Generative AI is revolutionizing all areas of society and marketing is one of the most. As technology continues to advance, its role in all strategies becomes more present.
In recent months, generative AI is also taking center stage in Demand Gen or demand generation . In particular, generative AI is revolutionizing the marketing industry by automating previously time-consuming and manual tasks and processes.
Companies are already using generative AI in a Demand Gen strategy and different applications are already beginning to become popular.
How to use generative AI in Demand Gen?
Aside from marketing, one of the areas where generative AI is growing the most is commercial. Different studies show that almost two-thirds (61%) of sellers already use AI in their operations.
Marketing and sales are the disciplines most interested in generative AI and also in demand generation .
Some ways generative AI is employed in demand generation include:
1.- Automated lead scoring
Automated lead scoring uses machine learning algorithms to evaluate and prioritize leads based on various factors, such as their online behavior, interactions with content, and demographics.
It allows sales and marketing teams to concentrate their efforts on the leads with the highest probability of conversion, saving time and resources. This improves efficiency and increases conversion rates.
2- Creation of personalized content
Generative AI can create content tailored to the needs and preferences of specific audiences. It uses data about user behavior and interaction history to produce relevant and engaging messages.
It allows you to generate content at scale without sacrificing personalization, which improves the customer experience and increases the likelihood of conversion. It also frees up time for marketing teams to focus on more creative strategies.
3.- Hyper-individualized messaging
Hyper-individualized messaging refers to creating extremely personalized messages that go beyond traditional segmentation. Use real-time data and predictive analytics to send specific messages to each customer at the right time.
Significantly improves the relevance and resonance of communications, which can increase response rate and customer loyalty. Advanced personalization can also reduce unsubscribe rates and increase marketing ROI.
4.- Predictive modeling
Predictive modeling uses historical data and machine learning techniques to predict future customer behavior, such as the likelihood of purchasing, abandoning, or responding to specific campaigns.
It allows companies to anticipate customer needs and behaviors, optimizing marketing strategies and improving planning and resource allocation. This can lead to more effective campaigns and a better customer experience.
With the help of generative AI , demand generation specialists can optimize processes, improve efficiency, and achieve better results from their campaigns. This technology allows repetitive and complex tasks to be automated, freeing up time for marketing teams to focus on more creative and high-impact strategies.
Do you want to start benefiting from generative AI at Demand Gen? At PGR Marketing & Technology we help you achieve it.
