According to a 2018 McKinsey analysis, marketing is the domain where artificial intelligence (AI) will contribute the greatest value for organizations. It is believed that AI can significantly enhance marketing’s core activities such as understanding customer needs, matching customers to products / services and persuading them to buy. Furthermore, a 2020 Deloitte global survey of early AI adopters has shown that 3 of the top 5 AI objectives are marketing-oriented: (1) the enhancement of existing products / services, (2) the creation of new products and services as well as (3) the enhancement of relationships with customers. At a practical level, AI-enhanced marketing will focus on different areas, including:
1. Content creation. AI has given rise to the field of content intelligence, where AI tools provide content creators with data-driven insights and feedback. Creating a continuous feedback loop will eventually enable marketers to enhance the process of content creation. Content creation could be enhanced in several ways:
- by drafting optimized social media posts;
- writing data-driven blog posts to improve post rankings;
- personalizing e-mails and website copy that helps convert;
- conducting effective keyword research, etc.
AI will simplify the process of content creation, and will make it more effective by providing data-driven feedback and assistance in content profiling, topic search and content accuracy, to name a few. AI will also facilitate the creation of personalized content, which will enhance marketing efforts.
2. Hyper-personalized strategies. “Hyper-personalization is the future of marketing because of its ability to leverage real-time data and AI in order to deliver the relevant content and products / services,” explains Elice Max, an entrepreneur. Research shows that 86% of marketing professionals believe that the effectiveness of AI-powered hyper-personalization has been changing for the better. Using its powerful analytical techniques, AI will help marketers adopt highly personalized marketing strategies with the aim of enhancing customer engagement. Not only will that add extra value to businesses, but it will also increase their competitiveness.
3. Advanced data collection and processing. Although we are already living at the time of big data, the amount of data that we will be able to collect in the coming years is going to increase at an exponential rate. The rise of the Internet of things (IoT) means that the amount of data generated by Internet-based devices is going to increase further. Once machine learning algorithms are better at processing that huge amount of data fast, the data could be utilized better. Thanks to advanced data processing, marketing messages could be much better personalized, as marketers will rely more on AI-driven customer data collection running in the background while using websites, social media and other platforms.
4. Voice search. People have been actively using voice search. As the transition to mobile progresses, the popularity of voice search will be increasing further. It is predicted that by the end of 2021, 50% of all online searches will be voice-based. One of the reasons for this growth is significant advances in understanding human speech by machine learning algorithms. Speech-to-text conversion programmes have become very accurate. For example, it is estimated that Google’s algorithms can understand human speech with a 95% accuracy. As the technology improves further and people get used to voice commands, businesses will have to adjust their search engine optimization (SEO) and content marketing strategies so that they are better aligned with voice search.
5. Image personalization. Many marketers have been taking advantage of AI-enabled content personalization. Using customer data, browsing history and individual preferences, AI models can predict what kind of content will appeal to each customer individually. At the moment, this is applicable to text-based content, but it is forecast that in the near future AI will also enable content personalization for images, having in mind that the impact of AI on images has already been significant as it enables “the auto-tagging of images with critical information like object, colour and text recognition”. It is predicted that when an AI model is connected to a digital asset management system, it will enable selecting any image available at an organization.
References: Thomas H. Davenport, Abhijit Guha and Dhruv Grewal, hbr.org | Beena Ammanath, David Jarvis and Susanne Hupfer, deloitte.com | Ron Stefanski, engati.com | Elice Max, convinceandconvert.com | Ascend2, Hyper-Personalization Strategies: Survey Summary Report | Luke Fitzpatrick, techbullion.com | Carlie Hill, cmswire.com