Abstract
- AI improves productivity. Generative AI enables marketers to increase efficiency by focusing on productivity tools rather than replacing human effort.
- Improve your audience targeting. Generative AI enables deep data exploration and personalized marketing, revolutionizing the way you target your audience.
- Balance AI and humanity. Despite advances in AI, maintaining human interaction in customer service is still critical to satisfaction.
According to a Statista study, marketing and advertising has the highest adoption rate of generative AI in the workplace at 37% (percentage of respondents), which may come as no surprise.
But what may come as a surprise is that the top categories of AI tools are not aimed at marketing, copywriting, chat, or generative art, but rather productivity. (Kaguru)
What does this mean for marketing? Generative AI, and AI more broadly, will ultimately mean that marketers and advertisers are not responsible for the bulk of their marketing work, but rather that their work is more productive. The purpose is to increase the
The following near-term generative AI marketing use cases should be considered by marketers as well as advertisers, and should be considered with data privacy, governance, and consumer trust in mind. At the end of the day, human-generated AI marketing is the best way to protect both brands and consumers from mistakes.
So, what are the use cases for generative AI marketing in the near future?
Futuristic generative AI marketing use cases
Let's explore some:
1. Data exploration
Generative AI gives marketers access to data for easy data exploration and advanced segmentation. Say goodbye to complex query languages and code writing, and instead use natural language processing (NLP) and understanding (NLU) powered by embedded martech-generated AI assistants.
Gain insights by simply asking questions about your data in plain, natural language. Generative AI marketing allows you to easily build audiences for both marketers and advertisers, and even incorporate synthetic data when there is a data gap. By segmenting their customer base and analyzing diverse data sources (think zero, first, second, and third-party data), marketers can engage in targeted, personalized marketing to their audiences. can.
Related article: Generative AI in Marketing: Will it drive growth or detract from your department?
2. Personalized marketing campaigns
Marketers can use generative AI to access data, identify patterns and preferences from customer behavior variables in the audiences mentioned above, and combine this with reinforcement learning to align with substages of the larger customer journey. Create hyper-personalized marketing campaigns that tailor content, offers, and recommendations. individual customer level.
Related Article: Beyond the Hype: Practical Applications and Limitations of Generative AI in Marketing
3. Multimodal dynamic pricing optimization
Generative AI can analyze public information about market conditions, competitor pricing, and customer behavior and combine it with other analytical data streams to optimize dynamic pricing strategies. This enables brands across industries (travel, retail, hospitality, banking, insurance, etc.) to adjust prices in real time to maximize revenue and stay competitive.
4. Chatbots and virtual assistants
Leveraging a combination of generative AI and other AI technologies, chatbots and virtual assistants can engage with customers, answer questions, provide product recommendations, and assist with the sales process.
But buyer beware. Recent research shows that people prefer human interaction and are dissatisfied with virtual assistants powered by generative AI. According to an Ipsos poll, 77% of US consumers think their service chatbots are frustrating, and 88% would rather talk to a human.
Related article: A journey through time: How chatbots have evolved over the decades
5. Customer journey mapping
The path to purchase is not easy. Consider the combination of channels, devices, and points in time that your customers can interact with your brand. The possibilities are endless. Generative AI marketing analyzes secured customer interaction data across all touchpoints to create both inbound and outbound customer journey maps that identify pain points and optimize the user experience. It helps make interactions seamless.
Related article: Old customer journeys and the impact of AI
6. Test, target, and optimize your creatives
Generative AI marketing can improve targeting by helping marketers and advertisers identify the most relevant audience segments for their products and services. This increases campaign efficiency while reducing spending. Additionally, generative AI can streamline the A/B testing process by analyzing results and suggesting optimal variations. This allows marketers to quickly identify high-performing content, designs, or strategies, leading to more effective campaigns.
Related article: Generative AI in Marketing: Smoothing your creative work
7. Market research, trend analysis, and search engine optimization
Generative AI provides access to processes and analyzes vast amounts of data to identify market trends, consumer sentiment, and new opportunities. Marketers can use this information to stay ahead of competitors, whether it's bringing new competitive campaigns to market, new digital properties keyword-optimized based on trends, or shifting market strategies. can.
final thoughts
It's safe to say that generative AI is advancing faster than most people imagined. While there appears to be no limit to the use of generative AI for marketing and advertising purposes, it is important to use these emerging technologies in a responsible manner.
There's no doubt that generative AI marketing can improve our creativity and efficiency as marketers throughout the customer engagement lifecycle, but it's only limited by the limits of our imaginations.
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