The AI gap for marketers has moved from “what is it?” to “how do I use it?” That’s why Informa Tech recently hosted The Marketing Leader’s Guide to Getting Started with AI webinar, where our experts not only gave an overview of artificial intelligence marketing opportunities for creativity and demand generation, but also shared insights on how to get started.
Here are three important takeaways from the conversation between Eden Zoller – who is Omdia’s Chief Analyst, Digital Consumer Platforms and AI – and Liam Berry, a senior content strategist at studioID who specialises in AI creative integrations.
Generative AI is just a piece of the puzzle
It’s easy to focus on generative AI because it’s the tool marketers are most familiar with today (ChatGPT experiments being the most obvious). But the possibilities artificial intelligence presents to marketers are truly boundless. While no one expects marketers to be experts in how AI works, getting familiar with what its applications can do – from solving task automation problems to analysing deal flow and predicting supply chain issues – will help them more quickly understand how to take advantage of its power.
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The marketing leader’s guide to getting started with AI
AI now touches every step of the buyer journey. But where should marketers start? From CX to targeting and boosting creativity, our team will focus on what marketers need to know right now.
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“[AI] touches every part of the consumer path to purchase, from customer intelligence to advertising, transactions, customer support, and post-purchase activities,” Zoller said during the webinar.
So, how do marketers tackle AI adoption internally?
Many marketers find the best approach to discovering use cases for AI and then experimenting is similar to how they’d tackle any major problem: Get their smartest people in a room and hack together a plan.
“The creation of a task force can be hugely helpful with this,” Berry said during the webinar. “At studioID, we created our own task force and that helped us decide where we can responsibly begin with something like this.”
But when it comes to AI, internal adoption also means coaching your team on how the right mental approach will pay off for them personally, too. Marketers may be hesitant to implement machine learning tasks that appear to make their personal contributions and output less vital to the team. But, as Berry points out, AI is more likely to become an amplifier than a replacement for your most skilled employees.
“There’s a lot of humans involved in making [AI applications effective],” Berry said. “But what is undeniable is that it’s going to change the way that we work. So for people who [want to] grow in their role, a new way to do that is now to learn how to work as best you can with these systems to speed up the processes that need to be sped up, in the same way that someone using a screwdriver is not going to be as fast as someone using a drill.”
The good news is there’s no shortage of potential paths to turn AI into ROI.
“The integration of AI tools has greatly improved our marketing practices, enabling us to generate well-informed and data-driven creative solutions for messaging that has a significant impact on our target audience,” said Freya Smale, Director, Marketing, Automotive at Informa Tech. “By using AI to analyse customer engagement patterns in our email campaigns, we have been able to refine our messaging and send messages at optimal times tailored to our audience’s preferences. This has resulted in an impressive doubling of open and clickthrough rates.
“It is important to note that adopting AI technology requires a comprehensive assessment of processes to ensure successful integration and use. Nevertheless, the potential benefits and advancements that AI provides make the investment worthwhile in the long run.”
Start using generative AI for data analysis
Data analysis via generative AI is the next significant opportunity to boost both your organisation’s productivity and its insights.
“Generative AI can make it easier for marketers to interrogate data sets,” Zoller said during the webinar. “Trying to extract usable [insights] from data is almost a specialist task. It’s time consuming. It’s frankly quite tedious at times. But generative AI can really help marketers because it gives them an easy method to extract data and insights. And I think that can make it easier to share and collaborate and also speed up data-driven decisions.”
Case in point: We used generative AI to analyse the webinar transcript and select meaningful quotes for this article. We then narrowed down the generative AI chatbot’s 14 selections to three highly relevant topics and verified the accuracy of the quotes. The chatbot we used pointed us in the right direction, but definitely made some transcription errors we had to edit before publishing. The same types of processes can be developed for creating quick charts and other data visualisation tasks – though, if using a publicly available generative AI tool, be sure not to upload any proprietary information you wouldn’t want leaking to the public.
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