Ad Spend Monitoring for DTC Brands
AI guardian built for direct-to-consumer brands scaling paid acquisition. Ad spend alerts for DTC brands that protect your ROAS across every channel with cross-platform AI monitoring — preventing wasted spend during the aggressive growth phases that make or break your brand.
Common Challenges
Scaling ad spend aggressively while maintaining target ROAS is a constant balancing act
Creative fatigue and audience saturation cause sudden spend inefficiencies that go unnoticed
Cross-platform attribution gaps make it hard to know where budget is actually being wasted
Rapid campaign iteration means budgets change daily, outpacing manual monitoring capacity
CAC spikes during peak seasons can burn through monthly budgets in days
How Ad Spend Guardian Solves This
AI-powered anomaly detection catches ROAS degradation and spend inefficiencies before they compound into real losses
Predictive pacing prevents budget exhaustion during high-velocity scaling by modeling spend against daily and weekly targets
Autonomous monitoring protects your acquisition channels 24/7 — especially during overnight hours when CPMs shift
Intelligent cross-platform spend correlation identifies which channels are draining budget without delivering returns
AI-driven threshold automation adapts to your scaling pace so guardrails grow with your ad spend
Perfect For
Other Use Cases
Ecommerce Brands
AI-powered ad spend alerts for ecommerce brands that protect your profit margins around the clock. Our AI guardian monitors Facebook, Google, and TikTok spend in real time so surprise overspends never eat into your bottom line.
Marketing Agencies
An AI guardian for client budgets that delivers ad spend alerts for agencies managing multiple accounts. Protect every client relationship with autonomous budget monitoring that catches overruns before your clients do.
High-Volume Advertisers
AI defense at scale — ad spend alerts for high-volume advertisers where every hour of undetected overspend costs thousands. Our AI processes spend data continuously so you can scale aggressively without scaling your risk.