How to Measure ROI with AI Marketing

AI has captured everyone’s attention—including B2B marketers.

According to ON24’s report on the State of AI in B2B Marketing in 2024, 72% of executives are asking their marketing department how they use AI.

Therefore, it’s no surprise that 87% of execs are using or testing AI in their marketing. Furthermore, 84% of marketing managers are expected to integrate more AI into their strategies.

The question I tend to ask my clients is, “If you do put more budget into AI, how will you measure your ROI with your AI efforts?”

I’m not going to walk you through developing and carrying out an AI marketing strategy here—you can check out my book The Modern AI Market in the GPT Era to learn more about that in depth.

There are seemingly endless places generative AI can fit in to boost ROI, whether to help create content, strategize, analyze data, and so on.

But you need to have a strategy and human marketers at the center to make it work.

Here are three ways to quantify by capitalizing on AI: as an efficiency gain, marketing as a cost reduction, and as a revenue impact.

1. AI as an Efficiency Gain

The easiest way to calculate efficiency is time savings. AI-powered content generation can create marketing materials at scale, and it can also quickly optimize for search engines and social media platforms.

Having AI create content as the initial draft can save copywriters so much time. However, you will absolutely still need copywriters to make sure it has a human touch, is on brand with a personalized flair, and does not contain any inaccurate information.

Writing a blog post or emails can take 3-4 hours. With AI, you can brief an LLM (large language model) and ask it to come up with several write-ups. The whole process may take less than one hour with several rounds of quick edits.

You can calculate the hours of savings based on the number of emails and content pieces you plan to craft. Say you send 30 emails and 50 blog posts out based on your various campaigns per year. That can be a certain amount of hours saved as an efficiency gain.

You need to understand how your marketing department uses ChatGPT or other LLMs to estimate hours saved by normalizing over one year. Again, a projected time savings is fine as long as you can confirm that with content creators or the team who use AI for content creation.

2. AI as a Cost Reduction

From a management perspective, cost reduction in enterprise organizations tends to be measured by headcount or pure budget reduction. Can you reduce the number of heads needed for content and design creation by leveraging AI?

Before making that decision, you need to carefully consider the pros and cons of trading (laying off) a human with AI.

AI-powered customer service chatbots on websites or through SMS have become essential for elevating customer engagements and streamlining communication. By handling routine inquiries and transactions, chatbots significantly reduce the workloads of customer service teams.

Then, it gives you the option to either reduce the headcount in the customer service team and/or free the team up to focus on more complex queries and strategic initiatives.

Another way to evaluate the cost reduction is to automate your workflows with AI. For example, rather than your BDRs (Business Development Reps) manually routing the qualified leads to different sales teams, you can use AI to route the leads to different salespersons based on routing criteria you set up.

It frees up a BDR’s time to make more calls, which can be counted as efficiency gains by making more calls or boosting revenue impact through identifying more prospects.

The key is to be conscious of where you’ll place AI to help you. Then, quantify the cost reductions based on automation or workload reduction.

3. AI as a Revenue Impact

Using AI to analyze vast amounts of customer behavior, preferences, and market trends can provide valuable insights which inform marketing strategies, validate assumptions, and drive real results.

For example, AI-driven predictive analytics can forecast future sales trends and identify high-value customers, allowing marketers to tailor their campaigns to meet evolving consumer demands. This level of foresight could directly impact revenue.

Another option to impact revenue is AI-powered segmentation which enables marketers to create personalized experiences for individual customers.

By doing so, it may increase the number of MQLs or the MQL to SQL conversion rates or deal won closure rate. You can look at the conversion or deal closure rate pre-and-post-AI integration to quantify the revenue contribution.

You can also take segmentation one step further by evaluating past prospects’ engagement or behavior data, segment them further accordingly, then use look-like customer data to predict their likelihood to buy from your business.

Depending on the algorithms and the quality of your customer data, AI may not provide you the perfect answers, but it certainly can give you recommendations and explanations why it sees prospects’ future behaviors. The information, along with salespeople and your judgment, will guide future sales engagement and tailor marketing outreach.

You should evaluate AI’s revenue impact based on sales and marketing success metrics.

Ask Yourself: Is AI Marketing Worth the Investment?

For AI to work well and efficiently for you, you need to spend money first. You can measure AI’s ROI against your AI investment.

You can also treat AI investment as another item of your martech budget, measuring the efficient gains and revenue impact separately.

In many cases, you may not initially see AI’s ROI until your teams are sufficiently using AI, the workflows are tested, and the teams are fully revamped.

It takes time, budget, and resources to implement the proper transformation to capture the ROI you envision.

As you integrate AI into your martech stack through workflows and automations, you need to give some thought on how to measure AI’s ROI in relation to your marketing organization structure, headcount tradeoffs, budget allocation, tech stack, and your team’s adoption pace.

AI has the potential to drive significant impacts on B2B digital marketing. Whether those impacts are positive or not are up to how effectively you implement AI into your overall marketing strategy.

Feel free to reach out to me if you have any questions about AI marketing!

Check out the Modern AI Marketer Series: In GPT Era and AI Promps.