Learn how marketers can leverage their expertise to drive innovation, enhance user experience, and reduce product failures. Discover the untapped potential of combining marketing and AI for a competitive edge.
Is your marketing team still using generative AI just for content creation? If so, you’re missing a tremendous opportunity. The real magic happens when marketing becomes integral to the product development process.
According to a Capgemini report, 60% of companies already invest in AI for marketing purposes. Some sophisticated marketing teams use AI for idea generation, data analysis, campaign creation, and personalization. However, this is just scratching the surface. The true potential lies in involving marketing throughout the entire genAI product development lifecycle.
Why involve marketers in AI product development?
With large language models (LLMs), machines can understand human language for the first time. Marketers are uniquely positioned to lead in this AI-driven world due to their communication skills and deep understanding of customer needs. This collaboration can revolutionize how AI products are conceived, developed, and launched.
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How can marketers add value to AI product development?
To seize this opportunity, marketers must engage in product development from start to finish. This involves partnering with product managers to identify customer pain points, define features, and build, test, and launch products.
In the discovery phase, marketers can bring invaluable insights from customers. Their deep understanding of market trends, consumer behavior, and pain points can guide product managers in identifying the most pressing issues that need to be addressed. These insights help the product team prioritize features that cater to user preferences beyond the generic AI-powered chatbot we see everywhere. Involving Marketing at this stage also helps frame and test the product’s value proposition early in the development cycle. In many cases, teams may realize that AI is unnecessary for the specific problem they are trying to solve, saving time, money, and valuable engineering resources.
In the building phase, marketers can assist by providing real-world scenarios and use cases that engineering teams might overlook. Their involvement could ensure that the AI models are trained on appropriate data and that the prompts are crafted to reflect realistic customer interactions, minimizing hallucinations. Testing is where marketers’ understanding of the target audience becomes even more crucial. They can help design prompts and tests that mimic real-world usage and provide feedback on the AI’s performance from a customer’s perspective. Their input helps refine the product to meet customer expectations better.
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Consider the example of Air Canada’s chatbot, which began providing incorrect information about the airline’s bereavement policy. This issue likely arose because edge cases like bereavement policy prompts were not adequately tested. Marketers being close to customers can help product teams anticipate such use cases and ensure that the AI handles them correctly. Their unique insights into customer needs and behaviors can help identify edge cases that engineers might not consider, leading to a more robust and user-friendly AI system.
At the launch stage, marketers’ skills in crafting compelling messages and campaigns are even more important for generative AI products. One of the significant challenges with generative AI adoption is demonstrating a clear return on investment (ROI) to potential customers. When involved from the early stages, marketers can craft and validate ROI messages that effectively communicate the benefits and efficiencies gained through the AI product, helping sales teams close deals.
For example, GitHub Copilot, an AI-powered code completion tool, has been marketed as a significant productivity booster for developers. By highlighting how Copilot can save time and reduce repetitive coding tasks, marketers at GitHub have positioned it as a valuable tool for enterprise adoption. Additionally, marketers’ expertise in change management is crucial for driving AI product adoption within organizations. Generative AI products often require changes in user behavior. For example, prompting is a new skill that users are not accustomed to. Perplexity AI, a search application similar to Google, provides suggested prompts to help users narrow their searches. Marketers can assist in developing and testing such prompts to facilitate user adoption.
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The stakes are high – marketer’s must step up
Despite AI’s promise, there have been notable failures. Even big tech companies with top-tier talent and endless resources have made huge missteps leading to failed products and lawsuits. Often, it’s because products are developed in a vacuum, without marketers involved from the beginning. This siloed approach can result in products that miss the mark with customers and tarnish the company’s reputation.
By bridging the gap between product development and market expectations, marketers can create products that truly resonate with users. Natural language is the new coding, making human skills more valuable. Marketers must step up and participate in building generative AI products together with product managers.
