This is a continuation of a previous article on AI for product development.  Since marketing is one of the core influences on product development, this article reviews how AI is changing marketing and driving rapid business growth.

Marketers use AI to create product descriptions. Typically, this involves words and phrases that come from research on target audience but when the same is used by marketers over and over again, it can become repetitive. AI rephrasing tools can help teams find new ways of describing the most prominent features of their products.

Content marketers are often caught up in the task of creating more content but it’s equally important to optimize the content that’s already on the site. As content gets older, it becomes dated and less useful which brings down the SERP. When a particular URL is provided, AI can inform the keywords its ranking that URL for and which keywords need a boost. This helps marketers go further.

AI is most used in data analytics. Performance of various content types, campaigns and initiatives used to be time consuming just by virtue of sourcing it from various origins and the tools varied quite widely. Now teams empower themselves to quickly get and analyze the data in which they are interested. Business Intelligence teams continue to tackle complex data, but it is easier to get started with data analytics for most users.

AI can also help optimize marketing activities by providing insights into customer behavior and preferences, identifying trends and patterns, and automating processes such as content creation, customer segmentation and more. AI initiatives achieve better results and help the marketing strategy better connect with the customers.

Website building, personalized targeting, content optimization, or even chatbot assistance for customer support are some well-known areas for AI based enhancements. AI content generation can help accelerate content creation. Fact-checking information in the articles and ensuring that messaging and tone are aligned with the brand voice continue to require supervision.

The right tool for the right job adage holds truer than ever in the case of AI applications. Technology and infrastructure can evolve with business as it grows, and long-term investments certainly help with the establishment of practice. Text to Text and Text-to-Image generators are popularized by tools like ChatGPT and DALL-E 2. These make use of large language models, natural language processing, and artificial neural networks. The caveat here is that different tools are trained on different models. It is also possible to mix and match, for example using ChatGPT to create a prompt and then use the prompt with DALL-E 2 or Midjourney. Social media platforms like Facebook and Instagram offer ad targeting and audience insights. Email marketing platforms like Mailchimp provide AI powered recommendations for subject lines and send times.

Some of the bias against AI comes from inaccurate information from generative AI. Others come from the bias served up by the AI tools. These are overcome with a wider range of datasets. AI4ALL for instance, works to feed AI a broad range of content to be more inclusive of the world. Another concern has been over-reliance on AI. A straightforward way to resolve this is to balance the use of AI with those requiring skilled supervision.