How Brands Can Capitalize on GenAI to Improve Marketing ROI

It’s amazing to witness OpenAI’s GPT (generative pre-trained transformer, a large language model), as well as ChatGPT, take the world by storm.

In addition to answering any number of questions, ChatGPT can also provide insightful recommendations, create powerful content through writing and design and analyze data with precision. The global population was so taken by its capabilities that ChatGPT, in particular, reached 100 million users in just two months; for context, it took TikTok nine months and Instagram 12 months to accomplish these same numbers.

Many marketers are using ChatGPT (or Microsoft’s Copilot, Google’s Gemini, Anthropic’s Claude, etc.) to “chat” with LLMs (large language models) and accomplish the following: 

• Write long- and short-form content 
• Create plans and campaigns 
• Answer marketing-related questions 
• Create buyer personas 
• Generate graphs 
• Summarize research findings 
• Analyze campaign findings 
• And more… 

So, what about marketing ROI? Can AI impact your marketing ROI? And can it be measured?

Here are three ways to quantify the impact of AI on your business.

AI as an efficiency gain 

The easiest way to calculate efficiency is through the amount of time saved. AI-powered content generation can create marketing materials at scale! It can also optimize content for search engines and social media platforms quickly.

Having AI create content as an initial draft can save copywriters an impressive amount of time. However, you may still need human copywriters to review the material and make sure it has that magical bit of warmth that will make readers feel connected and invested. It’s also important to have quality control in terms of making sure things stay on brand with a bit of personalized flair peppered in.

Writing a blog post or a dedicated email can take three to four hours. With AI, you can brief a bot and ask it to come up with several options. The whole process may take less than one hour. Truly incredible stuff! 

You can calculate the hours saved based on the number of emails and content pieces you plan to craft. Say you send out 25 marketing emails and publish 30 blog posts on average every year. That can add up to a significant number of hours saved, translating to a healthy efficiency gain for your organization. 

Pro Tip: You need to understand how your team uses ChatGPT or other AI chatbots to estimate the hours saved by normalizing usage over the course of one year.  

AI for cost reduction 

From a management perspective, cost reduction in enterprises tends to be measured by headcount or pure budget reduction. Can you reduce the head count needed for content and design creation by leveraging AI? But before making that decision, you need to carefully consider the pros and cons of swapping a human with AI.  

Chatbots on websites or SMS have become an essential tool for elevating customer engagement during their buyer journey. By handling routine inquiries and transactions on social media, chatbots significantly reduce the workloads of social media teams. Then, you have the option of either reducing the headcount of your team or freeing up employees to focus on more complex queries and strategic initiatives.  

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

Pro Tip: The key is to be conscious of how you’ll leverage AI to cut down expenses. Then, quantify the cost reductions based on the amount of time and money saved through automation or workload reduction.    

AI as a revenue generator 

Using AI to analyze vast amounts of data pertaining to customer behavior, preferences and market trends can provide valuable insights that inform your marketing strategies, validate assumptions and drive tangible 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 revenue-impacting option is AI-powered customer segmentation, which enables marketers to create personalized experiences for customers. As such, it may increase the MQL to SQL conversion rate or deal closure rate. You can quantify the revenue contributions by measuring the increase in conversion or deal closure rates after implementing AI.   

You can also take segmentation one step further by evaluating past prospects’ engagement or behavior data, segmenting them accordingly and then using lookalike customer data to predict their buying patterns.  

AI may not be accurate 100% of the time, but it certainly can give you recommendations and explanations as to prospects’ potential future behaviors. That information, along with the sales agents and your judgment, will help guide your sales engagement strategy and tailor marketing outreach.  

Pro Tip: Evaluate AI’s revenue impact based on sales and marketing success metrics.  

In summary… 

As we integrate AI into our martech stack, workflows and even consider headcount tradeoffs, it’s important to give some thought to measuring AI’s ROI in relation to marketing organization structure, budget allocation, tech stack and even your team’s adoption pace. Also, bear in mind, it takes time, budget and resources to implement AI properly to capture the ROI you envision.