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Predict the market. Move
first.

Cost per click · Google Search

Car insurance quotes · today

Forecast
Cost per click, Google Search, todayObserved cost per click from 08:00 to 13:00 is about $2.80 to $3.10. The forecast rises to about $3.90 by 17:00, with a widening 80% range. A recommended action is marked at 14:15. $2.50$3.00$3.50$4.00$4.5008:0010:0012:0014:0016:0018:0020:00 Now 13:00
Observed Forecast 80% range Act at 14:15, before the 16:00 rise

Budget moved · Meta to Google Search

RatioCast campaign · executed 14:15

Executed
Change
+$2,400 today on Google Search, −$2,400 on Meta
Why
Next-dollar return forecast at 1.7× on Google, 1.1× on Meta. A rival’s budget is pacing to run out by 15:30.
Expected
+3% to +7% conversions today, 80% confidence
Limits
Within max budget $40,000 a day and min tROAS 350%
InspectPauseRevert

Holdout test · conversions per $1,000

RatioCast campaign against its holdout · day 9 of 28

Measuring
4.04.55.0Day 0Day 7Day 14Day 21Day 28Today, day 9
RatioCast Holdout Lift so far +5.0%, 95% range −1.9% to +11.8%. Not yet significant.

Algorithmic trading for paid media. RatioCast reads your ad accounts, first-party data and market signals in real time, and moves budgets, targets and bids toward your real goal, before the market does.

Markets move in minutes. Marketing, in weeks.

Ad auctions reprice by the minute. Yet every advertiser now runs the same AI agents on the same clock.

Conversions report back in days, and most teams edit campaigns, budgets and targets weekly at best.

86% of marketing teams already use AI. Meta’s Advantage+ runs at a $75B+ run-rate, and over 30% of Google Search spend is in AI campaigns.

Same data, same AI, same clock. The edge is knowing where the auction goes next.

How fast things move

Each figure links to its source

A time scale from minutes to a year. Market events happen in minutes to days; marketing decisions take days to a year.

Ad auctions are markets

Trading went algorithmic decades ago. RatioCast brings that discipline to marketing, and treats every auction like the market it is.

Exchange
Google, Meta and TikTok auctions
Price
CPC and CPM
Volatility
Swings in CTR, CVR and CPC
Order-book depth
Bid headroom and impression share
Other traders
Competitors entering and leaving
Macro events
Seasonality, news and weather
Alpha decay
Creative fatigue
Broker as counterparty
The platform sells the inventory and bids for you
Backtesting
Simulate first, then run holdouts

One loop, in real time

Don’t act on what happened. Forecast what’s next. Swipe or use the arrows to follow the loop.

Sense

Your ad accounts, your first-party data and external market signals, read in real time and corrected for conversions not yet reported.

Real-time data pipeline

Your goal, not the platform’s

Platform bidders chase a ROAS or CPA target on average. RatioCast steers them toward what you actually want, and every move it makes is measured against that goal.

Pick a goal to see how RatioCast steers.

Maximises
Profit: revenue times margin, minus ad spend
Steers
Sets each campaign’s tROAS where the next dollar still earns more than it costs
Guardrail
Never below your min tROAS of 350%

Proposed Google Search tROAS 410% → 370%. Forecast: the next dollar still returns 1.4× after margin.

Maximises
New customers, at or above your return floor
Steers
Raises budgets and loosens targets wherever the next dollar clears the floor
Guardrail
Return floor 300%, max budget $40,000 a day

Proposed TikTok budget +18% today. Forecast: return stays at 330%, above the floor.

Maximises
Users who convert and stay, at a lower cost each
Steers
Feeds your first-party quality signals back, so bidders favour users like your best customers
Guardrail
Max tCPA $85

Proposed Meta tCPA $85 → $72, weighted to high-retention audiences.

Illustrative example. Your goal and limits are set together at onboarding.

From the calendar to the forecast

DecisionToday, on the calendarWith RatioCast, on the forecast
GoalThe platform’s target: ROAS or CPA on averageYour goal: profit, growth, or cheaper and better users
Channel splitYearly, from the media mix modelDaily, toward the best next dollar
tROAS and tCPAQuarterly, on the averageDaily, on the margin
CreativeChanged after results dropChanged before fatigue hits
CompetitorsSeen in next week’s reportForecast by the hour
Known eventsLast year’s calendarAhead of the surge, when ad prices jump 80%+
Unknown eventsMissedWithin the hour: a rival pulls out, a trend breaks, a checkout fails
ProofPlatform-reported resultsMeasured against holdouts

One campaign first, then the whole budget

RatioCast earns the budget step by step. It never spends outside the limits you set, and every result is read against a holdout.

  1. First, connect your accounts. RatioCast reads them in real time, with your first-party data and external market signals.

    Your ad accounts

    • Google Ads
    • Meta
    • TikTok

    First-party data

    • Site conversions

    Market signals

    • Trends
    • Weather
    • News

    Reading your accounts, first-party data and market signals in real time.

  2. Then, set the limits. RatioCast runs one campaign per channel inside them.

    RatioCast campaigns created on Google Search, Meta and TikTok. Capped by these limits.

  3. Finally, prove it against a holdout, then expand to the full budget.

    Land

    One capped campaign per channel

    Done

    Prove

    Lift measured against a holdout

    Day 9 of 28

    Expand

    The full budget, once it is proven

    Next

Under the hood

Four capabilities that are rare on their own. RatioCast runs all four together, for every account.

Bidder expertise

Thinks like the auto-bidders.

Models Smart Bidding and Advantage+ logic: targets, pacing and learning phases, so every move works with the platform, not against it.

Real-time data

Your data and the market, as it happens.

Streaming pipelines across your ad accounts, your first-party data and external market signals, corrected for late conversions.

Auction X-ray

Decodes the black box.

Rivals’ bids, budgets and pacing, inferred from partial signals through inverse auction modeling.

Auction foundation models

Learns how auctions move.

Sequence and time-series models trained on pooled data, so every account sharpens the forecasts for all of them.

A note from the founder

Tzahi Zilbershtein

Founder & CEO

I have spent my career building the engines that bid in ad auctions. I led an engineering group in Google Ads EMEA, served as CTO and VP R&D, hold patents on auction bidding systems, and hold an Executive MBA.

RatioCast starts from one observation. AI now runs the bid for everyone, on the same data and the same clock, but it does not look ahead. Budgets, targets and the channel split still move on the calendar. Trading desks solved this decades ago with models that forecast the market and act inside strict risk limits. RatioCast brings that discipline to ad auctions: forecast, act inside limits, measure against a holdout.

The AI behind RatioCast is of a specific kind. Not a chatbot, but sequence and time-series models that learn how each auction moves, reverse-engineer rivals from partial signals, and get sharper with every account they learn from.

We are starting with a small number of large performance advertisers on Google, Meta and TikTok. If that is you, I would like to show you what RatioCast sees in your auctions.

See the road ahead

Smart Bidding is the engine. RatioCast is the driver who sees the road ahead.