An Artificial Future for Marketing.

If you like crystal ball gazing, January is generally your best month of the year.  Predictions and forecasts are all over your social feed.  There are many changes that marketers are experiencing in 2023 but none are as impactful as the influence of Artificial Intelligence (AI) on the profession, and there is a growing body of evidence to support this. AI or more accurately Machine Learning (ML) has made rapid progress over the last 24 months and we’re seeing more and more ML projects jettison from development into commercial products as the accuracy of such Machine Learning is perfected.  2023 is the year, if you haven’t already, to ask yourself what AI/ML can do for you. What can this technology contribute towards your marketing success?

Here are just six visions of how you can embrace AI and Machine Learning in 2023 and up your marketing game.

1. The impact of AI on data privacy: AI can be a powerful tool for marketers looking to improve data privacy for their customers. By leveraging the capabilities of AI, marketers can systematically comply with privacy regulations, de-identify data, aggregate data, and encrypt data, all of which can help to protect the privacy of customers.  Using such techniques will allow marketers direct access to customer data for insight and campaign activation. Until now, most marketers have relied on Business Intelligence (BI) or Data Science functions to deliver insights or audience activation. Safe direct access to data, through intuitive visualisation tools (such as Intent HQ’s Insights Explorer), will empower marketers and reduce the reliance on knowing what questions to ask your BI team before you know yourself! 
2. Personalisation: AI can be used to analyse customer data and create personalised marketing campaigns for delivery at scale.  Customer segments can go beyond demographics, incorporating such characteristics as behaviour, and interests. This can help marketers to create more targeted and effective marketing campaigns. Tailored to the individual needs and preferences of each customer or nuanced micro-segments, this can help to increase customer engagement and improve the overall conversion rates of marketing efforts. This isn’t just limited to message. Personalising timing, channel, and synchronising to behavioural triggers is now in the grasp of any marketer with the right platform technology.  For loads of statistics on the value of personalisation in digital marketing, see this list.
3. Content creation: AI can be used to generate high-quality marketing content, such as blog posts and social media posts. In 2023, Canva has just started to trial a tool that creates images in real-time based on the description you type in such as ‘Dancing cat in a leather jacket’. This can help to save time and resources for marketers, while still providing engaging, original, and relevant content to customers.  In fact, 50% of this article has been written using AI-generated content, shifting the human focus from writing to editing and curating content appropriate to your message. 
   
   As of October 2023, Canva are now experimenting with text-to-video. You can see from the example below that it still has some way to go! The prompt used below was ‘Blue and red fireworks in the sky with the Empire State Building in the foreground‘ but the fireworks implode on themselves.

4. Predictive analytics: Until now, one of the barriers to effective predictive analytics (and generating prescriptive outcomes) has been the volume of data required to be accurate.  AI can be used to analyse huge amounts of data to identify patterns and predict future trends. This can be useful for marketers and product teams looking to anticipate customer needs and develop targeted marketing campaigns.
5. Automation: AI can be used to automate various marketing tasks, such as email marketing, social media management, and reactive triggers to inbound prospect behaviour. Predictive lead scoring will ensure a dramatic reduction in missed leads and cleaner more certain leads. One platform spearheading this is Objective. This can also free up time for marketers to focus on more high-level, strategic tasks. Combining Automation and Personalisation can have a huge impact on your bottom line.  
6. Attribution modelling: Data science is utilising machine learning to better determine the effectiveness of different marketing channels and campaigns, and to attribute value to each touchpoint in the customer journey. Google Analytics Attribution modelling that currently remains in beta is reliant on Machine Learning algorithms to learn how different touchpoints impact conversion outcomes.   This can help marketers to allocate their resources more effectively and make more informed decisions.

The incorporation of AI into marketing strategies is likely to become increasingly common in 2023 and beyond. By leveraging the insights provided by AI, marketers can make more informed and data-driven decisions, and optimize their campaigns for better results.

Originally Published on Linked In, January 2023. Updated for October 2023.