11 Ways in Which AI Will Transform Performance Marketing

From print ads to digital advertising, marketing has drastically evolved over the years. And it continues to evolve, with data-driven performance marketing becoming the cornerstone of success for modern businesses. 

But there’s a lot that marketers have to get a hold of, from learning the different platform algorithms to targeting, which often results in slip-ups. Missing out on crucial data can be damaging to achieving a higher ROAS.

It is difficult for businesses to cut through the noise and achieve the desired results from their marketing campaigns. This is where AI can help businesses enhance their performance marketing campaigns by improving targeting, personalizing ad creatives, foreseeing consumer behavior, and maximizing ROI.

In this guide, we’ll look at the impact of AI on performance marketing and the many ways AI helps businesses achieve significant success.

11 ways how AI is transforming performance marketing

There are several ways in which AI is enabling performance marketers to run high-performing campaigns. Here are the top use cases of AI we have noted:

1. Optimizing ad creatives 

Ad creatives rely on brand guidelines, industry norms, or personal design preferences, making it difficult for brands to crack a successful creative in the first go. It often leads to repetitive processes, where brands must go back and forth with their design team to find what works best for them. 

AI helps them with image analytics, measuring creative performance by assessing factors like colors, layouts, and visuals. It provides granular insights into what works best for the business as well as the audience and generates them accordingly, which helps brands optimize their ad creatives effectively.

CNNs (Convolutional Neural Networks) can be used to analyze images and videos related to marketing campaigns. This includes extracting insights from visual content, such as identifying products, logos, and user engagement in images and videos, which makes it easier for performance marketers to optimize for visually appealing creatives. 

For example, tools like Eacel.ai can diagnose your creatives and your performance while proactively alerting you of creative fatigue. It also helps generate high quality ads in minutes, as compared to the traditional way of optimizing that takes days to weeks of back and forth between teams. 

Traditionally, creative optimization has focused on quantitative factors like campaign types, bidding and targeting. The inability to dive into subjective factors of creatives led to missed opportunities to improve campaign performance.  

With AI, the long ignored part of performance marketing - the creatives - will see a surge in popularity as an area to improve to increase ROAS. AI is likely to learn, adjust, and learn again, growing your creatives’ impact on your through iteration.

2. Understanding customers better

AI enables a deeper understanding of customers, going beyond demographics by analyzing their past interactions and sentiments. This sort of AI can allow performance marketers to clearly and dynamically segment their audience for each campaign and message.

AI discovers insights about individual preferences, behaviors, and sentiments by digging data from various touchpoints, including social media, website visits, and purchases. This nuanced understanding allows businesses to personalize marketing efforts, tailor product recommendations, and anticipate customer requirements efficiently. 

Using entity detection technology, businesses can identify important information in conversations for future actions. They can automatically fill in customer details, like, name, address, and occupation. It can also gather feedback for its services and competitors to gain a competitive edge.

Further, machine learning models can help performance marketers predict future customer behaviors based on historical data. Performance marketers can leverage these predictions to tailor campaigns, focusing on high-conversion periods. 

22% of marketing professionals worldwide use AI with marketing automation to generate product and content recommendations and personalized email subject lines.

For instance, Spotify uses AI to understand users' music preferences and behaviors. After analyzing the user’s listening history, playlist creation, and interactions, it recommends music and personalized playlists via retargeting campaigns. This has helped the app increase their user retention and session times, also leading to higher conversion on their paid subscriptions.

3. Evaluate sentiment and engagement

Imagine investing heavily in ads to reach a wider audience, only to discover negative responses. AI is a savior here to detect sentiment trends across the wide net of data swiftly. 

AI tools can provide valuable insights into audience sentiment and engagement levels by assessing real-time social media comments, customer feedback, and other interactions using NLP (Natural Language Processing). 

This allows marketers to change their strategies promptly, addressing concerns of audiences sharing experiences in different languages, refining messages, and optimizing campaigns. AI is also increasingly helping brands with mass-scale campaigns manage their online reputation better. 

For instance, if you’re running a cultural campaign worldwide, AI enables you to evaluate the overall sentiment around it across different segments. This could mean mapping performance of the campaigns across demographics like age, gender, locations, and gathering insights that help you localize the campaign creatives to meet local sentiment. 

