Despite the challenges of recent years, many pharma companies have recorded top-line revenue by exploring opportunities to work with industry experts. Across the industry, companies are adapting to newer and intelligent technology models, especially generative AI cases that have allowed significant competitive gains with proprietary applications and tools. 

Generative AI is making significant contributions in the industry and marketing is only a small part of the whole structure. It’s intuitive abilities to adapt and respond to complex tasks, adapt and respond to prompts, and create texts, images, videos and speech. The technology’s sophistication is expanding daily, challenging notions about its limitations. 

Key focus areas

Analyzing unstructured data to understand consumer preferences

One of the most impactful applications of generative AI is its ability to process massive volumes of data. Its ability to learn and generate insights from unstructured sets faster than traditional market research methods and with more granularity allows marketers to uncover data bias and make informed decisions. This is especially beneficial in today’s digital age as organizations receive an overwhelming influx of data, including consumer feedback, purchase histories and feedback surveys across traditional channels and e-commerce platforms. Through collaborations with artificial intelligence consulting and advanced AI models, marketers can identify patterns and trends, summarize and categorize customer preferences and draw conclusions. By understanding these aspects, marketers can predict future behaviors, address growth opportunities and craft unique brand positioning.

Expedite product development cycle

The versatility of generative AI can be tracked by how products are conceptualized, tested and launched. Gen AI and large language models trained on extensive data sets can perform simulations that can mimic consumers and competitors to predict future actions and identify flaws before production begins. Furthermore, gen AI trained on preliminary and regulatory requirements can review claims based on authority, and administrative guidelines can help remove nonviable options and suggest alternatives. Pricing is another aspect of the product lifecycle that generative AI can help with. By analyzing market trends, competition and consumer willingness to pay for a product, AI models can help establish a sustainable pricing structure. The system can create virtual personas and test consumer reactions on various price points, helping marketers identify the perceived value of the product and the impact on top-line revenue and bottom-line profitability. Simultaneously, marketers can work with pricing strategy consulting services to implement pricing that better meets consumer needs. 

Content personalization and streamlining marketing tasks

Modern marketing gimmicks are focused on channel and consumer microsegment, especially millennials and Gen Z. Generative AI empowers marketers to deliver personalized customer experiences by tailoring marketing messages and creating custom headlines based on consumers’ online history and interactions rather than depending on traditional email marketing tactics. While the intent is to improve interaction, place their brand better and streamline marketing communications, it doesn’t replace human oversight but rather enhances existing processes. Through automation in communication channels, marketers can save potential costs, eliminate rework and reduce external dependencies, allowing for a more cohesive marketing environment. 

Generative AI capabilities yield better results and allow marketers to streamline mundane tasks, freeing them to focus on value-based work, all the while leading the team towards innovation and product success.