Artificial Intelligence & Marketing Strategy by Prof. Purvi Shah

• Are you debating the role of AI in Marketing Strategy?

• Is AI useful only as a tactical tool? OR

• Is AI a tool for marketing strategy formulation? OR

• Something in between?

Strategy is formulated with a series of decisions that are vital for an organization’s performance. In my opinion, AI can partner with managers, and support and augment marketing decisions and strategy formulation in various areas such as:

• understanding consumers’ value needs (e.g., market research, segmentation, social listening),
• creating a value proposition (e.g., innovative and customized product design, personalized user experience, dynamic pricing),
• communicating the value proposition (e.g., content creation, media planning, digital advertising)
• delivering a value proposition (e.g., retail chatbots, inventory optimization, identify sales leads)

For repetitive, routine, high-speed decisions, AI can play an important role in enhancing efficiency and productivity. For more important, strategic, and consequential matters, human involvement (over and above AI’s supporting role) is key.

There are many different perspectives and frameworks about AI’s role in marketing. For example, Eriksson et al (2020) found support for AI as a tool for marketing strategy formation through a “creative-possibility perspective”. Kshetri et al (2024), presents various use cases of Generative AI in marketing. These include content personalization, customer insight generation, and idea generation for content marketing (mainly tactical applications). Huang and Rust (2021) propose a strategic AI framework of three types of AI that can each be used in three different marketing roles. They found that mechanical AI, thinking AI, and feeling AI can be used for marketing research, marketing strategy, and marketing action. Davenport et al (2020) present an integrated framework to comprehend the influence of AI in marketing, considering factors such as intelligence levels, types of tasks, and whether the AI is embedded in digital or robotic form.

Davenport, Guha, and Grewal (2021) emphasize that AI implementation in marketing comes with its risks and challenges. To expand the reach of AI, marketers must,

• Ascertain transparency in privacy and security controls
• Conform with laws to allow customers to self-regulate privacy and security controls
• Involve customers to include their thoughts and ideas on how their data is collected and used
• Provide customers with a fair value in exchange for their data
• Test and then remove biases in marketing applications of AI

Examples of AI’s Marketing Applications and Useful AI Tools

Advertising:

• Ad Campaign Optimization – Trellis
• Image and Video generation for ad creatives – Synthesia, Canva , Descript
• Ad content personalization – Omneky, Celtra

Marketing Analytics:

• Social Media Monitoring – Brand24, Brandwatch
• Scraping Web Pages for Data – Browse AI
• Customer insights - Optimove

Public Relations:

• Drafting and distributing press releases – MarketersMEDIA
• Media Management and Analytics – Propel PRM
• Pitch generation + personalization and media connections – PRophet

Digital and Social Media Marketing:

• Content creation – Jasper
• Search Engine Optimization – Surfer
• Ad content personalization and optimization – Albert: AI Marketing (Acq. by Zoomd)
• Social Media Management – Jasper , FeedHive
• Influencer Marketing - Influencity - Influencer Marketing Platform

Email Marketing:

• Subject line automation - Phrasee
• Email marketing optimization - Seventh Sense ™
• Personalized newsletter creation - rasa.io

References:

• Davenport, T.H., Guha, A., & Grewal, D. (2021). How to Design an AI Marketing Strategy. Harvard Business Review, https://hbr.org/2021/07/how-to-design-an-ai-marketing-strategy
• Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42.
• Eriksson, T., Bigi, A., & Bonera, M. (2020). Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation. The TQM Journal, 32(4), 795-814.
• Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50.
• Kshetri, N., Dwivedi, Y. K., Davenport, T. H., & Panteli, N. (2024). Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda. International Journal of Information Management, 75, 102716.