How to Measure AI-Generated Content ROI: Experts Weigh In

How do you measure the ROI of your AI-generated content? Here is what 8 thought leaders have to say.

1. Assess SEO Rankings and User Interaction
2. Gauge Engagement as a Success Indicator
3. Analyze Impact and Efficiency Gains
4. Utilize Engagement Heatmaps for Insight
5. Calculate Incremental Revenue Versus AI Costs
6. Benchmark Performance Before and After AI
7. Monitor Analytics and Compare Resource Savings
8. Measure Incremental ROI Across Implementation Stages

1. Assess SEO rankings and user interaction

AI-generated content is mostly acceptable, but for the search engine, it presents a significant challenge. If you check the search engine rankings, you will notice that the best content still comes from human input. And if you are using AI-generated content to increase traffic on your website, you simply see the ROI.

Content that ranks on Google is the content with a high ROI, but it is more than just high traffic. Also, there are tools like Hotjar that will show you how users interact with your website, so you can learn from them and adjust your content to improve the user experience.

All in all, if it is web content, just focus on the user experience and see if the content is ranking on Google. If it is not ranking, then you probably need to adjust your content.

Burak Özdemir, Founder, onlinealarmkur.com

2. Gauge engagement as a success indicator

Most often, measuring the performance of AI-generated content is challenging due to the lack of established KPIs. However, in my opinion, the most crucial metric to consider is engagement. How many people are consuming the content?

How many are leaving comments or sharing it with others? If you’re witnessing significant engagement, it’s a strong indicator that the content is resonating with your audience and achieving its intended purpose.

Engagement serves as a reliable proxy for the content’s effectiveness. It demonstrates that the content is stimulating interest, sparking conversations, and driving interactions with our brand. From a business perspective, increased engagement can translate into higher website traffic, improved brand awareness, and boosted sales.

Luciano Colos, Founder and CEO, PitchGrade

3. Analyze impact and efficiency gains

Measuring the ROI of AI content boils down to two main areas: impact and efficiency. The Impact page tracks engagement metrics such as shares, clicks, conversions, and revenue attributed to your AI-generated content. Compare this to traditional content to see if AI improves your key performance indicators.

Efficiency measures the time saved using AI tools for creativity, research, writing, and more. Quantify this time savings and compare it to the cost of your AI software to assess the economic benefit. By combining impact and efficiency analysis, you get a complete picture of the ROI of your AI content, showing whether it can drive engagement and save valuable resources.

Fahad Khan, Digital Marketing Manager, Ubuy India

4. Utilize engagement heatmaps for insight

In measuring the ROI of our AI-generated content, I often turn to engagement heatmaps. These are incredibly insightful. For instance, we recently launched a campaign featuring AI-created workout guides. The heatmaps revealed that our audience spent more time on sections detailing personalized workout routines than on generic fitness tips.

This was eye-opening. It told us that our followers prefer content that feels more tailored to their individual needs. By focusing our AI to generate more of such content, we saw an uptick in engagement, customer loyalty, and brand advocacy. It’s fascinating how such data-driven insights can steer content strategy in a direction that resonates more deeply with our audience.

Jay Barton, CEO and Founder, ASRV

5. Calculate incremental revenue versus AI costs

You can calculate the ROI of AI-generated content the same way that you calculate the ROI of producing other content for performance-marketing campaigns. Divide the incremental revenue generated by the content by the cost of the AI content to find the return on investment.

Eric Novinson, Founder, This Is Accounting Automation

6. Benchmark performance before and after AI

Measuring the ROI of AI-generated content can be done through benchmarking and comparative analysis. Basically, this involves comparing data from before and after you start using AI for content creation. You look at how your performance metrics have changed. Then, you benchmark these results against what’s typical in your industry or with what your competitors are doing to really understand the impact on ROI.

To get specific, in measuring the ROI of AI-generated content, I first collect key metrics like engagement, traffic, and conversion rates before bringing AI into the picture. After we’ve started using AI for content, I track these same metrics again to see any improvements or changes. This comparison gives a clear picture of the impact AI has had.

I also compare our performance with industry standards or competitors who might not be using AI for content. This helps me see how much of an advantage AI is giving us. Finally, I look at cost savings from the AI, like less time spent on content creation, and consider how the AI’s content quality affects customer engagement and satisfaction.

Lucas Ochoa, Founder and CEO, Automat

7. Monitor analytics and compare resource savings

When we’re looking at the ROI for our AI-generated content at Content Whale, it’s really about two big things. First, we’re always keeping an eye on the numbers—how’s the content performing? This means diving into our website analytics to see stuff like how many people are visiting, how long they’re sticking around, and if they’re taking actions like signing up or buying something. It’s all about seeing if the content is really hitting the mark with our audience.

Then, there’s the cost side of things. Using AI to whip up content can be a real time-saver, and time is money. We compare how much effort and resources go into AI content versus the old-school way. Plus, AI lets us cover more ground faster, which is a big win.

So, we’re not just looking at the immediate savings but also how this scales up over time, especially with our SEO game. In short, it’s a mix of checking out the direct results and appreciating how much smoother and faster the whole process gets with AI.

Bhavik Sarkhedi, Growth Head and CMO, Content Whale

8. Measure incremental ROI across implementation stages

A useful approach I recommend for measuring the ROI of AI-generated content is Incremental ROI Measurement. This means dividing the AI implementation into separate stages, so you can track the ROI of AI across different periods. This method is great for showing progress and confirming that the investment is paying off at each stage.

To do this, I start by setting clear benchmarks for each phase of AI implementation. This involves identifying specific metrics, like engagement rates or content output, that I expect to improve with AI. As we progress through each stage, I compare the current results with these benchmarks to see how much impact the AI is having.

This step-by-step analysis not only gives a clear picture of the ROI at each phase but also helps in making any necessary adjustments to maximize the benefits of AI. Finally, I sum up the improvements from each stage to understand the overall ROI of the AI-generated content, ensuring that our investment is yielding tangible results.

Precious Abacan, Marketing Director, Softlist

What have we learned?

AI powered tools that help us create high-quality content are invaluable in helping businesses reach their target audience. However, many people are reluctant to invest in artificial intelligence without being able to predict or accurately measure the return on investment.

These 8 thought leaders have shed light on how we can be more confident in using AI-powered content tools. If you analyze data, keep track of the time-consuming tasks that are taken off your hands, and analyze user behavior, you’ll be able to get a good idea of the ROI of your new content creation process.