What guardrail-driven automation actually delivers
Real outcomes from AI automation built with accountability. Every number below is an average across client engagements, measured against each account's own baseline — and tied to a specific trigger, action, and logged impact.
The averages we hold ourselves to.
Three headline numbers from the paid-media workflows we automate most. Here's what each one means — and below, exactly where it comes from.
Each figure is an average from client engagements, measured against that account's own baseline before we started. The 13 hours is the time a team used to spend by hand on these workflows every cycle. The 27% is the median ROAS lift after automating the budget, negative-keyword, and regional work. The +2 is the average Quality Score gain after matching language across keyword, ad, and landing page. Your numbers depend on where you start.
Want a baseline of your own? An automated AuditDemand audit ↗ quantifies the wasted spend in your account before any engagement starts.
Where the 13 hours go — and the ROAS and Quality Score with them.
The work a paid-media team does by hand on every deployment — who normally does it, how long it takes, and what comes back once we automate it. Each task maps to the metric it moves, so this one table backs all three numbers above. Medians across client engagements.
Four workflows do most of the work. A good paid-media manager already knows how to run them by hand — we build them as systems that run on every campaign instead.
Negative-keyword strategy
Catch the search terms quietly draining budget and shut them off every week, not once a quarter. Less waste, more spend on the terms that actually convert.
Budget aligned to performance
Move money toward the keywords and campaigns tied to real business results, and away from the ones that only look busy. Spend follows revenue, not clicks.
Regional inventory matching
Point budget at the regions that can actually fulfil, and pull it from the ones that cannot. You stop paying for clicks you could never serve.
Keyword, landing page, and ad language matched
Line up the words in the keyword, the ad, and the page it lands on. Google rewards the match with a higher Quality Score, which lowers cost and widens reach.
Four engagements. Four measurable results.
CPA reduced 35% in 90 days
Mid-market B2B SaaS. Google Ads. Waste analysis identified $4,200/month in underperforming spend across 6 ad groups. Guardrail rules automated bid adjustments and negative keyword additions weekly.
2.75× pipeline from dormant contacts
Professional services firm. 4,800 CRM contacts older than 90 days. Segmentation + personalized sequences + routing logic. Pipeline generated in first 45 days: $218,000.
68% faster campaign launches
Agency managing 12 client accounts. Brief-to-launch workflow automated. Average campaign setup time dropped from 11 hours to 3.5 hours. Deployed across all accounts in week 3.
+81% lead-to-meeting rate
B2B SaaS. Trade show lead capture. Enrich → personalize → route → track pipeline. 340 leads processed automatically within 4 hours of badge scan. Follow-up sent same day.
Every result is auditable.
Each automated action in our system is logged with its trigger condition, the action taken, the guardrails respected, and the measured impact. Nothing runs in a black box.
The TAI framework: Trigger / Action / Impact
Every automation we build follows the same accountability schema. A trigger defines the condition that initiates an action — a threshold crossed, a timing rule met, or a data signal detected.
The action is what the system does in response — and it only runs if all guardrails are satisfied. Spend caps, brand exclusions, and approval gates are evaluated before anything executes.
The impact is logged automatically — what changed, when, and by how much. Every sprint deliverable includes the TAI log as part of the handoff.
Read the full TAI framework →