At a glance
Per-campaign drill-down of zero-conversion spend on Snapchat. The companion to Wasted Spend. Each row is a campaign live more than 7 days that produced zero attributed purchases. The 7-day filter excludes Learning-Phase campaigns (Snap’s algorithm typically needs 50+ purchases to fully optimise; campaigns younger than 7 days are still in this window). On Snap, this card commonly surfaces vertical-fit failures and high-iOS-share attribution false-positives more than creative-fatigue cases.
| What it counts | Per-campaign rows where purchases = 0 AND spend > 0 AND campaign_age_days >= 7. Each row shows campaign name, age, spend, impressions, swipe-ups, CTR, and the diagnostic shape. |
| Marketing API level | Campaign-level. Drill down further to adset via Wasted Spend. |
| The 7-day filter | Snap’s algorithm needs 50+ purchases to optimise fully; campaigns younger than 7 days are usually still in Learning Phase. Lower-volume accounts may need 10, 14 days. |
| Currency | Account currency. |
| Attribution model | Account default (typically 7d swipe-up + 1d view). |
| iOS 14.5+ ATT impact | Largest false-positive risk of major platforms. Snap’s iOS share (60, 75%) means a Pixel-only campaign on iOS-heavy audiences can appear here even when actually converting. Cross-check GA4 / Shopify before pausing. |
| CAPI impact | Reduces false-positives by 30, 50% post-rollout. Card row count drops accordingly. |
| AR Lens / Awareness objectives | Lens and Brand Awareness campaigns systematically appear here (zero direct purchases by design). Filter at alert-rule level. |
| Time window | 30D. |
| Alert trigger | >$0 on any campaign >7D old. |
| Roles | owner, marketing, finance |
Calculation
Calculated automatically from your Snapchat Ads data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A US Gen-Z DTC fashion brand. 30-day window 02 Apr 26 to 01 May 26. Account currency USD. CAPI live. iOS share 73%.| Campaign | Age (days) | Spend ($) | Impressions | Swipe-ups | CTR | Verdict |
|---|---|---|---|---|---|---|
| Cold prospect, gym-equipment 25-45 male | 28 | 1,400 | 410,000 | 1,840 | 0.45% | Pause: vertical-fit failure |
| Cold prospect, yoga 25-34 female | 21 | 920 | 220,000 | 2,200 | 1.00% | Broaden: vertical-fit edge |
| AR Lens, branded selfie filter | 14 | 1,400 | 6,200,000 | 12,400 | 0.20% | Filter: Lens objective |
| Story Ads, creator @charli boost | 11 | 480 | 140,000 | 4,200 | 3.00% | Watch: high CTR, awareness-tier |
| Brand Awareness, hashtag flight | 9 | 1,800 | 14,200,000 | 8,400 | 0.06% | Filter: Brand Awareness objective |
- Cold prospect, gym-equipment 25-45 male ($1,400, 28 days, zero conversions). CTR 0.45% is below platform average. Audience is firmly outside Snap’s vertical fit (older male, industrial product). Vertical-fit failure. Pause permanently and don’t re-test on Snap. Redirect to Meta where this audience converts.
- Cold prospect, yoga 25-34 female ($920, 21 days). CTR 1.00% is platform-average; the audience clicks but doesn’t convert. Two reads: (a) audience too narrow (broaden to 18-34) → likely converts; (b) Snap can’t break through with this product on this demographic → pause. Test the broaden first.
- AR Lens, branded selfie filter ($1,400, 14 days). 6.2M impressions, 12k engagements. Direct conversions zero is expected, Lens is awareness-tier. Filter
objective in ('LENS', 'AWARENESS')from the alert rule. - Story Ads creator boost ($480, 11 days). CTR 3.00% is excellent (well above platform average). Zero conversions despite strong engagement is the awareness-tier shape on creator partnerships. Watch, don’t pause. Spark Ads-equivalent on Snap have brand-equity value beyond direct attribution. Judge on 60, 90 day MMM read.
- Brand Awareness hashtag flight ($1,800, 9 days). Reach-objective; zero direct conversions is expected. Filter from alert rule.
- Pause the gym-equipment cold prospect today (clearest vertical-fit failure, $1,400 freed).
- Broaden the yoga audience to 18-34 for one more period (low cost, high information value).
- Filter AR Lens and Brand Awareness from the alert rule (configure
objective not in ('LENS', 'AWARENESS', 'BRAND_AWARENESS')). - Reallocate $1,400 to LAL 1% (purchasers) and 7d-cart-abandoner retargeting.
- Same vertical-fit-failure audience appearing for 2+ periods = your team is testing audiences outside fit. Stop.
- AR Lens / Brand Awareness rows = filter, not pause.
- High-CTR / zero-conv rows = downstream problem (landing, pricing) or awareness-tier objective. Don’t fix at the ad level.
