AI Use Cases in Marketing

Cameron Welland
piexchange
Published in
5 min readJun 6, 2023

As marketers, we are constantly looking to stay ahead of the curve, to get an edge on our competition.

It’s no wonder marketers are making full use of the abundance of AI tools available, to do tasks faster and more accurately than previous methods.

In this blog, we’ll go over some powerful AI use cases in marketing. Included will be both traditional machine learning use cases which makes predictions on a given set of data, and generative AI use cases which makes new data in the form of text, images etc.

If you find this interesting, you might also like checking out my list of the 10 best AI tools in marketing.

AI Use Cases In Marketing

Content Generation: Stopping writers block

I get it, sometimes writer’s block can strike, and progress all of a sudden comes to a screeching halt. But AI is here to help, and recently it’s stepped up its game in writing content.

At this point, everyone’s heard about ChatGPT powered by large language models (LLM’s), and how it can whip up blog posts, social media captions, ad copy, and pretty much anything else a marketer could ever need.

However, before you start blindly copying and pasting, large language models (LLM’s) like ChatGPT or Jasper AI aren’t infallible, they can be inaccurate and make mistakes.

But these tools are ready to churn out content at lightning speed, so as long as you’ve done your research, have precise prompting and have a thorough editing process, they can be a great starting point to get you going.

Search Engine Optimization: Writing the right stuff

SEO is a cornerstone of digital marketing, and although it takes time to get going, the consistent free traffic to your website from search engines, is very powerful to a marketer.

AI-powered SEO tools can co-pilot your SEO strategy, doing automated keyword research for you, finding holes in your current strategy, and pinpointing most relevant and impactful keywords for your website.

AI helps on-page SEO too.

Either by rapidly generating optimal titles and meta descriptions based on the content, or by suggesting improvements to the content in order to improve readability and structure, improving reader engagement.

AI tools have the potential to skyrocket your search rankings… and if you’re lucky, might even help you land you that #1 spot.

Competitor Analysis: Keeping tabs on your rivals

As marketers, we like to keep an eye on what the competitors are up to.

Don’t get me wrong. Too much focus on insights about rivals can leave your strategy reactionary, and will leave you a step behind.

But learning from competitors marketing strategies such as where they’re advertising, or what keywords their new content is targeting can be incredibly useful.

AI powered competitive analysis tools can perform faster, and analyze far more data sources, constantly monitoring and capturing the competitive landscape far more efficiently and accurately than manual methods.

This allows marketers to make informed decisions about how to position their brand, create more effective acquisition strategies and identify opportunities and threats in the market.

Customer churn prediction: Keeping customers hooked

Customer retention is one of the most vital metrics in business growth. No matter how many customers you’re acquiring, if they’re leaving at the same rate, the business won’t grow.

In the game of customer retention, predicting customer churn is the secret weapon.

AI models are the most effective method to predict customer churn ahead of time. By analyzing customer behavior, engagement patterns, and other clues, they can detect the warning signs of a potential churner.

Armed with this knowledge, marketers can proactively swoop in with targeted offers and direct communication to keep your customers from jumping ship, keeping business growth on an upward trajectory.

If you’re ready to start but don’t know where to start, the team here at PI.EXCHANGE has purpose-built a new customer churn template for the AI & Analytics Engine, no code required.

Customer lifetime value prediction: Peering into the crystal ball

You don’t need a crystal ball to predict the total monetary value of a customer for your business.

By crunching historical customer data and behavior, AI models can predict the lifetime value of your customers.

This guides marketers to focus on nurturing those high-value customers who are worth their weight in gold. In addition, marketers can analyze the consistent traits among them and adjust their marketing strategy.

One of the most sure-fire ways marketers can increase CLV is to create a strategy to win back lost customers, feel free to have a read of my blog on the topic!

Customer segmentation: Giving the VIP treatment

One-size-fits-all marketing approaches are a thing of history. Potential and existing customers are VIP’s, and they deserve better.

AI-powered customer segmentation uses a technique called clustering, which analyzes customer data to group individuals based on your data, such as common traits, interests and behaviors.

The ways to apply this are endless. Personalized messaging either by email that resonates, or product recommendations that actually make sense.

Marketers can use AI to make them feel like the VIP they truly are.

Sentiment analysis: Reading the room

Have you ever wanted to read your customers minds?

Marketers can now do just that, to every single one of their customers, at the same time. Kind of.

Sentiment analysis that uses AI to recognize and evaluate emotions expressed in text from feedback, social media posts, and reviews, ranging from positive to negative.

Marketers can read the room and react to the voice of the customers. Whether that’s delivering specific messaging to their own customers, making them feel heard and improving brand loyalty, or hitting the right emotional pain point of a competitors customer, to lure them.

Price optimization: Leaving everyone a winner

Who doesn’t love a good bargain?

AI price optimization models analyze market trends, competitor prices, and customer demand, and run endless pricing simulations of your product, to help you find the optimal price.

The sweet spot is the exact point where your customers feel like they’re getting a bargain, your profit margins are still intact for that product, and it doesn’t cut the sales of other products on offer.

It’s a win-win situation for everyone.

Wrapping up

How many of these use cases were you familiar with? Hopefully you learnt about some new ones and are keen to start using AI for yourself.

Plenty more AI use cases will appear in marketing as AI technology advances, and the strongest marketers will be the ones who embrace the new opportunities.

If you’re a marketer and want to start using AI in your work, consider using the AI & Analytics Engine, and let me know how you go.

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