Artificial intelligence (AI) has made some huge strides in recent years, with no sign of it slowing down anytime soon. AI will continue to make massive strides in the fields of health care, education, transportation, and other industries, but what does this mean for the future of marketing and copywriting?
Language models (LM) are sets of various statistical and probabilistic techniques to determine the probability of a given sequence of words occurring in a sentence. Language modeling is a subfield of AI, and in the past few years, language models have been used in a wide range of applications such as writing books, writing copy, chat bots, summarization, and translation.
To be able to generate words, language models first analyze large bodies of text, typically from the internet. These bodies of text provide a basis for word generations. Companies like OpenAI and Google have been able to build massive models that were trained on very large text data sets. With language models, size matters. The larger the model, the more capable it is of understanding the relationship between words and even objects in the real world. But, with all this computing power, language models are still pretty simple calculators with limitations.
So, what skills will marketers and copywriters need to focus on in order to make the most out of this evolving AI technology? Let’s dive in.
First, we have creativity. Defined as “The use of the imagination or original ideas, especially in the production of an artistic work” (Oxford Languages), creativity is the core piece of any type of writing — across any type of industry.
And how does creativity relate to AI? Language models have scanned the internet, so it’s probable that they can offer new viewpoints on your subject matter that you have not thought about. But would you consider this true creativity? Even if we avoid the philosophical aspects of language models and AI in general, marketers still need to be creative themselves to fully leverage the potential of AI.
AI only knows about your product and your message what you choose to tell it. The rest, it will find from references in its data set. Your main inputs are:
- Product descriptions
- Audience definitions
- Core messaging
Here are some pitfalls that marketers can make when crafting these inputs:
- Defining your product offering in an unimaginative way. AI writes by reading what you give it and comparing it to what it has read in the past. If you give the AI unengaging copy to begin with, it’s not likely that your outputs will be engaging.
- Not being specific enough (or being too specific). AI needs to know what you mean, but you can’t limit it too much. If you get it just right, AI can scale your messages with hundreds of variations that hit the mark across all of your formats — each one tweaked towards a specific audience persona.
So, the bottom line? The more creative you are at the start, the more creative your AI variations will be.
At its core, marketing is about getting people interested in your product or service. If you can’t listen to what people are saying, how can you hope to make them interested?
Listening involves paying attention to your customers, and not just what they say, but how they say it. What makes them tick? What are their pain points? What do they want? These are questions you can’t answer without listening. AI has the benefit of being able to access a wide bank of information about any subject matter. But, only you can really know your audience.
For instance, you can use customer reviews left by your customers to instruct an AI platform and create copy for all of your channels. Reviews will help you focus on features or benefits of your product that resonate with your audience. But more importantly, this feedback would also reveal how your customers talk about your product.
Social media is another great place to spot trends and changes on how your product is perceived. Changes in the market, seasonality, and competitors need to be taken into account when composing your messages across channels. Social media is a great resource to pick up on these trends that are relevant to your customers, product, and industry. These changes need to be crystalized and succinct before incorporating them into an AI writing process. Listening, summarizing, and categorizing these learnings will become key skills in any successful marketer’s toolbox.
3) Data Analysis
Tying your success metrics (the numbers that are important to you) back to their underlying factors is a vital skill. Underlying factors in copywriting include format, tone of voice, CTA, pain points addressed, and others.
Tone of Voice + CTA + Pain Points + Emotions Conveyed + Personalization = Success Metrics
For instance, with ads there are multiple types of success metrics. One example is CPC (cost-per-click), which is how much it costs for someone to click on your ad. Next, look at CTR (click-through-rate), meaning how many people did actually click on your ad when it was shown. Looking at these two numbers, as well as your conversion rate (how often people took an action after clicking on your ad divided by how many times you were clicked on) can provide valuable insights into which ads have worked well and why they worked well. But don’t forget there’s more than one type of metric!
If you are writing new copy for an ad it’s important to analyze your past ads. If a specific ad performed well, analyze why, and take note of what you did right. If it didn’t perform as well as you hoped, look at why and use that information the next time around. But most likely, you will be running multiple ads and learning from a group of instances. This is when you need to apply data analysis techniques. These techniques, when applied correctly, can help to isolate your data so you know which aspects actually impacted performance.
However, understanding the entire funnel is even harder. You may have 100 people click on an ad that reads “Learn More.” With no other information provided, 50 of those 100 people may decide to visit your site and one of them may purchase something off of it. Without gathering data about them, it is hard to tell what was responsible for their decision. Was it your website design? Perhaps your brand voice or style? Was it your CTA? Was it something different entirely?
AI writers have the power to create content at scale, but you will need analytical skills in order to fully understand that content.
4) A Sense of Adventure
The marketing industry is going through big changes right now, and many of those changes driven by technology. In particular, artificial intelligence is already affecting marketing, and it’s only going to become even more prevalent. A good marketer needs to be curious enough about trends and advances in their field so they can keep pace with them as they happen. They must be willing to embrace change rather than fight it. Don’t just react as AI advances — get ahead of the curve by thinking up creative ways that you can use this technology to your advantage!
Use Anyword to Ease The Transition
For marketers or copywriters first starting to use AI in their writing and content creation, it can be a little daunting. It’s hard to know where to begin — and how. That’s where Anyword’s AI Copywriting Platform can help.
This AI copywriting tool not only allows its users to create a wide range of content (everything from social ads and landing pages to blog posts and emails), but it also provides unique predictive analytics. These analytics help its users better understand how their copy will perform, as well as understand exactly who the content will resonate with and why.
So, if you’re a marketer looking to jump head-first into the latest AI technology of copywriting, sign up for our free, 7-day trial and see how it works.