4. Finding the right platforms for cross-channel optimization  

Identify the platforms your target audience is primarily active on, be it any social media platforms or specialized platforms related to your industry. Looking at where your competitors are advertising can throw some light on which platforms are ideal and effective for your industry. Start with platforms that look promising and run small-scale ad campaigns on those platforms to test their efficiency, and then use AI to benchmark the results.  

Compare different ad creatives, targeting options, and messaging with the help of A/B testing and AI. Tracking key metrics of each platform, like click-through rates, conversion rates, cost per acquisition, and ROI, can be overwhelming for performance marketers. But with AI, marketers can consolidate the insights faster and derive actionables that help them re-allocate resources to the right channels and platforms. 

AI is also enabling performance marketers to create effective cross-channel campaigns with detailed audience profiles, insights on engagement levels, timing of engagement and the varying targeting ability across channels like Google, YouTube, Facebook, Instagram, TikTok and others. This helps marketers optimize cross-channel campaigns for maximum engagement, driving higher ROI from each platform based on its capabilities. 

For example, with the help of AI, you can identify channels that are the best at driving top of the funnel traffic for you, and those that are more optimized to generate leads. Marketers can then tie the two channel campaigns to create connected experiences that lead to faster conversions. 

Thinking a step further, it’s not too far into the future that there will be AI that will run ads across all platforms at different intensities, at different times of the day, and with different creatives and messaging to give you the highest ROAS. With multi-channel marketing taking the center stage, AI tools will be enabling performance marketers to keep up with nitty gritties of each platform.

5. Setting up better attribution models

AI-driven attribution models use machine learning algorithms to assess large datasets that contain customer interactions across various touchpoints. AI can help consolidate insights across website analytics platforms (Google, Adobe Analytics, etc), MMPs (like Branch), product analytics (Amplitude, Mixpanel, etc) and other brand touch point data to enable improved campaign success attribution. 

With AI, performance marketers can spot trends and connections to figure out which ads or marketing strategies are actually making people buy things. 

AI can analyze complex customer journeys, considering various touch points across different devices, channels and platforms. This analysis helps marketers understand the sequence of interactions that lead to conversions and optimize campaigns accordingly in real-time. 

Simply put, AI is making data-driven attribution possible. 

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6. Enable predictive analytics and optimization

Understanding customers’ behaviors and patterns, examining first-party data, and capturing strategic insights are much easier with the right AI tool. Businesses can optimize their campaigns to foresee the outcome of a customer taking a specific action in a better way with robust data analysis. This allows their campaigns to become more and more efficient gradually.

With AI’s ability to assess consumers’ past behavior, businesses can predict their future value to the business. This helps estimate a customer’s potential revenue generation over their lifetime, helping marketers prioritize their marketing efforts and allocate resources at the right places.

AI can quickly identify customer churn by analyzing various data points, like purchase history, engagement metrics, or customer feedback. This enables performance marketers to reach out to customers with remarketing and retargeting campaigns that are focused on re-engaging their interest, and nurturing it into intent. Brands like Uber have been able to reduce their user churn rate by integrating AI into not just app analytics, but how they re-engage their audience via paid campaigns.

7. Leverage dynamic pricing 

AI helps businesses optimize real-time pricing strategies to increase revenue and profitability. AI algorithms can analyze vast datasets about what people want to buy, competitors' pricing, and how customers behave when they engage with ad campaigns or make purchases from the brand. 

This enables businesses to capture maximum value from each transaction and performance marketers to highlight the value in future campaigns. AI can also predict fluctuations in demand, helping businesses make proactive pricing adjustments to capitalize on opportunities and avoid risks by over-promising or under-promising through marketing campaigns. 

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8. Generate optimized ad copies and landing pages 

Something a bit more obvious. We’ve all used ChatGPT to create or fine-tune an ad copy or landing page content. You will receive no judgment from us. 

Creating compelling ad and landing page copies takes a lot of time and effort. But the next step is for AI to use advanced algorithms to analyze data and create content that is tailored to a specific audience.

These algorithms can identify key themes, language patterns, and emotions that resonate with the target audience. In fact, content generation tools built with natural language processing, can also help performance marketers localize their ad campaigns and landing pages faster.

