How AI-driven Campaign Forecasting Boosts Telco Marketing Efficiency

Taking the pain out of marketing ROI unpredictability

Delivering ROI on telco marketing campaigns has become much harder in recent years. Budgets are under pressure, expectations from the boardroom are rising, and competition is intensifying — not only from traditional rivals but also from nimble MVNOs and challenger brands. In this environment, marketing leaders face a double challenge: deliver short-term results while building long-term brand equity.

CFOs tend to see marketing spending through a single lens; one that delivers predictable ROI. If results don’t materialize, Marketing risks being seen as a cost centre rather than a growth engine. Marketing teams need to demonstrate, on a regular and consistent basis, the short-term results that marketing can deliver. At a time when they are moving forward with personalized, AI-driven engagement, they must come up with transparent, predictable results.

So, what if telco marketers could break that cycle of unreliable forecasts with predictable results? What if they could say, with confidence: “Increasing spend by 20% on the postpaid sector should drive more than $3 million in incremental revenue — and here’s how we’ll validate that prediction.” That’s the language CFOs understand and with AI-powered forecasting, it’s becoming possible.

From reactive to predictive marketing

Traditional campaign planning is reactive. Teams look back at what worked — or seemed to work — in previous quarters and replicate it. But conditions change, customer behaviour shifts, competitors adjust, and new offers hit the market. What succeeded last quarter may flop today.

The solution is to flip the question from “What worked?” to “What should we do next — and how sure are we?” This is where AI-driven KPI forecasting enters the picture.

With AI-driven KPI forecasting tools, marketing teams can simulate campaign outcomes before committing a single dollar. They can test different offers, channels, and audience segments; identify underperforming combinations; and optimize messages and timing. By refining messages, adjusting timing, or switching audience focus before a campaign even launches, marketers can minimize risk in decision-making and maximize overall performance.

Scenario planning for smarter spend

Scenario planning is a powerful technique that helps marketers prepare for a range of possible outcomes, not just one. By modelling multiple “what-if” scenarios, they can keep strategies resilient, even when conditions change unexpectedly.

This approach is particularly valuable in telecoms, where customer churn remains one of the biggest threats. Let’s look at a real-world example.

A mobile operator is facing rising churn in its high-value postpaid base. Historically, its retention tactic was to blast out blanket offers like discounts or free data to broad customer segments. But this strategy wasted money on customers who weren’t leaving and missed many who were.

Instead, the operator could build a customer behaviour model using AI and machine learning. This model would be built through a deep analysis of usage patterns and trends, billing history, interactions with customer service teams, and responses to past offers. Let’s imagine, for illustrative purposes, three potential retention strategies designed by the marketing and product teams.

1. Customers are offered 10GB of free data for three months

2. Customers receive a 15% discount on their monthly bill for a month

3. Customers receive a free subscription to a video streaming service bundled with zero-rated data.

Rather than running one – or more – of the campaigns without being confident about which will have most success in terms of ROI the marketing department could simulate outcomes from each of the three options. Each scenario would have both revenue and cost implications, and the operator could choose whichever one had the best overall ROI.

With AI-driven KPI forecasting marketing teams can run simulations on multiple combinations of campaign variants to see which one is most likely to yield the best results. Rather than working with large target segments, they can drill down into subsegments and niche audiences, testing outcomes with precision to identify highly personalized and effective offers. They can test variants like:

• Audience segment responsiveness

• Offer attractiveness

• Pricing strategies

• Timing and delivery channels

• Campaign cost and ROI

At a time when efficiency and productivity are the watchwords for each and every CSP, such a simulation helps Marketing to bridge the gap between a customer-centric strategy and one which meets corporate efficiency goals and guidelines.

Modern KPI forecasting engines and Etiya Campaign Management

There are many different capabilities that modern KPI forecasting engines offer, to turn insights into actions. They include:

• Dynamic what-if scenarios with adjustable parameters (audience, offer, budget, channel).

• AI-powered modelling based on historical campaign data, customer behaviour, and segment-level trends.

• Instant visualization of predicted outcomes, from open rates and click-throughs to conversions and revenue.

• Democratized access through a no-code interface, so marketers — not just data scientists — can run simulations.

Etiya has added these capabilities into a new feature, Forecast KPI, which is part of its Campaign Management product. It is powered by Etiya’s AI platform, recognized in the Gartner Magic Quadrant, delivering exceptional intelligence and automation. The tool transforms aggregated marketing, product, and customer data into predictive business intelligence, helping marketers plan with precision.

At its core is a simulation engine powered by rich historical data and advanced AI algorithms. It estimates campaign outcomes — open rates, clicks, conversions, and revenue potential — across multiple scenarios. Marketers can compare these side by side, refine strategies, and defend budget requests based on actual data.

The feature has also been designed to give marketers access to cutting-edge AI capabilities but without the need to master AI technical skills. The no-code interface puts advanced forecasting capabilities directly into the hands of marketing teams, removing dependence on IT or data scientists. In just a few clicks, teams can model new campaigns, test assumptions, and iterate quickly.

Tools like Etiya’s AI-driven Forecast KPI take telecoms marketing from a reactive to a predictive discipline, offering operators a strategic enabler to optimize marketing spend, increase personalization, and align with CFOs’ demand for predictable ROI.