The essential
- AI increases productivity. Generative AI allows marketers to improve efficiency rather than replace human effort, by focusing on productivity tools.
- Improve audience targeting. Generative AI enables deep data mining and personalized marketing, revolutionizing the way audiences are targeted.
- Balance AI and human touch. Despite advances in AI, maintaining human interaction in customer service remains crucial for satisfaction.
Perhaps unsurprisingly, marketing and advertising has the highest adoption rate of generative AI in the workplace at 37% (share of respondents), according to a survey by Statist.
However, what may come as a surprise is that the main categories of AI tools are not for marketing, copywriting, chat, or generative art, but rather for productivity. (Kaggle)
What does this mean for marketing? This means that ultimately, generative AI, and AI in general, is about enabling marketers and advertisers to be more productive in their work, instead of doing the lion’s share of the work marketing in their place.
The below AI generative marketing use cases in the near future are ones that marketers and even advertisers should consider – and do so with data privacy, governance and consumer confidence. After all, with the help of man generative AI marketing is the best way to protect brands and consumers from any missteps.
So, what are the use cases for AI generative marketing in the near future?
Generative AI Marketing Use Cases in the Near Future
Let’s explore a few:
1. Data mining
Generative AI allows marketers to access data for effortless data exploration and advanced advancements. segmentation. Say goodbye to complex query languages and writing code and use natural language processing (NLP) and understanding (NLU) powered by built-in martech generative AI assistants.
Just ask a question in simple, natural language about your data, and it will provide you with insights. Generative AI marketing can even effortlessly create audiences for marketers and advertisers, even incorporating synthetic data where gaps exist. By segmenting their customer base and analyzing various data sources (think zero, first, second, and third-party data), the marketer obtains highly targeted and personalized marketing audiences.
Related article: Generative AI in marketing: a boost or a bust for your service?
2. Personalized marketing campaigns
Marketers can use generative AI to access data to identify patterns and preferences from customer behavior variables contained in the audiences above and combine this with reinforcement learning to create hyperpersonalized marketing campaigns — tailor content, offers and recommendations to sub-steps of a broader customer journey — at the individual customer level.
Related article: Beyond the Hype: Practical Applications and Limitations of Generative AI in Marketing
3. Optimization of multimodal dynamic pricing
Generative AI can analyze publicly available information about market conditions, competitor prices, and customer behavior – and combine it with other analytical data streams – to optimize dynamic pricing strategies. This will help brands across various industries (travel, retail, hospitality, banking, insurance, etc.) adjust their prices in real-time to maximize revenue and stay competitive.
4. Chatbots and virtual assistants
Powered by a combination of generative AI and other AI techniques, chatbots and virtual assistants can interact with customers, answer queries, provide product recommendations and assist in the sales process.
But buyer beware: Recent studies reveal that people prefer human interaction and are frustrated by AI-powered generative virtual assistants. An Ipsos survey found that 77% of U.S. consumers think customer service chatbots are frustrating, and 88% would prefer to speak to a person.
Related article: Time Travel: How Chatbots Have Evolved Over the Decades
5. Customer journey mapping
The path to purchase is not simple. Think about the combination of channels, devices and moments in which a customer can interact with your brand: the possibilities are endless! Generative AI marketing can help brands make these interactions seamless by analyzing protected customer interaction data across all touchpoints to create inbound and outbound customer journey maps that identify pain points and optimize user experience.
Related article: The old customer journey and the impact of AI
6. Creative testing, targeting and optimization
AI generative marketing can improve targeting by helping marketers and advertisers identify the most relevant audience segments for their products or services. This increases campaign effectiveness while reducing expenses. Additionally, generative AI can streamline the A/B testing process by analyzing results and suggesting optimal variations. This helps marketers quickly identify the best-performing content, designs, or strategies, leading to more effective campaigns.
Related article: Generative AI in marketing: streamlining creative operations
7. Market Research, Trend Analysis and Search Engine Optimization
Generative AI provides access to processes and analyzes large amounts of data to identify market trends, consumer sentiments and emerging opportunities. Marketers can use this information to stay ahead of the competition, whether it’s new in-market competitive campaigns, new digital properties optimized by keywords based on trends, or a pivot in market strategy.
Final Thoughts
It’s safe to say that generative AI is advancing at a faster pace than almost anyone imagined. And while there seems to be no limit to the use of generative AI for marketing and advertising purposes, it’s important to use these emerging technologies in a way that responsibly.
There is no doubt that AI generative marketing can improve our creativity and effectiveness as marketers throughout the customer engagement lifecycle and is only limited by the limits of our imagination !
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