1-day vs 7-day click attribution

Admaxxer is a DTC analytics platform with built-in Meta + Google ad ops. Picking 1-day-click vs 7-day-click attribution is a trade-off between over-crediting Meta and under-crediting it — there is no neutral option. The short answer: pick 1d-click for impulse categories (AOV < $60, consideration lag < 2 days) and 7d-click for considered categories (AOV > $150, consideration lag > 5 days). For everything in between, run both and blend. ## TL;DR - 7d-click overweights Meta's share; 1d-click underweights it - Match attribution window to consideration lag (time from first click to purchase) - Apparel ~2 days, supplements ~5 days, furniture ~14 days — rough bands - 1d-click gives cleaner creative-level decisions; 7d-click gives better campaign-level bid signal - Reconcile both against Shopify first-click via the Admaxxer [attribution model selector](/docs/attribution) ## Consideration lag by category Consideration lag is the time between first paid click and purchase. It's the single biggest driver of whether 1d or 7d is right for your store. - **Apparel (T-shirts, basics):** 1–2 days. Impulse-driven. 1d-click is closest to reality. - **Beauty (skincare, cosmetics):** 2–4 days. Blend of impulse and research. 1d-click captures most of the revenue; 7d inflates. - **Supplements:** 4–7 days. Research-heavy. 7d-click is more accurate than 1d but starts to over-attribute if competitor research happened between click and purchase. - **Furniture, home goods:** 7–21 days. High AOV, extensive research. 7d-click misses the tail; consider 28d-click view if available. - **Electronics (headphones, gadgets):** 3–14 days. Wide range depending on AOV. - **Food & beverage subscriptions:** 2–5 days for first order, <1 day for reorders. You can measure your own consideration lag in the Admaxxer [attribution dashboard](/docs/attribution) — it shows the distribution of days-from-first-click to purchase for your last 90 days. ## Diagnostic steps ### Step 1: Measure your actual consideration lag In Admaxxer's attribution view, look at the "days from first paid click to purchase" histogram. If 80% of purchases happen within 24 hours, use 1d-click. If the distribution has a long tail out to day 10, 7d-click captures more of the truth. ### Step 2: Compare Meta's 1d-click and 7d-click columns Open Meta Ads Manager → Ad Set level → Columns → Comparing Windows. Add "Purchases (1d click)" and "Purchases (7d click)" as parallel columns. The ratio between them tells you how much of Meta's claimed revenue is "tail" — purchases that happened days after the click. - 1d/7d ratio > 0.85: short consideration. Use 1d-click. - 1d/7d ratio 0.65–0.85: medium consideration. Either works; blend. - 1d/7d ratio < 0.65: long consideration. Use 7d-click, but worry about the tail over-attributing. ### Step 3: Cross-reference with Shopify first-click Shopify's first-click (from the `first_landing_page` or UTM source) is deterministic. If Meta claims 100 purchases at 7d-click but Shopify first-click only attributes 55 to Meta, the other 45 are either multi-touch (Meta contributed but wasn't last) or over-attributed. ### Step 4: Pick a primary window and document it Don't flip between 1d and 7d monthly — you'll confuse your own historical comparisons. Pick one, use it for bidding and performance review, and use the other as a cross-check. ### Step 5: Use Admaxxer's blended MER tile as the sanity check Regardless of which window you pick for Meta, blended MER is window-agnostic. If your 7d-click ROAS says 4.2× but MER is 2.1×, half of that ROAS is overlap or modelled. See [Blended MER vs ROAS](/guides/blended-mer-vs-roas). ## When to use hybrid windows Some teams use 1d-click for creative-level decisions (which ad to pause) and 7d-click for campaign-level bidding. This is defensible because: - **Creative-level** decisions need fast feedback. 1d-click gives you cleaner signal per ad because it's less susceptible to time-series noise from the 7d tail. - **Campaign-level** bidding benefits from longer windows because Meta's optimiser uses the full 7d signal to train its delivery model. If you run a 1d-click view-through ad set on the 7d-click creative, Meta's optimiser gets noisier signal and performance degrades. A hybrid approach: set the optimisation window to 7d-click in the campaign, but review performance at the ad level using 1d-click columns. The [Admaxxer creative grid](/docs/creative-grid) supports both views side-by-side. ## Common mistakes Three patterns we see often: 1. **Switching windows during a test.** If you changed from 7d to 1d mid-month, your comparison with last month is broken. Meta's reported totals shift by 20–40% just from the window change. 2. **Using 7d-click for brand search on Google.** Brand search is high-intent; the click-to-purchase gap is hours, not days. 7d over-attributes brand search by 30–50%. 3. **Ignoring view-through.** 7d-click + 1d-view adds view-through attribution. For upper-funnel video ads, view-through matters; for DR creative, it usually over-attributes. Meta's default is 7d-click / 1d-view. For long-tail consideration (furniture, mattresses), consider the 28-day click window Meta exposes in custom columns. It's not the default but it matches reality better for high-AOV goods. ## FAQs **What window does the Admaxxer default use?** Admaxxer stores raw event data and lets you pick the window at query time. The default display uses 7d-click to match Meta's default, but the [query_metrics](/docs/ai-agent) tool accepts a `window` parameter. **Does this also apply to Google Ads?** Yes but the tradeoffs are slightly different. Google's default is 30-day click + 1-day view for Search and Shopping. You rarely want anything longer for DTC — 7 days is usually enough. **What about data-driven attribution?** Google's DDA uses a machine-learning model to assign partial credit across the path. It's better than last-click but harder to reconcile with your Shopify ground truth. See [Platform vs pixel conversions](/guides/platform-vs-pixel-conversions). **Should I use 1d-click during scaling phases?** Yes — when you're scaling spend 50%+ month-over-month, shorter windows give faster signal and prevent runaway bid inflation on modelled tail conversions. **Can I run different windows per ad set?** Meta allows it, but mixing windows within a campaign confuses the optimiser. Keep the window consistent within a campaign.