Predict Campaign Performance Before You Launch
AI-powered forecasting models that project ROAS, CAC, and revenue across multiple budget scenarios — so you invest with confidence, not guesswork.
Most businesses in Dubai plan marketing budgets by guessing or benchmarking against last year — without any way to predict what a given spend level will actually return. Campaign forecasting changes this fundamentally, giving you a data-backed projection of what your investment is likely to produce before you commit a single dirham.
BGS Technologies builds AI-powered forecasting models trained on your historical performance data, industry benchmarks, seasonality patterns, and competitive landscape. These models project ROAS, customer acquisition costs, and revenue outcomes under conservative, base, and optimistic assumptions — turning budget planning from a guess into an informed decision.
For growing UAE businesses making significant marketing investments, accurate forecasting is the difference between confident scaling and flying blind.
What's Included
Everything You Get with
Campaign Forecasting
Pre-Launch ROAS & CAC Modelling
Statistical models that project expected ROAS and customer acquisition cost for a planned campaign before launch — based on your historical data and market benchmarks.
Revenue Scenario Planning
Three-scenario projections — conservative, base, and optimistic — showing the range of revenue outcomes at different spend levels and performance assumptions.
Budget Allocation Recommendations by Channel
AI-driven recommendations on how to allocate your total marketing budget across channels to maximise projected revenue return — based on your specific margin profile and objectives.
Seasonal Trend Forecasting & Campaign Timing
UAE-specific seasonality modelling covering Ramadan, DSF, National Day, back-to-school, and other market events that predictably affect demand and campaign performance.
Competitor Spend Intelligence
Where available, we incorporate competitor ad spend and auction activity data into forecasts to model the impact of competitive pressure on your projected costs.
Post-Launch Forecast vs Actuals Tracking
Live dashboard tracking actual performance against forecast — identifying early divergences so you can adjust strategy before a campaign underperforms significantly.
How It Works
Our Process
Historical Data Analysis
We analyse your historical campaign performance data — ROAS, CPL, conversion rates, seasonality patterns — to build the foundation of the forecasting model.
Model Build & Calibration
We build the forecasting model, calibrate it against historical data to verify accuracy, and layer in market and seasonality variables specific to the UAE.
Scenario Modelling & Budget Planning
We run the model across your planned budget scenarios and produce a full forecast report with channel-level recommendations and confidence intervals.
Live Tracking & Model Refinement
Post-launch, actuals are tracked against forecast, model assumptions are validated against real data, and the model is refined for progressively greater accuracy.
Ready to get started?
Ready to invest in marketing with confidence, not guesswork?
Book a free strategy call — no pitch decks, no fluff. Just a clear plan for your business.
Common Questions
FAQ
How accurate can campaign forecasting really be?
Our models consistently achieve 85–95% accuracy for clients with 6+ months of historical data. Accuracy is lower for new campaigns or new channels where historical data is limited — in these cases, we use industry benchmarks with appropriate confidence intervals.
Do we need a lot of historical data for forecasting to work?
Six months of consistent campaign data is the ideal minimum. For businesses with less history, we use a combination of your available data, industry benchmarks, and comparable market data to build an initial model, which improves rapidly as you accumulate campaign history.
Can forecasting account for UAE-specific events like Ramadan?
Yes. UAE seasonality is a core component of our forecasting models — Ramadan, Eid, Dubai Shopping Festival, National Day, back-to-school periods, and summer slowdowns are all incorporated based on historical pattern analysis.
How is this different from the forecast tools built into Meta and Google Ads?
Platform-native forecasts only consider their own channel in isolation and are notoriously optimistic. Our models are cross-channel, calibrated against your actual historical data, and incorporate business variables like margin, churn, and CLV that platform tools ignore entirely.
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