At a glance
Snapchat-attributed purchase value across every campaign in the selected ad account. The numerator of ROAS. NOT order revenue from Shopify, this is what Snap’s Pixel + CAPI says it drove. Snap’s iOS share is structurally the highest of the major platforms (60, 75% on US accounts), so the gap between Snap-claimed revenue and UTM-truth Shopify revenue is the largest, expect 60, 110% over-claim without CAPI, narrowing to 25, 50% with CAPI live.
| What it counts | purchases_value from Snap Marketing API, advertiser-level. Includes Pixel-confirmed purchases, CAPI events, and modeled-conversion fill. |
| Marketing API level | Advertiser-level. Per-campaign / per-adset / per-ad revenue rolls up to this card. |
| Currency | Account currency, single per account. |
| Conversion attribution | 7-day swipe-up + 1-day view (post-iOS 14.5 default). Configurable to 1d, 7d, 28d for swipe-up and 1d, 7d for view. (Snap calls a click “swipe-up”, a holdover from the original Stories UX.) |
| Attribution window | Default 7d swipe-up + 1d view. Lengthening to 28d typically lifts revenue 8, 18% (Snap’s audience converts on a longer cycle than TikTok’s because Story-Ad recall is stickier; users see, save mentally, buy 3, 14 days later). |
| iOS 14.5+ ATT impact | Worst of the major platforms because of Snap’s high iOS share. Without CAPI, expect Snap-reported revenue to over-state UTM-truth Shopify by 60, 110%. With CAPI live, narrows to 25, 50%. |
| CAPI vs Pixel-only | Pixel-only: ATT-blocked iOS purchases missing → revenue under-states real, then Snap auto-fills with modeled conversions → over-states. Net: noisy and structurally inflated. CAPI live: tighter, less modeled fill. |
| Modeled conversions | Snap auto-fills attribution gaps. Modeled fill typically runs 18, 28% of purchases_value on Pixel-only DTC accounts (highest of the major platforms); drops to 8, 15% post-CAPI. Cannot opt out. |
| AR Lens-attributed revenue | Lens conversions track via the same Pixel and surface in purchases_value if the user swipes through to the brand site after engaging. Most Lens-driven revenue arrives via brand-search lift on Google 30, 60 days later, NOT through this card. |
| View-through revenue | Included in the default 1-day view window. Pure swipe-up only revenue is in swipe_up_purchase_value (separate metric). |
| Bot / invalid traffic | Snap filters detected bot impressions pre-billing. Filtered traffic does not produce attributed revenue. |
| Time window | T/7D/30D vsP. 4, 8 hour ingest lag plus 24, 72h modeled-conversion convergence. |
| Alert trigger | drop >20% vsP. |
| Roles | owner, marketing, finance |
Calculation
Calculated automatically from your Snapchat Ads data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A US Gen-Z DTC fashion brand on Shopify. 30-day window 02 Apr 26 to 01 May 26. Account currency USD. CAPI live since 09 Mar 26. iOS share 73%.| Campaign | Spend ($) | Snap-attributed revenue ($) | Per-campaign ROAS | Notes |
|---|---|---|---|---|
| Conversions, cold prospect (Story Ads) | 7,200 | 24,800 | 3.44x | 6 vertical-video creatives, fortnightly refresh |
| Conversions, retargeting 7d (Story Ads) | 1,800 | 12,200 | 6.78x | warm pool |
| Catalog Sales (DPA) | 3,400 | 13,600 | 4.00x | feed-driven, top-30 SKUs |
| AR Lens (auction self-serve) | 1,400 | 1,800 | 1.29x | branded Lens, awareness-tier |
| Account total (this card) | $13,800 | $52,400 | 3.80x |
- Snap claims 19,400 UTM-tagged. That’s a 2.7x gap, the widest of any major platform. Real Snap-driven revenue is closer to 52k to the CFO without the iOS-gap caveat.**
- Modeled fill at 22% of
purchases_valueis high but expected on a 73%-iOS account even with CAPI live. Pre-CAPI fill was likely 35, 45%. If post-CAPI fill stays above 25%, audit the dedup setup (Pixel + CAPI must use matchingevent_id). - AR Lens ROAS at 1.29x is misleading, the Lens drove 6.2M impressions; most of the brand value lands as branded-search lift on Google 30, 60 days later, not in direct attributed revenue. Don’t kill the Lens campaign on direct ROAS. Cross-reference Google branded-search organic clicks 30 days from Lens launch.
