Lessons in AI: How to Get Started with Generative AI For Technology Marketing

The explosion of generative artificial intelligence (Gen AI) tools has undoubtedly disrupted the marketing space. Aiding in idea generation, content creation, data analysis, editing and more, Gen AI offers marketers more ways than ever before to drive efficiency, saving organizations time and resources.

During last month’s Technology Marketing Alliance (TMA) virtual event, “Generative AI for Technology Marketing - What We Know and Where We Can Go,” moderator Brian Reed, head of marketing at Appdome and founding board member of TMA, drove the discussion around AI adoption and use within the technology marketing arena. Joined by industry experts, Geoff Livingston, principal analyst and founder of CognitivePath, and Nicole Leffer, CMO AI advisor at A. Catalyst, the panel discussion focused on best practices for effectively integrating and using AI for marketing efforts, providing attendees with actionable insights on how to elevate their business with AI.

Getting Started 

With many organizations just beginning their Gen AI implementation journeys, the conversation began with a discussion on how marketers can get started with Gen AI platforms. According to Nicole, marketers should take the leap by experimenting with tools: “Start playing and talking with [generative AI] and asking it to help you to begin getting a feel for how conversations with generative AI tools work. You will be blown away very quickly at how powerful it is even if you do not know anything.”

As far as beginner-friendly products, Nicole mentioned chatbots, where users can prompt the bot to produce their desired output. She recommended upgrading platforms such as ChatGPT to premium models for higher functionality and higher quality outputs. On the other hand, Geoff advocated for Claude, another chatbot “trained to be safe, accurate, and secure.” Ultimately, the panelists suggested marketers try both platforms and determine which works best for their use cases. Apart from chatbots, Geoff also mentioned beginning one’s AI journey with Grammarly, a free tool to support writing efforts.

Producing Quality Outputs

One of the key challenges faced when adopting Gen AI impacts output quality. To improve the quality of AI-generated responses, marketers must ensure they’re providing high-quality prompts– a practice known as prompt engineering. To tailor the outputs to their specific needs Geoff recommended that marketers input marketing briefs to train the technology as they can help shape the tone, purpose, call to action, and length of the prompted outcome. Marketers must remember that these models are not perfect, and therefore might need to prompt the model several times to achieve the wanted output. For these instances, Nicole suggested marketers observe and learn from each prompt they input to understand how different inputs impact results.

Maintaining Ethical and Privacy Standards

For all AI use, marketers must recognize and adhere to their organization’s policies regarding AI. As Nicole warned, some organizations have banned AI tools for security purposes, as many free models use the information inputted to train future models. As such, marketers must be wary of inputting proprietary or confidential information into software. For instance, Brian has utilized chatbots to develop sales leads based on analyzing customer behavior, but successfully disguised customer information by removing all private data and replacing it with a unique identifier number.

Common Usages

Generative AI provides endless opportunities for organizations to save time and money. For marketers, this means finding tasks that Gen AI can streamline to help produce elevated deliverables. Each of the panelists shared an example of their recommended use cases:

• Brian suggested leveraging Generative AI to analyze data-heavy pieces of content such as webinar transcripts to rapidly consolidate the insights into a more digestible form like a recap blog.
• Geoff recommended leveraging chatbots to analyze consumer behavior, discover trends, and predict future behavior to uncover new areas of revenue and high-spending prospects.
• Nicole mentioned Gen AI’s multi-faceted capabilities from A/B testing for optimized web pages to generating long-form content like white papers.

Utilizing Existing Software

The bottom line is that many solutions in the marketing stack already include or are introducing generative artificial intelligence functions. However, some products have not yet fully developed their AI offerings, so marketers should proceed with caution as Nicole warned.

The emergence of Generative AI presents marketers with opportunities for saving time and money while driving growth and innovation. Today’s technology marketers must seek to understand the different tools of the market, their capabilities, and their impacts.