Editorial
Proving the ROI of marketing efforts has long been one of the most frustrating challenges for marketing teams. Data fragmentation, outdated attribution models and shifting consumer behaviors make it difficult to connect the dots between campaigns and revenue impact. In an era where marketing budgets are under more scrutiny than ever, proving ROI isn’t just important to today’s marketers, it’s essential.
AI-powered tools are modernizing the way marketers measure, analyze and optimize performance. By leveraging machine learning, automation and predictive analytics, these tools help marketers track the effectiveness of their campaigns with greater precision, allocate budgets more efficiently and ultimately maximize the value of every marketing dollar spent.
Marketers should consider the following five AI-driven platforms, all of which are highly effective at empowering them to take control of their ROI.
1. AI for Multi-Touch Attribution
Suggested Tool: Rockerbox
What It Does: Rockerbox (recently acquired by DoubleVerify) created a unified measurement platform which combines multi-touch attribution (MTA), marketing mix modeling (MMM) and incrementality testing solutions into one unified platform, offering a single view of marketing performance. With it, marketers simplify the complexities of all their marketing channels into a single measurement solution.
Why It Matters: Often, marketers must juggle a series of disconnected reports that don’t always offer a single, trustworthy view of marketing performance. On top of that, traditional attribution models like last-click or first-touch fail to capture the true influence of each marketing channel as a contributor to the buyer's shopping journey. Combining the different types of reporting into one unified platform, and validating it with incrementality testing, this AI tool can simplify and streamline marketing reporting — and contribute to smarter channel optimization.
How It Works: Rockerbox centralizes marketing data and uses machine learning (ML) to assign value to each touchpoint — from social media ads to organic search.
ROI Impact:
- More accurate budget allocation
- Reduced wasted ad spend
- Deeper insights into which channels truly contribute to conversions
Alternative Tools: Windsor.ai, Triple Whale (for ecommerce-specific campaigns)
Related Article: Investing in AI Marketing Technology? 3 Areas With the Biggest Returns
2. AI for Predictive Analytics
Suggested Tool: Pecan AI
What It Does: Pecan AI is a tool that allows business intelligence professionals and analysts to create their own predictive machine learning models based on their own data sets, without needing to have coding or data science skills. It offers pre-built integrations that connect easily to many of the most widely-used data tools, and can even work with “messy” data — with automated processes that can detect and fix many of the most common problems in data sets.
Why It Matters: Marketers often rely on historical data to plan campaigns, but AI-powered predictive analytics forecasts early return on ad spend (ROAS) without having to wait a week or more. Pecan AI does this by analyzing your data and predicting customer lifetime value (CLV) and likely campaign ROAS within 24-48 hours. Instead of focusing on short-term campaign results, it can forecast what the campaign’s future value will likely be in one month to six months or more.
Pecan AI’s machine learning-driven predictive models can also assist marketers with challenges such as identifying likely-to-churn customers to target strategically, finding upsell and cross-sell opportunities, and scoring leads so revenue teams know where to best focus their efforts.
How It Works: Pecan AI builds custom machine-learning models easily (no machine learning knowledge required, only SQL skills). The tool can analyze customer behavior patterns and other signals in your data to predict disparate elements such as conversion likelihood, churn rates and revenue impact.
ROI Impact:
- Data-driven planning
- Reduced marketing guesswork
Alternative Tools: Black Crow AI (for sites on the Shopify platform), DataRobot
3. AI for Automated Marketing Insights
Suggested Tool: Looker Studio
What It Does: Formerly known as Google Data Studio, the free Looker Studio tool allows marketers to build customizable reports and graphs from connected Google data sources such as Google Ads and Google Analytics. You can also connect it to sources such as your own SQL databases, CSVs, social media platforms and other Google consumer products like YouTube and Search Console. The premium version, Looker Studio Pro, can also create AI-generated narratives and summaries to quickly give you insights from these reports. Additionally, Looker Studio’s AI-enhanced features include automated alerts, which notify marketers when certain key performance indicators experience unusual fluctuations, allowing for quick responses to optimize performance.
