In an ongoing conversation about AI in marketing, we asked our analytics and digital lead, James, about the best practices to incorporate AI in advertising to get the most of the ever evolving technology. Read on to learn his expert tips to use AI to your advantage.

An Intro To AI In Marketing

Like every other article written about AI in marketing, I started by asking ChatGPT for a summary of how AI tech could be beneficial to agencies. After some fine-tuning, and foreshadowing, I got the following answer.  AI technology enables marketing agencies to optimize campaign performance through data analysis, personalize customer experiences with chatbots, streamline content creation, and enhance data analysis for better strategic decision-making. Sounds brilliant! Let’s all just head to the beach then, the robots have got this. Is what I might be saying one day, but at least in my opinion, we’re not there yet. That’s not just my fleshy bias showing, there have been countless examples of AI oopsies since ChatGPT exploded onto the scene in November 2022. It doesn’t take much technical knowledge to have ChatGPT breaking it’s own rules and spitting out some VERY interesting things, that definitely aren’t publishable on the Arke website. This isn’t to say that there is no place for AI in marketing, but like most things in life, there needs to be a balance.

As digital marketers we’ve been utilising ‘AI’ for the best part of ten years, our Google Ads bid strategies are all driven by machine learning and the combinations of assets tested in RSAs are assessed using the same tech. Anyone who has done so much as dabble in digital will likely have used these tools, maybe not even realising they are as much AI as ChatGPT is. The difference now is that the curtain has been lifted -, no longer are we wracking our brains to work out what Google’s almighty algorithms like to push. WeW, we can ask, and ChatGPT delivers.

AI For Content

So how can we use AI to bring value to us as marketing agencies, and most importantly, our clients? The most obvious place to start is with ChatGPT’s biggest strength:, language. As a copywriting tool, it’s not perfect, but with some clever prompting and that all-importantall important human touch, it can form a really helpful step in the creative process. 

As a challenge I took the above explanation of how AI can help us, and asked ChatGPT to rewrite it in the tone of voice of Arke. The result shows one of the biggest problems with these tools, they will always try to give you an answer, even if that answer looks like this. Alright, mates! With AI tech at our fingertips, Arke Agency’s taking marketing to the next level. Picture this: we’re crunching data left, right, and centre, optimizing campaigns like there’s no tomorrow. Our chatbots? Spot on, mate! They’re giving customers a personalized experience like they’ve never seen before. And content creation? Sorted! AI’s streamlining it all, freeing us up for the big ideas. With AI by our side, we’re making waves in Brighton and beyond! 

Maybe I could spend a day feeding ChatGPT every blog we’ve ever written, and all the captions from our Instagram posts to better help it understand what our tone of voice is, but at that point, I might as well write it myself. Around the office, the prevailing attitude is that when it comes to copywriting, ChatGPT is best used to offer inspiration or trim down a piece rather than giving it a brief and taking the output as is.

The image generation side of AI is, in my opinion, another step behind the technology’s copywriting capabilities. With the ‘gloss’ I and others have come to associate with both written and visual content produced by AI being even more apparent in images. The ability to tweak an image to exactly match client feedback is also a concern, whilst you can provide the feedback as a prompt, replacing how a human interprets that feedback is much more difficult.

AI For Data Analysis

Something these AI tools are far better than you or I at is analysing huge amounts of data in a short period of time. They can process vast amounts of data from various sources, including social media, website analytics, and customer feedback, to identify trends, patterns, and consumer sentiment. This can lead to better-informedbetter informed decision-making by marketing agencies. Based on actionable insights, enabling them to optimise campaigns, target specific audience segments and allocate resources effectively. Identifying who is most likely to engage with the content we produce is a core part of our work, and can often be time-consuming when we’re pulling from multiple touchpoints. Cutting down this time by using AI allows us to spend more time on forming the strategy we would use to reach these key users. 

Natural Language Processing or NLP is a branch of AI focussed on interpreting and understanding language. In a marketing use-case we can utilise NLP to analyse UGC, such as reviews on a product page, to identify trends or common sentiments. This can then be used to write better copy, product descriptions and even inform keyword selection. NLP can also be used to analyse social media data, to gauge how users feel about a brand or specific content, again helping to inform future decisions.

How AI Can Aid In Streamlining The Client Onboarding Process

The above examples are just some potential uses for AI tech in marketing, there are more opportunities already available and undoubtedly the industry will continue to grow at such speed that tomorrow’s solutions may not even have been considered. 

From the initial keyword research and account setup  we can utilise NLP for keyword research  and website analysis tools to understand how users are using a site and where conversions are happening. This can help provide an informed basis to lay out an account structure. We could then use a tool such as ChatGPT to provide ideas for ad copy, or adjust copy we have written to allow for A/B testing between variations. 

The optimisation of a campaign post-launch has been largely AI-driven for years now, with automated bid strategies taking the reins when it comes to when your campaigns serve. We also see machine learning at work in how creative variations are tested. 

When it comes to reporting on campaign results, GA4’s new insights feature uses machine learning to look for trends and patterns in how users are engaging with your site. This can then inform future strategy decisions and feed into all the previous stages mentioned leading to a better optimised account. 

In Conclusion

I think we are beyond the point of arguing whether AI is valuable to us as companies, even if we’re not quite at the stage where our jobs are being replaced. The tools already widely available can aid in so many elements of a marketers role it would be foolish not to learn how best to use them. Here at Arke we welcome our new robot overlords and are always looking for innovative ways to make the most of the opportunities AI presents. Whether it’s aiding in getting our creative juices flowing, analysing huge amounts of data in a flash or doing sentiment analysis to determine how customers feel. We’re learning every day new ways AI can aid us and whilst we don’t know everything (yet!), we do know that it’s here to stay.