How will GenAI and new trends in digital transform marketing as we know it? John Cradden looks at the key trends and technologies that marketers should use.
For what is a relatively new technology, the adoption of generative AI for marketing purposes has been relatively swift.
A recent survey by Salesforce of over 100 marketers in Ireland (as part of a global survey of 4,800) reveals that 75% of them were already using it or experimenting with it at work.
“Some marketers are using generative AI to analyse what their competitors are doing, assess consumer sentiment and generate new product concepts”
The expectation is that the roll-out time for marketing campaigns can be measured in days rather than months thanks to generative AI’s capabilities in areas such as content generation, automation, customer data analysis and the scaling up of personalisation.
So, based on market research insights from the likes of McKinsey & Company and Salesforce, what are the key trends and technologies within generative AI that marketers need to be looking at in 2024?
Market insights
It can take weeks or months to conduct market research but generative AI can augment this key part of any marketing strategy by providing insights into customer preferences, behaviours and market trends through advanced analytics and predictive modelling. This can potentially condense the time taken on research from weeks and months to mere days.
Idea generation
Some marketers are using generative AI to analyse what their competitors are doing, assess consumer sentiment and generate new product concepts. One example is Kelloggs, which scans online trending recipes that incorporate (or could incorporate) breakfast cereals and uses the resulting data to launch campaigns on social media around these recipes.
Personalisation
Research suggests that the pressure to provide personalised experiences to customers is increasing, but this can drain a lot of time and resources. This is where generative AI tools can help, helping to analyse large datasets and use the insights to create more defined customer segments and generate personalised product recommendations and website experiences, among other things. Another application is the use of AI-driven chatbots, virtual assistants and messaging platforms to help with website navigation or order management and generally improve user experience.
Generating content
Whether its text, visuals or video, generative AI has the potential to scale up the production of original and unique digital content for businesses at a lower cost. Generating copy is probably the best known use case with technologies like ChatGPT and Microsoft Co-Pilot and simple prompts to create blog articles, ad or social media copy and more personalised email marketing campaigns. For visuals, you can use platforms like DALL-E to create original images and branding materials that might otherwise require employing a designer or else spend time looking for royalty-free images. And with online video consumption rising, you can use generative AI to create voiceovers or translate into multiple languages for use in overseas markets.
SEO and automation
Generative AI can enhance the precision of your SEO efforts by identifying high-value keywords and suggesting SEO-optimised topics. Alternatively, you can use it to automate repetitive processes, such as the meta-tagging for websites, which can otherwise take up hundreds of hours.
Testing
Generative AI can also come into play for A/B testing of content by generating multiple different versions, whether that’s email ad or marketing campaigns, blogs, videos etc while also measuring and monitoring their performance and engagement with users.
Assess your customer data
When it comes to successfully executing more personalised marketing campaigns with the help of generative AI tools, much will depend on the quality and ease of access to customer data. The Salesforce survey suggests that only 26% of businesses in Ireland are satisfied with their ability to unify all their customer data sources, so getting this right will be essential for such generative AI-supported tasks as predictive data analytics, customer segmentation and even just better understanding your target audience. But depending on what data sources and platforms you use, there are likely to be AI tools that can help with this.
Risks
As you might expect, the Salesforce survey also indicated lingering concerns about the risks of using AI, particularly in relation to security, accuracy, data quality and copyright infringement. Consulting firm McKinsey & Company cautions against using generative AI for high-level decision-making, applications that involve a large volume of requests or numerical reasoning, or in areas where there is a lot of regulation.
Furthermore, raising awareness and organising staff training in generative AI tools would be a crucial element in any rollout of these tools across any organisation.
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