Why It Matters: Marketers often spend too much time creating reports. Looker Studio lets you build fully customized visuals of your data in seconds, complete with interactive filters and included annotations for faster insights.
How It Works: You connect Looker Studio to the data sources of your choice. From this data, Looker can create fully customizable, interactive reporting dashboards that visually display key performance metrics. The Pro version, Looker Studio Pro, incorporates AI-generated insights which highlight anomalies, trends and potential opportunities without requiring deep data analysis skills.
ROI Impact:
- Faster decision-making
- Reduced manual reporting workload
- AI-generated insights for smarter budgeting
Alternative Tools: Tableau AI, Microsoft Power BI with AI
4. AI for Personalized Customer Journeys
Suggested Tool: Persado
What It Does: Persado is an AI-powered content generation and optimization platform that helps brands create marketing messages that resonate emotionally with their audience. Using natural language processing (NLP) and deep learning, Persado analyzes past performance data to determine which words, phrases and emotions drive the best engagement.
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Unlike traditional A/B testing, which often involves trial and error, Persado’s AI predicts the most effective message variations before deployment, helping brands optimize content faster and with more confidence.
Why It Matters: AI-powered personalization drives engagement, but most brands struggle to scale it.
How It Works: Persado’s AI analyzes historical engagement data from emails, ads and web content to determine which language patterns and emotional triggers perform best. It automatically generates and tests multiple message variations to identify the most effective phrasing, tone and call-to-action (CTA). Over time, the AI refines its recommendations, continuously improving messaging effectiveness based on real-time customer responses.
ROI Impact:
- Increased open and click-through rates
- More effective product recommendations
- Higher customer lifetime value (CLV)
Alternative Tools: Jasper AI (for AI-generated content), Dynamic Yield (for personalization)
Related Article: Generative AI in Marketing: The Good, the Bad, the Unavoidable
5. AI for A/B Testing
Suggested Tool: Optimizely AI
What It Does: Optimizely AI is an advanced A/B testing and experimentation platform that helps brands optimize websites, ads and digital experiences in real time. Typically, A/B testing requires running multiple versions of content and waiting for statistically significant results, which can be a slow, manual process. Optimizely AI speeds up this process using machine learning, dynamically adjusting content and offers based on user behavior. By constantly learning from audience interactions, Optimizely AI removes the guesswork from experimentation, enabling brands to deliver the best-performing experiences faster.
Why It Matters: Traditional A/B testing is slow and manual, limiting marketers’ ability to iterate quickly.
How It Works: Optimizely AI automates and accelerates A/B testing by continuously adjusting content, offers and CTAs in real-time based on user interactions.
ROI Impact:
- Faster optimizations with real-time adaptive testing
- Higher conversion rates resulting from AI-driven recommendations
- Reduced reliance on manual testing, freeing up teams for other projects
Alternative Tools: AB Tasty, VWO (Visual Website Optimizer) (for small businesses)
Limitations of AI in Marketing
AI is fast becoming a necessity for marketers. Tools like the ones listed above can give marketing teams an edge, helping them work more efficiently and productively, maximize marketing spend impact and ultimately proving the value of their efforts.
However, a very important final thought: AI is a powerful tool, but it is not a strategy. While it can analyze data quickly, automate recommendations and more quickly help marketers optimize campaigns, AI lacks the deep understanding of your brand, customers and market nuances that experienced (human) marketers have. The most advanced AI can surface insights, but those insights still require human oversight and interpretation to ensure they align with your business goals and customer needs.
AI also doesn’t instinctively understand the complexities of your specific audience right away, unless you’ve fed it significant amounts of historical data. It learns over time. To get the most value from AI, marketers must guide it with clear data, well-defined goals and ongoing oversight. The best results come from a balance: leveraging AI for efficiency while applying human expertise to ensure its recommendations make strategic sense.
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