Optimize Marketing Spend Across Channels with Custom AI

Most marketing teams rely on the native AI bidding tools within Google Ads (Smart Bidding) or Meta (Advantage+). These tools are effective at optimizing spend within their own platforms but are fundamentally designed as black boxes. They cannot reallocate budget from a Google campaign to a Meta campaign, even if Meta is delivering a 50% lower cost-per-acquisition. Each platform operates in a silo, blind to cross-channel performance.

Consider a 10-person agency managing 15 client accounts. Every Monday, a campaign manager spends 4 hours pulling reports from Google Ads, Facebook Ads Manager, and LinkedIn Ads. They paste this data into a Google Sheet to calculate a blended CPA. Based on last week's data, they decide to shift $500 from a Google campaign to a Facebook one. By the time this manual change is made, the performance trend may have already reversed, making the decision obsolete.

The structural problem is data fragmentation combined with a lack of execution capability. Reporting tools like Supermetrics or Funnel.io can aggregate data into one place, but they are read-only. They can show you that LinkedIn is outperforming Google, but they cannot act on that insight. You still need a human to log in to each platform and manually execute the budget shifts, introducing delays and potential for error.

Syntora's process begins by mapping your current campaign management workflow. We conduct an audit of your ad accounts and conversion tracking setup. The goal is to codify the exact logic for budget allocation: what metrics (ROAS, CPA, CPL) trigger a budget shift, what are the minimum and maximum budget constraints per campaign, and how frequently the system should run. This audit produces a clear specification for the automation logic.

For a marketing agency, we built a similar system using Python and the Google Ads API. A full cross-channel solution would use a central Supabase database to store performance data polled from all connected ad platform APIs. An AWS Lambda function would run every 6 hours, pulling the latest metrics. A Python script then executes the allocation logic, calculating new budgets and bids, and pushes changes back to each platform. We use FastAPI to create a simple internal dashboard for monitoring and manual overrides, with an API response time under 200ms.

The delivered system runs automatically on cloud infrastructure that you control, with hosting costs under $50/month. It logs every change it makes for full transparency. You also receive a custom dashboard, powered by the Claude API, that provides plain-language summaries of performance shifts and reallocations. Instead of a spreadsheet, you get a daily insight summary like: "We shifted $250 from Google Search to Meta Retargeting because Meta's CPA dropped by 15% yesterday."