Everything is optimized; titles, descriptions, competitive pricing but sales are very inconsistent: some days a sale, some days nothing. Most of these products haven't come close to getting enough spend yet to actually tell whether they're a winner or not. I get that spreading €50/day across 153 products means each one gets very little data, and more products = longer to find winners. Question: is it better to just shrink our catalog for now so the remaining products get enough spend to actually prove themselves, or should we add more new products to test? What's actually worked for others in a similar high-ticket/reseller situation?

Hey everyone! What do you usually do with products that get 0 impressions in Google Ads? Do you leave them and wait, or exclude them? Is it even something worth worrying about?

I’m currently testing new products every day, but I’ve noticed that there are always a few products that eat up a lot of the budget. What I do now is set a target CPA based on the break-even price, and when it goes above that, I remove it from the campaign because it’s no longer a profitable product. Sometimes you see that they still generate sales afterward if you let them run for a while, for example, so that makes me think it might actually be good for the algorithm in some cases—hence the question. But what’s the best approach: be strict about this and remove them, or is it normal to give such products more leeway so Google can optimize them, and if so, how far can you go?