Skip to main content
Metrics type: Key Metrics • Category: Ad Platform

​
At a glance

TTD-attributed conversion value. Includes click-through, view-through (for CTV/display), and cross-device conversions via Unified ID 2.0 / Identity Alliance. The cross-device dimension is TTD’s measurement edge: a CTV impression to a household member that converts on a mobile device 5 days later is correctly credited where peer DSPs miss the link.

​
Calculation

Calculated automatically from your The Trade Desk data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.

​
Worked example

The same enterprise homeware brand. Window 02 Apr 26 to 01 May 26. Shopify revenue this window: 1.85M.UTM−taggedTTD−source:1.85M. UTM-tagged TTD-source: 94,000. GA4 Paid Display + Paid Video: 128,400.∗∗TTDclaims128,400. **TTD claims 283,400**, of which $91,400 is cross-device attribution that no other DSP would surface. What’s interesting:
  1. Cross-device attribution is 32% of total revenue (91,400).∗∗ThisisTTD′smeasurementdifferentiator.CTVimpressionsseeinghousehold−levelconversiononweb/mobile,retargetingfollowingusersacrossdevices,DOOHleadingtoin−apppurchases.∗∗PeerDSPswouldattributemostofthis91,400).** This is TTD's measurement differentiator. CTV impressions seeing household-level conversion on web/mobile, retargeting following users across devices, DOOH leading to in-app purchases. **Peer DSPs would attribute most of this 91k to “Direct” or “Branded Search”; TTD captures it correctly via UID 2.0.
  2. DOOH (18,200revenueon18,200 revenue on 8,400 spend = 2.17× ROAS) is unique to TTD. No other DSP has comparable DOOH inventory access; the attribution comes entirely from UID 2.0 cross-device match (a user seeing a billboard on their commute, then converting on mobile that evening).
  3. CTV combined click+view+cross-device = 93,600from93,600 from 61,200 spend = 1.53× ROAS, on the lower side of the gauge but consistent with the structural CTV pattern across all DSPs.
  4. Retargeting at 4.63× ROAS is the standout. UID 2.0 retargeting reaches the user across web and mobile app, multiplying retargeting reach 2, 3× vs cookie-only. This is the campaign type to scale on TTD specifically.
  5. **Compared to Shopify-truth (94kUTM−tagged)∗∗:TTDis3.0×over−claiming.StandardDSPgap;thecross−deviceportionishardertovalidateindependently.∗∗ForCFOreportingusetheblendedfigure∗∗:4094k UTM-tagged)**: TTD is 3.0× over-claiming. Standard DSP gap; the cross-device portion is harder to validate independently. **For CFO reporting use the blended figure**: 40% TTD-claim + 60% Shopify-UTM = ~170k, the honest contribution figure.
  6. Prior 30D had $246,000 revenue; this window up 15% vs spend up 19%, slight ROAS compression but healthy scaling overall.
Quick sanity tests:
  • Revenue up + cross-device share growing = UID 2.0 maturing well.
  • Revenue down + cross-device share collapsed = UID 2.0 implementation issue; check email-hash exchange health.
  • Revenue down + click-through held = view-through window probably reduced.
  • All channels revenue up = healthy account growth.
  • DOOH revenue dropping suddenly = UID 2.0 match rate degraded for outdoor inventory; check.

​
Sibling cards merchants should reference together

​
Reconciling against the vendor’s own dashboard

Where to look in The Trade Desk: TTD Platform → Reports → Performance → Conversion Value at advertiser level. Should match this card to within sub-percent rounding. Other TTD views:
  • Conversions count vs value: distinct fields; for ROAS use Conversion Value.
  • Cross-device conversions: subset of total. TTD surfaces this as a separate line; this card includes it in the headline figure.
  • View-through conversions: subset; toggleable.
Why our number may legitimately differ from TTD UI: Cross-connector reconciliation, the important one:

​
Known limitations / merchant FAQs

Why does TTD claim 283krevenuewhenShopifysays283k revenue when Shopify says 94k? Standard DSP gap PLUS TTD-specific cross-device dimension. The 91kcross−deviceportionincludeshousehold−levelconversions(CTVimpressiontoonedevice,conversiononanother)thatnootherDSPwouldsurface.TheShopify−truth91k cross-device portion includes household-level conversions (CTV impression to one device, conversion on another) that no other DSP would surface. The Shopify-truth 94k captures only UTM-tagged last-click; it misses cross-device by definition. Real TTD contribution sits between the two; weighted blend (40% TTD + 60% Shopify) = ~$170k, the honest CFO figure. Should I trust TTD’s cross-device attribution? With caveats. UID 2.0 cross-device is the most reliable method available in 2026 for measuring household-level conversion paths. But it’s still probabilistic in places (where email-hash exchange isn’t complete) and over-claims when the same household has multiple users with different intent. Validate via incrementality testing (CTV holdout in one geo for 14 days) at least quarterly to ground the cross-device claim against real causal lift. My TTD revenue dropped 30% but spend is unchanged, what should I check first? TTD-specific check order: (1) UID 2.0 implementation health (cross-device match rate); a sudden drop in cross-device match rate dries up 30% of TTD’s revenue claim overnight. (2) Pixel health on web/CTV. (3) Audience freshness / Koa exhaustion. (4) Site/checkout changes. Why is my CTV revenue split between view-through and cross-device? Both are valid attribution paths for CTV. View-through: the same device that saw the CTV impression converted (rare for CTV, since you don’t shop on a TV; but possible if the household’s CTV device is also a tablet). Cross-device: the CTV impression went to one device (smart TV) and the conversion happened on another (mobile/desktop) within the household via UID 2.0 match. The cross-device portion is usually 60, 80% of CTV revenue; view-through is 20, 40%. My DOOH revenue depends entirely on cross-device, can I trust it? Yes, but with the same incrementality caveat as CTV. UID 2.0 maps the household-level identity from a billboard impression (DOOH device-graph match) to subsequent on-device conversion. Always validate via geo-holdout testing before scaling DOOH on the basis of attributed revenue alone. Should I exclude cross-device from ROAS calculations? Depends on the use case. For business-truth board reporting: probably yes; cross-device is hardest to validate. For TTD-internal optimisation: no; the cross-device signal is real and Koa uses it for bidding decisions. For incrementality: neither; only holdout testing answers the incrementality question. Why is TTD revenue more reliable than MediaMath revenue? TTD has continuous engineering investment in the reporting and attribution layer; MediaMath’s post-restructure platform has had stability issues. Same architecture, different operational reality. The migration trend reflects this. Can I trust the “today” revenue? More than peer DSPs. TTD’s 15, 30 minute ingest is the fastest in market. Still, use 7-day rolling for the cleanest read. My retargeting revenue rose sharply after enabling UID 2.0, is that real? Mostly real. UID 2.0 enables tighter retargeting audience match (same user across devices, no third-party cookie dependency); reach genuinely expands and conversion attribution genuinely tightens. Expect 20, 40% retargeting revenue lift within 30 days of enabling UID 2.0. Some of the lift is also recapture from previously-missed conversions, which is real revenue, just not incremental. Why is my multi-touch attribution model showing different TTD contribution than this card? MTA fractionally credits across all touchpoints; this card uses TTD’s last-paid-click + view-through + cross-device. Disagreement is structural. Use MTA for budget allocation; use this card for within-TTD optimisation.

​
Tracked live in Vortex IQ Nerve Centre

Total Revenue is one of hundreds of KPI pulses Vortex IQ tracks across The Trade Desk and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.