By Pavel Yurovitsky, Chief Strategy Advisor and Chairman of the Board at KIT Global
AI is transforming marketing, promising a more data-driven, results-oriented approach. But while nearly nine in ten marketers currently use AI for content creation, only around half use it to analyze data to optimize campaigns and improve return on investment. This gap is especially critical in performance marketing, which is a strategy designed to ensure every marketing dollar drives measurable results.
Experts expect the performance marketing software market to reach more than $30 billion in value by 2032, showing that many businesses are investing heavily in data-driven advertising. Despite the best intentions, not all of that money produces the desired return on investment as far as many organizations are concerned. But there are ways to increase ROI through the right use of AI.
Understanding performance marketing
At its core, performance marketing is all about data. Unlike traditional advertising, in which businesses pay up front for ad space regardless of results, performance marketing means businesses only pay when a specific action happens, like a click, lead, or sale. Companies use it in affiliate marketing, social media ads, and search engine marketing to make sure that every dollar spent ties directly to measurable outcomes. One of the most common types of performance marketing that you’re likely familiar with is pay-per-click (PPC) advertising.
Performance marketing is especially necessary in tight budget scenarios. As ad costs rise, companies can’t afford to waste money on ineffective campaigns. Performance marketing should, in theory, solve this problem. The problem is, marketers don’t always use it the right way.
Doing performance marketing right
Many marketers focus on the wrong metrics when it comes to performance marketing. Clicks don’t always translate to sales. Neither do leads. Measuring success based on these surface-level numbers alone can create a false sense of effectiveness while failing to drive actual revenue.
However, those who really want to make the most of their strategies need to focus on something besides vanity metrics. AI-powered tools can help marketers analyze data across multiple campaigns and platforms to get a more complete picture of what’s working and what’s not. Instead of just tracking clicks, teams can measure more specific metrics, like customer churn rates or external market factors, to optimize strategies.
For example, a spike in churn may indicate misleading marketing that initially brings people in but fails to keep them when the product doesn’t measure up. A competitor’s PR crisis may mean you have an opportunity to increase your ad spend and visibility so that you’re in front of the eyes of the customers that are migrating away from their software. Those are factors that real-time monitoring through AI can automatically detect and integrate into marketing reports and campaigns.
Additionally, AI can help marketers personalize based on more information and tailor messaging that directly addresses customer pain points. If a competitor’s software recently suffered a major security breach, AI-powered performance marketing can identify and target affected users with messaging that shows your product has superior security features.
Using these strategies will allow you to make the most of your performance marketing strategies in the coming year.
Final thoughts
AI isn’t going anywhere, and neither is performance marketing. It’s up to you to ensure that you can get the full benefits of both. AI-driven insights can help you get away from surface-level metrics and make smarter, more strategic decisions. The companies that make a change now will both improve their ROI and gain a competitive edge in an increasingly data-driven marketing landscape.