- Retargeting at 6.78x is cookie-pool defence, the audience already visited the site; Snap is taking last-click credit for buyers who would have come back via email or organic. Same dynamic as TikTok / Meta retargeting. The “true acquisition” ROAS is closer to the cold-prospect 3.44x.
- Revenue dropped 11% versus prior 30D (52.4k) while spend held flat. Below the 20% trigger but trending. Cold-prospect Story Ads creative is on day 22 of its current rotation, well past the typical 4, 6 week Snap fatigue cycle. Refresh creative within 7 days to avoid a >20% drop next window.
- Revenue up + spend up = healthy on a vertical-fit account.
- Revenue flat + spend up = vertical-fit problem (audience saturated). Pull back.
- Revenue down + spend up = creative or audience exhausted. Refresh.
- Revenue down + spend flat = something changed in the funnel. Check Conversions Trend, Conversion Lag.
- AR Lens revenue drop = expected; judge brand-search lift 30, 60 days out, not direct revenue.
Sibling cards merchants should reference together
| Card | Why pair it with Total Revenue | What the combination tells you |
|---|---|---|
| Total Spend | The denominator of ROAS. | Whether revenue moved on cost-side or revenue-side. |
| ROAS | The efficiency ratio. | Revenue up alone is healthy only if ROAS held. |
| Revenue by Campaign | Per-campaign split. | Whether revenue concentrates in one campaign (risk) or spreads. |
| Conversions Trend | Volume side of revenue. | Revenue down + conversions down = real channel deterioration. Revenue down + conversions flat = AOV problem. |
| Conversion Lag | Snap’s 7d/1d window means today’s revenue is incomplete. | Use the lag card to gauge how much “today” revenue is still inbound. |
| Wasted Spend | Adsets producing no revenue. | If revenue is flat but spend is rising, wasted-spend share is climbing. |
| GA4 Revenue by Channel | Independent attribution check. | Snap typically reports 50, 90% higher than GA4 (the largest gap of the major platforms). |
| Shopify Total Revenue | The truth side. UTM-tagged Snap revenue is the lower bound; Snap’s claim is the upper bound. | Real Snap revenue between the two; use 25 / 75 Snap / Shopify blend for the CFO read (heavier toward Shopify than other platforms because of Snap’s iOS gap). |
| TikTok Total Revenue | Peer Gen-Z social revenue. | TikTok’s claimed revenue is structurally less inflated (lower iOS share). |
| Meta Total Revenue | Peer paid-social revenue. | Meta’s claimed revenue is also inflated post-iOS but typically less so than Snap (Meta’s iOS share is mid-pack). |
Reconciling against the vendor’s own dashboard
Where to look in Snap Ads Manager: Snap Ads Manager > Campaigns > Purchase value column. Date range matched to this card’s window; footer total reconciles to within sub-percent rounding. Other Ads Manager columns:- Purchases (count, not value).
- Swipe-up purchase value (click-only, excludes view-through).
