The State of Invalid Traffic (IVT) in 2026
Before we look at conversions, we must look at waste. The open programmatic web is still heavily plagued by non-human traffic. When brands buy blindly across standard ad exchanges or unvetted affiliate networks, a significant percentage of their budget evaporates before a real human ever sees an ad.
Across the open programmatic web, legacy DSPs regularly experience IVT rates between 5% and 12%. However, when advertisers switch to strictly filtered inventory using pre-bid behavioral analysis (the standard for Auctera), IVT drops by an order of magnitude:
- E-Commerce: Open web average is 8.2%. Filtered benchmark is 0.3%.
- Fintech: Open web average is 11.4%. Filtered benchmark is 0.4%.
- B2B SaaS: Open web average is 5.1%. Filtered benchmark is 0.2%.
- Gaming & Entertainment: Open web average is 14.8%. Filtered benchmark is 0.5%.
The Data Science Takeaway: If your platform does not natively offer deterministic pre-bid filtering, you are likely wasting roughly 8-10% of your gross media spend on bots, scrapers, and click-farms. By eliminating this waste at the root, advertisers instantly see a corresponding 8-10% improvement in their baseline CPA.
MTA vs. Last-Click ROAS Discrepancies
Our data shows a startling discrepancy between what legacy "last-click" dashboards report and what actually happened across the multi-touch journey. When we ported 50 enterprise clients from a legacy affiliate network to Auctera's Unified Data Layer, we discovered that 31% of all "affiliate conversions" had previously been touched by a DSP ad within the last 48 hours.
Because the legacy DSP and the legacy affiliate network couldn't speak to each other, the advertiser was paying both platforms for the same conversion. By moving to a Multi-Touch Attribution (MTA) model, these brands recovered nearly a third of their acquisition budget, allowing them to reinvest in net-new upper-funnel growth.
E-Commerce & D2C Benchmarks
The Direct-to-Consumer space relies heavily on dynamic creative optimization (DCO), sequential retargeting, and high-volume influencer affiliates. Margin compression makes every cent of CPA matter.
- Average CPA (Fashion): $22.50
- Average CPA (Health & Wellness): $38.10
- Average ROAS: 3.8x (up from 3.1x in 2024 due to better AI audience matching)
- Conversion Rate (from Click): 2.4%
- Highest Converting Channel: Cross-device Retargeting Cloud (42% of conversions), followed closely by Vetted Affiliate Content Sites (31%).
Fintech & App Install Benchmarks
Fintech requires rigorous brand safety, extremely high-intent targeting, and strict compliance with financial regulations. Consequently, CPAs are higher, but Lifetime Value (LTV) justifies the spend.
- Average Cost Per Install (CPI): $4.15
- Average Cost Per Funded Account (CPA): $68.00 (Retail Banking) / $145.00 (Crypto/Trading)
- Average Day-7 Retention: 28%
- Highest Converting Channel: Vetted Affiliate Network Partners (55% of conversions). Fintech apps rely heavily on trusted financial aggregators and review sites to build consumer trust.
B2B SaaS Enterprise Benchmarks
B2B sales cycles are long and require complex, multi-stage measurement over 90+ days. The goal here is not an impulse purchase, but a Marketing Qualified Lead (MQL) that turns into a booked demo.
- Average Cost Per Lead (MQL): $145.00
- Average Cost Per Demo Booked: $420.00
- Average Cost Per Won Opportunity (Enterprise): $4,800.00
- Highest Converting Channel: Programmatic Native & CTV Awareness (to build the initial brand footprint) followed by targeted LinkedIn/B2B Retargeting (65% of conversions).
Why These Benchmarks Matter
If your numbers are significantly worse than these benchmarks, your data is likely fragmented. When platforms compete against each other in silos, frequency caps break, users are spammed with identical creatives, and you end up paying duplicate commissions.
Unified architecture is no longer a luxury; it is the baseline requirement for hitting target ROAS in a highly competitive market. By comparing your internal dashboards against this $2B+ dataset, you can immediately identify whether your bottlenecks are creative, structural, or attribution-related.