AI can efficiently produce multiple variations of ad copies as well as landing pages through automated processes and optimize messaging for higher impact and relevance. This helps marketers create engaging ad assets faster, giving them the ability to scale the targeting of a campaign much faster.

9. Enable advanced campaign targeting 

AI combs through a lot of data to find patterns and trends like user behavior, demographics, online interactions, websites people visit, what they buy, etc. This helps marketers know their audience better and create narrowed down audience segments that can be personalized for. 

This means ads are seen by people who are most likely to buy, which helps boost the campaign efforts and makes them work efficiently.

47% of marketers in the U.S., U.K., India, and Canada said they trusted AI with ad targeting.

For instance, LinkedIn uses AI-driven targeting capabilities to help businesses connect with professionals on the professional networking platform.

With features like Matched Audiences and Interest Targeting, advertisers can target users based on their job titles, industries, skills, and interests. LinkedIn's AI algorithms analyze user profiles and interactions to optimize ad targeting and maximize campaign effectiveness.

There are also clustering techniques like K-means and and others where brands can leverage advanced customer segmentation with no predefined category to make their targeting more effective. Tools like Scikit-learn are making it easier for marketers to tap into similar tactics.

10. Proactive competitor analysis 

Another key aspect of AI in performance marketing is being able to proactively monitor and benchmark against competitors. AI can automate the collection of data from various sources -  including competitors' websites, social media platforms, ad networks, and other relevant channels. This includes data on ad creatives, keywords, audience targeting, and key engagement metrics that impact business outcomes.

This insight can help performance marketers identify strengths, weaknesses and opportunities to reach their target audience with better campaigns. Performance marketers can also leverage AI to respond to campaign engagement around themselves and competitors, faster, keeping the narrative in complete control as the ad expands to a wider target audience.

11. Real-time bidding (RTB) optimization

Real-time bidding (RTB) optimization with deep learning involves leveraging advanced AI and neural network models to enhance the decision-making process in programmatic advertising.

Deep learning models can be trained to predict the likelihood of a user clicking on a particular campaign (click-through rate prediction) or converting after clicking (conversion rate prediction). These predictions can be used by performance marketers to bid more aggressively on impressions that can lead to desired business outcomes.

Why use AI in performance marketing

As the digital landscape grows by the day, the need for businesses to be where their audience actively engages, is becoming overwhelming. The traditional ways to manage performance marketing campaigns are no longer effective and manually tracking data is beyond manageable.

That’s where fast-scaling performance marketing teams can be seen using AI extensively in their processes. Some of the key benefits of AI include:

• Processing vast amounts of data to identify patterns, behaviors, trends, and crucial insights.
• Personalizing messages, offers, and recommendations based on individual preferences and history.
• Optimizing marketing campaigns like ad targeting, bidding strategies, and content delivery for better performance and higher ROI.
• Predicting future trends, customer behavior, and market dynamics, helping marketers tweak their strategies proactively.
• Automating repetitive tasks which saves time and effort and gives marketers time to focus on strategic activities.
• Analyzing market conditions, competitor pricing, and consumer demand to adjust prices for maximum profitability.
• Examining conversations, reviews, and other valuable data from social media and other sources to refine their messaging and improve customer satisfaction.
• AI algorithms can detect patterns indicative of fraudulent activities, protecting marketing budgets from click fraud or other malicious activities.
• Optimizing marketing and advertising budgets per channel, platform, audience segment and other targeted parameters. 
• AI brings in time and cost efficiency with automation of repetitive tasks, data analysis, and campaign optimization. 
• AI facilitates seamless integration and coordination across various marketing channels, which helps deliver a unified and consistent customer experience.

According to surveys, the adoption of AI across digital marketing departments, has been steadily increasing. Of the 4,500 respondents surveyed, 37% of those working in marketing and advertising indicated that they use AI.

Wrapping up

AI is transforming how performance marketers engage with data and adapt their campaigns to audience responses. With AI, marketers can analyze demographic, behavioral, and contextual data to personalize campaigns for maximum impact. By understanding how audiences interact with content, AI helps optimize messaging, creative elements, and platform choices to resonate more effectively.

Tools like Eacel.ai use advanced algorithms to analyze audience data and automatically generate optimized creative variations. It allows marketers to deliver compelling content that resonates with their target audience, driving better campaign performance.

Book a demo today to witness the power of AI-powered performance marketing!