- iOS-heavy campaign appearing = check GA4 / Shopify before pausing. Could be attribution gap.
- New campaigns appearing day-1 of life = the 7-day filter is misconfigured; tighten.
Sibling cards merchants should reference together
| Card | Why pair it with Zero-Conversion Spend | What the combination tells you |
|---|---|---|
| Wasted Spend | The summary view; this is the per-row drill-down. | Concentrated waste vs spread waste. |
| Total Spend | The denominator. | Whether $3k waste is 5% of account spend or 30%. |
| CTR Trend | High-CTR / zero-conv = downstream problem. Low-CTR / zero-conv = creative or vertical mismatch. | Different fixes. |
| Conversion Rate Trend | Downstream-funnel check. | Distinguish ad-level waste from funnel-level waste. |
| ROAS by Campaign | Side-by-side view of zero-conv vs converting campaigns. | Are zero-conv campaigns a minority of spend or a big chunk? |
| Worst Performing Campaigns | The negative-ROAS list. | Some zero-conv campaigns also appear there (overlapping rows, different definitions). |
| Conversion Lag | Snap’s 7d/1d window means today’s zero-conv might convert tomorrow. | Don’t act on day-1 reads. |
| Meta Zero-Conversion Spend | Cross-platform peer. | Compare which platform produces more zero-conv waste; Snap rows skew vertical-fit, Meta rows skew audience-mismatch. |
| TikTok Zero-Conversion Spend | Cross-platform Gen-Z peer. | TikTok rows skew creative-fatigue (refreshable); Snap rows skew vertical-fit (structural). |
Reconciling against the vendor’s own dashboard
Where to look in Snap Ads Manager: Snap Ads Manager > Campaigns > sort by Purchases ascending, filter Spend > 0, filter Created > 7 days ago. Top of the sort matches this card’s list. Other relevant views:- Reports > Custom > Campaign Performance (downloadable).
- Audience Insights per campaign for vertical-fit diagnosis.
- Delivery > Learning Phase status.
| Reason | Direction | Why |
|---|---|---|
| Time zone | Boundary days off | Snap uses ad-account TZ; UTC card. |
| Modeled conversions | Lower row count in our card | Modeled fill counts toward the campaign’s purchase count. |
| Learning-Phase exclusion | Ours stricter | Our 7-day filter excludes Learning campaigns; Snap UI does not filter automatically. |
| Ingest lag | Higher count for “today” | 4, 8 hour lag. |
| Attribution window changes | Direction depends | 7d→28d switch reduces row count. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
google_analytics.ga_revenue_by_channel | If GA4 attributes Snap revenue to a campaign in this list, iOS attribution gap. | Real iOS conversions invisible to Pixel show in GA4 (Consent Mode v2). |
shopify.total_revenue | UTM-tagged Snap orders should account for “real” conversions. | Without UTM, Shopify can’t attribute back. |
facebook_ads.fac_zero_conversion_spend | Independent paid-social peer. | Meta rows = audience-mismatch; Snap rows = vertical-fit. |
tiktok_ads.tik_zero_conversion_spend | Independent Gen-Z social peer. | TikTok rows = creative-fatigue; Snap rows = structural mismatch. |
Known limitations / merchant FAQs
Why is the same campaign appearing here for 3 weeks running? On Snap, almost always vertical-fit failure. The audience is outside Snap’s natural fit window (older demographic, B2B-leaning, industrial product, mass-market non-lifestyle). Creative or audience tuning won’t fix this; the channel can’t reach the buyer. Pause and never re-test. Try this audience on Meta or Google Ads instead. The campaign just started, why is it on this list? The 7-day age filter should exclude very new campaigns. If a 2-day-old campaign appears, the alert configuration is overriding the default; tighten tocampaign_age_days >= 7 (or 10, 14 days for low-volume Snap accounts where Learning Phase takes longer).
My AR Lens always appears here, is that a problem?
No. AR Lens (auction self-serve) is awareness-tier; direct purchase attribution is the wrong measure. Configure the alert rule to exclude objective in ('LENS', 'AWARENESS'). The Lens value lives in branded-search lift and earned impressions, measured 30, 60 days later.
Should I pause every campaign on this list?
No. Triage:
- Vertical-fit failure: pause permanently.
- Vertical-fit edge: broaden audience first; if still wasted next period, pause.
- Awareness / Lens objective: filter from alert.
- High-iOS-share (>60%) campaigns: cross-check GA4 / Shopify; could be attribution gap, not real waste.
- Creator-boost / Story Ads partnerships with high CTR but zero conversions: watch, don’t pause; brand-equity value lives off-platform.
- Vertical-fit failure: campaign never converted from launch, multiple creatives tested. Audience is outside Snap’s fit. → Pause permanently.
- Creative fatigue: campaign converted historically (e.g. ROAS 3+ for 4, 6 weeks), then dropped to zero. Same audience, different time. → Refresh creative.