- Add to cart value: upper-funnel signal, not revenue.
| Reason | Direction | Why |
|---|---|---|
| Time zone | Boundary days off | Snap uses ad-account TZ (immutable). UTC card. For 30D the gap averages out; today / yesterday can shift on US Pacific accounts. |
| Attribution window changes | Direction depends | 7d→28d swipe-up switch typically lifts revenue 8, 18%. Snap’s longer-window option is not deprecated. |
| Modeled conversions | Both inflate equally | Snap blends modeled into purchases_value; this card reads the same blended field. |
| Ingest lag | Lower for “today” | 4, 8 hour lag on Marketing API; modeled-conversion convergence 24, 72h. |
| Currency | None expected | Both UI and card use ad-account base currency. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
google_analytics.ga_revenue_by_channel | GA4 Paid Social Snap revenue ÷ this card ≈ 0.4, 0.65 | Snap inflates by 50, 90% versus GA4 structurally on iOS-heavy accounts. |
shopify.total_revenue filtered to Snap UTM | This card claims 1.7, 3.0x the UTM-truth Shopify number | Pixel + CAPI + modeling all credit conversions Shopify cannot UTM-attribute back. Use a 25 / 75 Snap / Shopify blend for the CFO read. |
tiktok_ads.tik_total_revenue | Independent Gen-Z social revenue | TikTok’s claimed revenue is structurally less inflated. |
facebook_ads.fac_total_revenue | Independent paid-social revenue | Meta’s iOS share is mid-pack; Snap’s gap is wider. |
Known limitations / merchant FAQs
Why does Snap claim 19k from Snap-tagged orders? Because Snap’s iOS share is the highest of the major platforms (60, 75% on US accounts) and the iOS attribution gap is correspondingly the widest. Even with CAPI live, expect Snap to over-state UTM-truth Shopify revenue by 25, 50%. Practical answer: real Snap-driven revenue is closer to $24, 32k. Use a 25 / 75 Snap / Shopify blend for the CFO read (heavier toward Shopify than other platforms because of the larger gap). Why is Snap’s iOS gap worse than TikTok’s or Meta’s? Snap’s user base is structurally iOS-heavy. The platform rose to popularity 2013, 2017 on iPhone-first US Gen-Z; never won the Android share TikTok captured. Heavy Snap users on iOS spend more time than equivalent Android users, amplifying the iOS share among engaged users. Effect on this card: Snap-claimed revenue is the most inflated of the major platforms post-iOS 14.5. What’s the Snap CAPI rollout playbook?- Shopify: Snap official Sales Channel app > enable CAPI > “Maximum” data sharing. 30, 60 minute setup. Auto-deduplicates Pixel + CAPI via
event_id. - BigCommerce: Snap Pixel app + manual CAPI via Tag Manager + custom event_id. 2, 4 hours.
- Adobe Commerce / Magento: Snap extension + custom server endpoint. 1, 3 days.
- Custom / headless: Server-side proxy. 1, 2 weeks.
- In all cases: deduplicate via
event_id. Test in Snap Events Manager > Test Events. Allow 7, 14 days for retraining.
purchases_value on Pixel-only DTC, the highest modeled fill of the major platforms. Patterns:
- Pre-CAPI: ~28, 38%. Inflated.
- Post-CAPI clean: ~8, 15%. Healthy.
- Post-CAPI still high (>22%): implementation gaps. Audit
event_iddedup.
- Smaller audience pool means lower-volume campaigns hit lookalike saturation faster. A campaign that earned 2k/week as the audience exhausts.
- Lens-format virality is binary: a Lens that goes viral can drive 3, 5x revenue spikes; a Lens that doesn’t trend produces near-zero direct conversions.
- Vertical-fit dependency. Brands at the edge of Snap’s vertical fit (e.g. mass-market fashion, mid-range cosmetics) see week-to-week revenue swings driven by which sub-audience the algorithm samples each week.
- Cosmetics, fashion, lifestyle: Snap wins on CPM efficiency; TikTok wins on scale. Run both for incremental reach.
- Gaming, food delivery, dating apps: Snap-native verticals; Snap typically wins on direct-response.
- Electronics, footwear, athleisure: TikTok-native; Snap underperforms.
- Anything 25+ demographic: Meta wins; both Snap and TikTok underperform.