3 Generative AI Marketing Use Cases That Aren’t Copywriting

How is your marketing team using generative AI? Here are the results of a survey I conducted earlier this year:

Although this survey focuses on email marketing professionals, the results align with trends in the broader marketing landscape. But in my experience, copywriting is not the most effective use of generative AI.

Here are three areas where generative AI can really add value: If your marketing team wants to get the most out of AI, start here, not in copywriting.

Use case 1: Improve your marketing basics

Your marketing team should have foundational information for every campaign they create, such as:

• Analysis of features, advantages and benefits (FAB).
• Potential obstacles and solutions.
• Target audience descriptions.
• Price details.
• Offers.

Essentially, this is the critical information that forms the basis of the creative brief.

Case study

Earlier this year, I was working with an academic client and needed a Features, Benefits, and Benefits (FAB) analysis to obtain an MBA. I got my MBA (from Georgetown University, Hoya Saxa!), so I could have created this from my own experience. However, I decided to collaborate with the custom “marketing strategist” GPT I created to save time.

I quickly wrote a short, low-detail FAB analysis, compiled a list of relevant web pages from the client site and third-party sites about the value of an MBA, and shared it all with the AI. Next, I asked the custom GPT to improve and expand on the FAB analysis I had provided.

In less than a minute, I had a list of 12 high-quality features, each with advantages and benefits. I looked at it and requested some adjustments to the GPT, but the process was much faster than it would have been without the AI.

The value brought by AI

Many people talk about the value of generative AI in terms of the amount of information it ingests. For me, it’s in his ability to quickly ingest and synthesize information. We direct him to specific, relevant information and ask him to digest it, identify what is important to the project, and deliver the result in a usable format.

For this use case, generative AI increased my productivity while maintaining the quality of the deliverable.

Dig Deeper: Data analytics and market research top the list of AI use cases

Use case 2: Receive personal feedback on your marketing campaigns

This use case is more fun than the first. Generative AI can act like a lead or customer and give your marketing team feedback on your campaigns to optimize them as they are created.

Case study

Earlier this month, I created a custom GPT “persona” and named her Sarah. I asked for feedback on FABs, my custom GPT “marketing strategist” and I had created a sample mail order barbecue for a marketing campaign that would serve eight people for holiday entertaining.

Sarah liked most of them, but she had four suggestions for improvement.

Some of his comments were not helpful. For example, she suggested that we expand the scope of FABs from winter holiday entertainment to various occasions, such as birthday parties and summer get-togethers. But this is specifically a winter holiday campaign, so we didn’t take that into account.

Some of his comments were very helpful. For example, FABs said the barbecue was premium, authentic and “best” in its class. Sarah asked for more details on why this happened. She suggested adding information about unique cooking methods, specific ingredients and other elements that would strengthen these claims.

I passed this information on to my personalized “marketing strategist” GPT, who revised the FABs to address Sarah’s comments. Next, I submitted the revised FABs to Sarah to ensure we addressed her concerns.

The value brought by AI

In this case, my personalized GPT “persona” identified a blind spot in the FABs: a lack of support for some of our assertions. It’s always good to get a second set of eyes on something. Using an AI for this purpose is more cost-effective than using a real person, and it allows us to create a feedback source based specifically on our target audience.

For this use case, generative AI gave me feedback from my target audience to optimize my campaign as we developed it.

Dig Deeper: 6 Ways to Use Generative AI for Your Marketing

Use case 3: Create tables and graphs from raw data in spreadsheets

If charts and graphs make up a large part of your marketing team’s work, this use case can be useful. But this makes me sad, because I love creating tables and graphs in Excel.

Case study

I started using AI to create the standard charts and graphs I use to report campaign performance. It’s quite easy. I simply upload a spreadsheet to my custom “data scientist” GPT and request the specific tables and graphs I need.

This GPT is designed to follow the specific configuration instructions I provided:

• Metric: A document describes key metrics, how to calculate them, and includes sample data with calculations.
• Examples: Example tables and graphs serve as templates for the desired appearance of the result.
• Branding: A brand guide, including company colors and logo, ensures consistency of visual elements.

I download a spreadsheet of raw data and request the tables and graphs I need by name. I always make sure the column names match the provided metrics documents; if discrepancies arise, the GPT will seek clarification.

I always check the calculations. Until now, they have always been right. Although accurate, the GPT tables and graphs are not as visually appealing as I would like. As an example, here is the GPT version of the bar chart that appears at the beginning of this article:

Do you see what I mean? I’ve tried to provide creative guidance to GPT to get closer to what I can achieve with Excel, to no avail.

The value brought by AI

I wish AI was really good at this kind of rote work. It does the job quite well and faster than me, but not as visually. Hopefully his creative output will improve with time.

For this use case, generative AI saves me time by handling rote work that I would otherwise have to do myself.

Dig Deeper: How to use generative AI in writing an A/B testing program

Using generative AI beyond copywriting

AI is this year’s “bright, shiny thing.” Instead of buying into the hype or being completely skeptical, your organization should encourage your marketing and other internal teams to find practical, realistic tasks where AI provides value.

Despite what 83% of email marketers do, I don’t see copywriting at the top of the list. The best way to progress through the AI ​​learning curve is to experiment and share our experiences.