What is AI Marketing?
by Ana Gotter • August 16, 2022
Artificial Intelligence (AI) has been a central point of discussion in many industries for over fifteen years now.
People have long wondered what the full potential of AI is— can it streamline or take over certain tasks? Can this make us more efficient and productive? Will it be cost-effective? Will it take away our jobs?
As artificial intelligence tools have trickled into the marketing industry over the last decade, we’ve started to get a grasp on what AI in marketing can really do, and what it can’t.
So in this post, let’s take a look at AI in marketing as it stands now and what it means for advertisers and businesses everywhere.
What Is AI in Marketing?
Artificial intelligence (AI) in marketing relies on deep machine learning and programming to provide either some form of creative or campaign optimization based on predictive data analysis.
This can include campaign optimization, copy suggestions, and even sales or customer service help through chatbots.
AI in marketing is typically capable of analyzing massive amounts of data, testing what works, and improving on it moving forward. It continually gets smarter, meaning that theoretically, the results get better over time.
4 Different Types of AI Marketing Tech
There are a few different types of AI marketing tech that are on the market today. Some of it (like chatbots) are accessible to brands of all sizes, while other tech (like advanced copywriting software) is currently much more expensive.
They also vary in effectiveness and reliability, especially depending on the quality and type of tool you’re choosing.
Let’s take a look at four different types of commonly-used AI marketing tools.
1. Copywriting AI
Copywriting AI is probably one of the biggest and hottest topics in some parts of the marketing industry right now.
You’ve got basic AI writing tools like Grammarly or Hemingway that can offer suggestions to catch typos, improve sentence clarity, and reduce grammatical errors. These are useful (I use Grammarly myself), but they should never be set on autopilot because they do sometimes get things wrong.
Another option is predictive suggestions for optimizing or suggesting headlines, product descriptions, or meta descriptions. Some email marketing software offers predictive headline analysis or recommendations to help improve open rates.
There is also copywriting software that’s much more advanced, offering auto-generating content and copy that theoretically can be used for landing pages, product descriptions, emails, and blog posts.
Some of these tools are fairly impressive at a first glance and can replicate the voice of a writing sample or well-known person. They are, however, still deeply limited. They’ll pull from sources that are already available online (some of which contain inaccuracies) and aren’t capable of creating new insights that can help you stand out.
2. Campaign Optimization AI
Campaign optimization AI can be beneficial when you know how to leverage it.
These tools will do a deep dive into the analysis of campaign performance. Some will look at general campaign performance, some look at your particular campaign performance, and others take both into account.
They’ll either offer suggestions about how to optimize your campaigns or automatically test different optimization tactics to see what works.
Examples might include:
- Pay-per-click (PPC) platforms automatically optimize campaign delivery based on the audience you want to reach and the specific results you want
- PPC analysis tools that provide suggestions for copy, targeting, or bidding in order to help you get more results
- Split testing email campaigns through email software to find which has better open or click-through rates
- Site optimization tools that are designed to split test landing pages and offer suggestions for improvements
These tools are often great as a resource for new strategies you can implement to improve your results, but you need to know how to implement them correctly.
3. Chatbots
Chatbots make use of predictive customer service and sales programming (both of which can be helpful for marketing).
You can program chatbots— or have someone do it for you— to offer basic support to customers on your site and even on social media.
The options here are seemingly endless. Chatbots can:
- Provide customer support with questions like “where’s my order”
- Offer product suggestions based on what customers are looking for, or answer questions customers might have like “is it gluten-free”
- Process sales
- Capture lead information
- Share resources, like product care or usage guides
These chatbots can act as an extension of your sales and marketing departments. You can learn more about how they work here.
4. Content & Product Personalization
One small but effective way to implement AI on your site is to teach different tools how to offer relevant product and content recommendations to each individual user.
If someone is browsing on your site, for example, you can show them “previously viewed” items, but you may have more luck showing them products that are similar or complimentary to what they’re already viewing.
This works for content marketing, too. When users are reading one blog post, you can show them suggestions for other content they may be interested in. This could include high-value resources like an ebook or webinar that’s designed to push them to the next stage of the funnel.
Like most AI, the usefulness will rely on how well you’ve “taught” the software to work for you, and those with machine learning can learn more over time.
How Effective is AI in Marketing Now?
The efficacy of AI in marketing right now depends partially on which technology you’re looking at.
Across the board, however, it’s clear that AI can be a great start but that it’s always going to be most effective when it’s leveraged by marketing experts who use it to enhance their campaigns instead of using it to create and run campaigns entirely.
And it’s important to note that marketing AI can have some serious limitations, and it can also have a real impact on potential customers.
The “You Might Also Like This” recommendations that show up on eCommerce sites are a great example. These tools (which are often plugins) must be well-programmed in order to understand what products customers might actually be looking for.
If customers see “you might also like this” but don’t see anything close to another option they like, they may assume you don’t have something that fits their needs, whether it’s due to product relevance or cost.
Similarly, predictive customer services and sales-based chatbots can be helpful. They’re able to take on commonly-asked and simple customer questions like “what is your return policy” and even “how does a subscription work.” They are limited, however— sometimes customers may not get the information they need, and quick access to an experienced (and human) salesperson or customer service rep is crucial.
The copywriting AI software on the market is perhaps the most significant example. As we mentioned above, even the most advanced copywriting AI is deeply limited. While capable of imitating someone’s voice and tone extremely well, the reality is that it’s only capable of recreating some version of information that’s already out there. You aren’t getting anything truly new or original.
While this may seem helpful for content generation, this also means that the AI can easily end up picking up inaccuracies from other sources and dropping it in. (Some early tests also showed it picking up racist and sexist ideologies from Twitter, which is the last thing you’d want your brand associated with).
A lack of originality and the potential for inaccuracies make this software useful as a starting point but not an end result, especially since as a brand you need to be unique, even if it’s for a short 100-word product description on your site.
Final Thoughts
AI in marketing is outstanding when you’re looking for fast ways to enhance campaigns, offer insights, generate new ideas to try, and even offer additional support to leads and customers.
At least at this point in time, however, that’s as far as its usefulness extends. You should never rely on it entirely— campaign optimization can start targeting the right types of customers without realizing it, and inaccuracies can end up throughout content and even chatbots.
Instead of working with AI to create and manage the campaigns that you, work with a qualified and experienced advertising firm. Here at Disruptive Advertising, we use top-of-the-line analysis software to give us detailed insights that we then use to create strategic, creative campaigns that will set you apart.
No AI can make up for human touch and strategy, both of which are needed for creativity and originality.
Looking to step up your campaigns to maximize your ROI? We can help. Get in touch for your free audit here.