Without a shred of doubt, 2023 has been a breakthrough year for AI. Although ChatGPT is what truly started the revolution by taking the technology to another level, artificial intelligence is now being used all across the board for smart automation to help you save on your most valuable resource – time.
As you can imagine, using AI for marketing is what can truly give you a competitive advantage in this day and age. But if this is your first time dabbling in this relatively new technology, you will be prone to making common AI mistakes that can be avoided with a little bit of know-how and experience.
The good news is, you don’t need to make these mistakes on your own to learn the lessons. To save you the hassle of trial and error, we’ve prepared a comprehensive list of the most common mistakes marketers make when using AI and what to do instead. Some of these will be specific to ChatGPT, while others are general principles you can apply to a myriad of AI tools of your choosing.
Off to the first one!
Mistake 1: Forgetting to fact-check ChatGPT’s output
As we’ve written about before, ChatGPT is a potent tool that has a glaring drawback – factual accuracy comes second. And yet it’s so incredibly good at what it does that it has the capacity to convince you of a glaring falsity that appears to be true. Some of these are subtle inaccuracies, while others tend to be dramatically incorrect.
The solution for ChatGPT fails may not be what you want to hear, but you’re going to have to double-check its output to ensure that everything is correct. We are not yet at a point where you could let it run freely without supervision and not worry about a thing. Perhaps one day! Until then, manually reviewing it is still going to be faster than writing everything from scratch.
Mistake 2: Resorting to AI for every single task
If you’re an efficiency-oriented individual who prefers not to waste time on menial tasks, invoking the power of AI will be your knee-jerk reaction. But your obsession with productivity could be exactly what ends up holding you back. Have you ever heard of the KISS principle? It stands for “keep it simple, stupid”. Generally, the more multi-layered and complex you make things, the greater the chance of it all taking longer to implement and going wrong.
AI, by its very nature, tends to be a complex entity. Figuring it all out, implementing it, and monitoring its performance can very well be a massive time sink. Sure, it can run like clockwork when you reach that point, but think of all the time it’s going to take to get there and ask yourself whether it’s worth the effort compared to using a simple spreadsheet or other manual means from the realm of old-school.
You can still be using AI for marketing, but make sure it’s going to be for tasks that can be described as dull, repetitive, and boring. Generally, that’s where it shines and you can reach a point where messing with it is going to be worth going the extra mile.
Mistake 3: Instructing your team to use it without proper guidance
As you can probably tell from your own experiments, AI fails can often result from a lack of experience. These can be subtle things like forgetting to personalize its output and just going with generic responses it gives. When you have the luxury of having an entire team under your command, you want to make sure that resource is utilized well, and instructing them to use any kind of tools they haven’t received proper training on can result in unexpected quirks.
In this case, the solution is two-fold. Not only should you spend some time and resources on training them properly, you should also judge each and every situation on a case-per-case basis to determine whether using AI truly yields any benefits over completing a task manually. You may very well find out that certain repetitive and boring tasks are suitable for automation, while others are still better left to a real industry professional.
Using or not using AI is also a matter of keeping their spirits up, so try to place yourself in their shoes. In most likelihood, the majority will be happy to let go of repetitive and soul-sapping tasks in favor of pursuing a more creative outlet.
Mistake 4: Not personalizing ChatGPT’s output
Most social media experts will agree that using AI for marketing is a no-brainer. But the top-performing talent, the people who know how to get sales and conversion, will pretty much all tell you that the devil is in the details. In other words, it’s the subtle nuances in how you phrase your sentences and speak to your audience.
As you may know, certain groups of people tend to have their own slang and buzzwords. Typically, this is a phenomenon observed in niche groups. For example, golfers have their own lingo, which is evident from the way they refer to different types of swings and similar. Instead of trying to address them in a generic tone (the kind that ChatGPT tends to write in), you will have much better success with incorporating some of that lingo into your social media marketing campaigns.
At the end of the day, a generic approach tends to yield generic results. Therefore, look for ways on how you can make your message and content more personalized.
Mistake 5: Not wanting to delve deeper due to fear of technical difficulty
Ironically, not wanting to study the technology in-depth due to fear of it being too difficult is one of the most glaring AI mistakes so many people make in their marketing career. But here’s the thing: just like you don’t need to understand how a stove works on a technical level to use it, neither do you need to be a tech whiz to unleash the power of AI.
Remember, you’re not training AI models here; you’re simply using AI for marketing to take some of that monotony out of your daily routine and spend your time in a more efficient manner. For instance, let’s take ChatGPT as an example yet again. There are various ChatGPT prompts and usage examples out there and we’ve written a detailed guide on the subject ourselves. Spoiler: you can use it for way more than just content generation.
