Supercharge personalized customer marketing with AI
Generative AI has assimilated into our lives. By this point, most marketers have weighed its benefits, suffered its drawbacks, and found a balance with genAI for daily workflow — 68% of marketers use AI daily at work. Any given week involves us searching for potential genAI solutions to our problems.
If you’ve landed here, you’re probably searching for more solutions. Because many of us are currently working with AI, the question is how other marketers use it to stay ahead. We will walk through use cases for genAI in customer marketing, bearing in mind that the end goal for any AI project is a more leisurely life — for marketers and customers.
First, let’s clarify what genAI is and what it’s not. This can help you decide whether genAI is the right tool for your job.
What is genAI?
Generative AI is the subset of AI that uses training from massive datasets to create new content: pictures, videos, writing, and so on. These gigantic datasets give genAI its creativity (to an extent). The AI uses training to synthesize information from a mass dataset to make something new. Voila!
Traditional AI, on the other hand, is built to recognize patterns and react to those patterns based on a predefined ruleset. Think predictive analytics, recommended products, decision trees for chatbots, and the like. Traditional AI has been a piece of many software tools, products, and websites for years.
The brief history of genAI
Generative AI isn’t brand new. Chatbots have been around since the 1960s, and plenty of modern tools appeared as genAI novelties in the 2010s — remember Cleverbot?
While genAI didn’t take off in its early days, the current information age means LLMs have the entire web to use as training data (though more on the ethical implications of this later).
That’s why 2022 was a big year for genAI with the release of ChatGPT and DALLE 3. It caught on in early 2023, and, since then, every corner of tech has been wondering how best to use it. The global generative market is worth $44.89 billion, and plenty of opportunities exist to make — and save — money.
Why are a majority of marketers using genAI?
In short, genAI makes some processes easier. But as you may have discovered through experimentation, it can also make work harder. That’s why it’s essential to lean on other marketers to find effective use cases.
What do marketers see in genAI? It has some key benefits.
Marketing ideation done quickly
All marketing requires research. GenAI pulls from a dataset with thousands or millions of sources to help us brainstorm. Since genAI excels at synthesizing information from multiple sources, it’s a great place to ideate.
Have you heard of rubber duck debugging? A programmer explains their code line by line to a rubber duck. Just having the cute fella to talk to solves many problems with code.
ChatGPT has become a rubber duck debugger for marketers, but one that quacks back. It can give you an idea. You can throw out parts you don’t like or throw them out altogether, but it’s gotten the ball rolling by putting your thoughts into words — which can be extremely helpful when brainstorming new marketing ideas and campaigns.
Improved efficiency
54% of companies report that AI has improved efficiency and reduced cost issues. We’ll get to the cost element in a minute, but it’s not hard to imagine why genAI makes simple tasks more efficient.
GenAI can reduce busy work; it’s like a personal assistant that writes first drafts, marketing copy, campaign strategy ideas, and more. Marketers save 2.5 hours a day overall with AI tools. While it still needs human oversight, genAI makes work more efficient and less tedious for us.
Budget allocation
GenAI improves efficiency and reduces labor costs. Less time spent on your part cleaning up a spreadsheet or prepping content means less salary a company pays for that work.
This frees up your budget for other pressing concerns, allowing you to restrategize, knowing some simple tasks can be automated.
Where to use genAI in customer marketing
Where are savvy marketers making use of AI? They’re using it in places that automate time-consuming tasks without cutting corners. These are some of the ways genAI can help you with customer marketing.
Content creation
When we talk about genAI, content creation comes to mind first; 76% of marketers are using genAI to create content. For retail brands, this means generating personalized content across multiple channels. Here's how customer marketers are using it:
- Email campaigns segmented by purchase history ("Hey sneakerheads, check out our latest drop")
- SMS notifications customized by browsing behavior ("Those jeans you viewed are now 30% off!")
- Push notifications based on location ("Your nearest store has 3 items from your wishlist")
- Social media ad copy targeted by customer interests ("Athleisure lovers: Meet your new workout essential")
- Product descriptions that adapt to different customer segments
The key is using genAI as a starting point, then refining the output to match your brand voice and customer needs.
Customer chatbots and conversational AI
A bad chatbot does more harm than good, but 41% of customers prefer brands that use AI in their customer experience, and that number is growing.

By this point, many consumers are used to AI chatbots being available to usher in new customers or troubleshoot common problems. They can bypass these systems if they prefer to speak to a human. The worst issues arise when a chatbot can’t solve their problem, and there’s no human to speak with.
It’s worth seeing if a chatbot entices users to speak with someone from your team!
Expedited data analysis
53% of marketers use AI for data analysis, and retail brands are finding it particularly valuable for understanding customer behavior and campaign performance. For instance, you can ask genAI to:
- Analyze which product categories drive the highest customer lifetime value
- Identify patterns in customer churn across different segments
- Compare campaign performance across channels ("Show me which email campaigns drove the highest conversion rates last quarter")
- Spot seasonal trends in purchase behavior
- Track customer engagement metrics across different demographic groups
Many genAI tools can handle these tasks quickly. Simply upload your campaign data or customer metrics and ask specific questions like "Which customer segments showed a 20% increase in repeat purchases?" or "What time of day did our push notifications perform best?"
Customer research
GenAI makes customer research easier. You can ask it to help you create surveys or summarize their findings. SurveyMonkey is one of the many survey tools that’s built this feature into its product!

The same goes for persona research and help with customer journey maps. GenAI usually only provides the basics. Like the data analysis above, you can use genAI to look at CRM lists and customer spreadsheets to extract insights quickly. It can save you hours combing data and building pivot tables.
Content personalization
Give GenAI your personas and customer journeys to ask for its help with personalized messaging. AI can tailor emails, ad copy, and even text messages depending on who you’re speaking to.

Check out this conversation I had with ChatGPT on writing SMS messages for my hamster wheel company.
Using genAI for positive brand reputation
Start small
Like all data-backed marketing decisions, run some small tests to see if you can prove the value of genAI. Choose one tool and consider how to use it! From there, you can upgrade to paid tools that specialize in that aspect of generative AI.
Use secure tools
Have you heard of the chatbots that serve users private customer information? Be sure your technology is secure, and don’t give AI access to certain private or customer information unless you’re sure it is.
Keep overhead in the loop
Sometimes, you’ll need to walk eager supervisors through what genAI can and can’t do for customers and the team. The best way for them to learn is to show them, so communicate your genAI discoveries early and often.
Mandatory disclaimer: When genAI isn’t appropriate
It’s important to note a few things about genAI that remind us to tread carefully. First, genAI content isn’t copyrightable. Because of this, we shouldn’t use it to create key branding content like landing page copy, sales enablement assets, and other content we expect to own.
Another issue is that AI still suffers from hallucinations and biases. Hallucinations make content inaccurate — AI aims to please and will hallucinate facts to support points if you seek them.
The biases are based on the data from which it’s trained, meaning it can perpetuate these biases from what it’s learned. These can damage your brand, so you should fact-check everything and run AI work by multiple people to catch bias.
Another issue is creating consistency with genAI, ensuring the whole team understands how and when to use it. For this, an ounce of prevention is worth a pound of cure. You can avoid the problem by sharing AI work and building a content plan for where and when AI is appropriate.
Conclusion
The potential for generative AI is exciting, and it can mean a better customer experience when we marketers use it wisely. So, the next time you have a tough project to tackle, ask yourself: how can AI help? Spending time workshopping new ways to streamline tasks will save you time in the future. Let’s embrace a future with more AI to come!