Paid advertising
Full coverage across major global ad ecosystems. An outcome-driven, multi-channel methodology — every dollar trackable, every dollar optimizable.
PAID ADS · Channels
Methodology
Audience layering
Cold / warm / hot segmentation based on intent signals, with differentiated creative per layer
Creative factory
Systematic multi-variant creative output; A/B and incrementality testing drive iteration
Attribution optimization
Cross-channel attribution and automated bidding to reduce CAC and grow incremental conversion
Outcomes
Why AI Agent paid playbooks differ from standard SaaS
AI Agents have a longer decision path than a typical SaaS. A buyer needs to grasp both “what can this Agent actually do for me” and “what will it do with my data.” That rules out one-click cold conversion. Trust has to be layered across cold / warm / hot audiences, and every creative is tuned to the specific objection of its layer instead of a single pitch repeated to everyone.
Cross-channel attribution is the other big one. AI Agent buyers often see a Reddit thread, read a Google comparison, and sign up via a LinkedIn ad. Last-click alone would push you to over-invest in LinkedIn while ignoring the upstream ignition. We model cross-channel contribution so budget follows incrementality, not last-touch.
What we won’t do
- No campaigns without working landing pages and event tracking — ads without data are just burn
- No fake traffic or follower purchases — only attributable real-human reach
- No headline CAC promises — we commit to iteration cadence and A/B pace; the number fluctuates with the market
- No locked-away accounts or creative — the ad accounts, audiences, and creative all belong to you
Every ad dollar — tracked, attributed, optimized
Cold / warm / hot audience tiers, full-funnel from impression to LTV.
- Google / Meta / X / LinkedIn / Reddit end-to-end
- Creative factory + weekly A/B-driven iteration
- Cross-channel attribution to lower CAC and lift incrementality