Mistake 6: Assuming the AI landscape never evolves
Prior to where we are now, there were early AI attempts and at their earliest stages, they left much to be desired. Some of those who played around with the AI technology back then had arrived at the wrong conclusion that the state of technology was constant rather than dynamic and rapidly evolving as it is in reality, making them ignore any emerging tools and subsequent releases.
However, ignoring the AI landscape ultimately comes at your own peril, especially in the post-2022 era where ChatGPT is making everyone bedazzled at what it’s capable of. So much so that other clones started emerging, with Microsoft Bing’s Sydney and Google’s very own attempts at making a similar tool effectively becoming one of the primary development goals.
In addition, its success has inspired an onslaught of other AI tools that don’t aim to become yet another ChatGPT clone, but rather expand on the realm of possibilities brought about by the technology. Think voice changers, process optimizers, keyword research tools, image generators, and more. What a time to be alive!
Mistake 7: Thinking AI chatbots can replace your entire customer support department
AI chatbots have been around for a while. The idea behind their design is to take off some of the burden often faced by customer support departments, effectively allowing companies to have less customer support agents on board and still get the job done. The problem is, AI fails some of the time and when that happens, you’re going to need a real support agent to take the wheel.
Typically, a chatbot’s capabilities are based on analyzing the knowledge base and recognizing the patterns. For instance, if the chatbot provides an answer Y to a question X and the user who asked it is satisfied with the response more often than not, that is a signal to the chatbot that the answer is helpful. However, a chatbot may struggle with providing more custom-tailored advice. If the question cannot be fitted into a category of answers or the chatbot isn’t sure how to proceed, it will give you the option of getting in touch with a real customer support agent.
So how is this relevant to social media marketers? A while ago, we did a post on the dos and don’ts of social media customer support. Not everyone knows this, but it’s possible to integrate a chatbot into Facebook messenger directly, allowing it to take over your conversations with customers. Brushing up on what you can do with one will certainly help your business and allow you to optimize the amount of staff you need deployed on the customer support front.
Mistake 8: Not experimenting enough
Using AI for marketing can be done in a myriad of ways, and the best way to learn what it can do is to give it a spin. As you’ll find out, not all of these uses will be relevant for what you’re trying to achieve with your social media marketing campaigns, but some of them can be game-changing.
To refer to one of the points made above, it may be that the juice is not going to be worth the squeeze when pondering whether to do something manually and weighing it against the benefits of automating it with the help of AI. But without experimenting, there’s no way to tell. Since many things you can do with AI still remain an unexplored territory, it will be crucial for you to approach things with an open mind to get the most of it.
Mistake 9: Failing to understand how AI gauges its responses
The state of AI is what it is thanks to constant learning and improvements in a trial and error fashion. Training it to provide the right responses often boils down to making a lot of oopsies and mistakes along the way before it gets the data necessary to learn and progress.
The downside of this is that it might take a bit of time and resources to get it where it needs to be. On the flipside, once the initial learning period is over, it gets better and better at its job over time. With this in mind, don’t make one of the common AI mistakes of giving up on your tool of choice too quickly. Whatever its current state may be, it’s not going to be this way for the rest of its life-cycle and this is a good thing.
Mistake 10: Conversing with ChatGPT without a suitable degree of clarity
Plenty of ChatGPT AI fails can be attributed to the user not asking the right questions or providing clear-enough instructions. Remember that the technology heavily relies on past experiences to answer your question, using anything and everything at its disposal to provide a suitable answer. In a lot of cases, it finds itself in a situation where it needs to answer a certain question for the first time.
As advanced as its technology may be, ChatGPT is no mind-reader! Therefore, letting it in on the purpose of the question certainly contributes to it being able to provide a higher quality answer. Furthermore, you should make an effort to ask the question in a clear manner so there’s no way to interpret it in multiple ways. For instance, if you instruct it to write your next social media post, give it some information about your target audience, what you want to post to be focused on, etc.
Alternatively, run the script a couple of times and simply pick the most suitable responses. That works too! Since this approach requires very little effort on your end, many users prefer to do it this way. This is exactly how Ocoya’s AI is set up. In this example, we’re going to walk you through how to generate tweet ideas for your next Twitter post.
First, navigate to Ocoya’s main page and find the AI Copywriter section on the left.
Keep scrolling down until you find the Tweet Ideas section. Open it.
Tell Ocoya a bit about your main niche. No need to go into detail, a brief couple of sentences will do. Finally, click Generate.
Voila! To the right, you will see more than plenty of keyword-based AI tweet ideas you can modify or use as is. These have a star rating next to it, so choosing the right ones will be a breeze.
If you want to be using AI for marketing, you need to study up on the most common AI mistakes to unlock its full potential. Today, we’ve gone over some of these made by others so you won’t have to repeat them yourself.