Many marketers are familiar with using generative AI for its content-creation capabilities, but AI presents opportunities to help marketers natively within applications they use in their martech stack every day.
Beyond generative AI, opportunities await marketers with machine learning and other forms of AI. What keeps many organizations from moving forward with these initiatives are obstacles around team training and data governance.
Other areas of the organization, including security, legal and compliance will also present challenges to adoption of these new technologies.
This discussion from the Fall 2024 MarTech Conference was led by Craig Schinn, Co-founder and COO, Actable, and Michelle Simone, Principal Consultant, Pepper Foster Consulting.
Among the topics covered in this discussion:
- 4:59: Examples of AI use cases, in customer service and HR.
- 7:23: Why is there a lack of adoption of AI and machine learning at the enterprise level?
- 12:29: AI features in martech applications.
- 14:00: How to think about the governance of AI in your organization.
- 17:24: Is generative AI over-shadowing machine learning and other forms of AI.
- 20:16: Obstacles to AI adoption (and potential solutions).
- 30:57: Primary concerns about deploying AI.
- 40:00: AI-powered applications marketers in the discussion are using.
- 47:20: Use cases for custom GPTs.
Dig deeper: AI in marketing: Examples to help your team today
The post Marketers discuss using AI beyond content creation appeared first on MarTech.
**Marketers Explore Expanding AI Applications Beyond Content Creation**
Artificial intelligence (AI) has become a transformative force across industries, and marketing is no exception. While AI’s role in content creation—such as generating blog posts, social media captions, and product descriptions—has garnered significant attention, marketers are now exploring its potential in other areas of the marketing ecosystem. From customer insights to predictive analytics, AI is proving to be a versatile tool that can revolutionize how brands engage with their audiences and optimize their strategies.
### The Evolution of AI in Marketing
AI’s initial foray into marketing was largely focused on automating repetitive tasks and enhancing efficiency. Tools like OpenAI’s ChatGPT, Jasper, and Copy.ai have enabled marketers to generate high-quality written content at scale, saving time and resources. However, as AI technology continues to advance, its applications are expanding beyond content creation to encompass a broader range of marketing functions.
Marketers are now leveraging AI to improve customer targeting, personalize user experiences, enhance campaign performance, and even predict future trends. This shift is driven by the growing availability of data, advancements in machine learning algorithms, and the increasing demand for more sophisticated marketing strategies.
### AI Applications Beyond Content Creation
Here are some of the emerging ways marketers are using AI beyond generating content:
#### 1. **Customer Insights and Behavior Analysis**
AI-powered tools can analyze vast amounts of consumer data to uncover patterns and insights that would be difficult for humans to detect. By analyzing customer behavior, preferences, and purchase history, AI can help marketers segment their audiences more effectively and create highly targeted campaigns.
For example, AI can identify which products a customer is likely to purchase next or predict when they might churn. This enables marketers to take proactive measures, such as offering personalized discounts or sending timely reminders, to retain customers and boost sales.
#### 2. **Predictive Analytics**
Predictive analytics is one of the most promising applications of AI in marketing. By analyzing historical data, AI algorithms can forecast future trends, such as which products will be in demand or which marketing channels will deliver the best ROI. This allows marketers to allocate their budgets more effectively and make data-driven decisions.
For instance, AI can predict the success of a marketing campaign before it even launches by simulating different scenarios and identifying potential challenges. This reduces the risk of failure and ensures that resources are used efficiently.
#### 3. **Personalization at Scale**
Personalization has become a cornerstone of modern marketing, but delivering personalized experiences to millions of customers can be a daunting task. AI makes it possible to achieve personalization at scale by analyzing individual customer data and tailoring messages, recommendations, and offers accordingly.
E-commerce platforms like Amazon and Netflix have long used AI to provide personalized product and content recommendations. Now, other industries are following suit, using AI to create hyper-personalized email campaigns, website experiences, and even dynamic pricing models.
#### 4. **Chatbots and Conversational AI**
AI-driven chatbots and virtual assistants are transforming customer service and engagement. These tools can handle a wide range of tasks, from answering frequently asked questions to guiding users through the purchase process. Unlike traditional chatbots, modern conversational AI systems are capable of understanding context, sentiment, and intent, making interactions more natural and effective.
For marketers, chatbots offer a unique opportunity to engage with customers in real-time, gather valuable data, and drive conversions. They can also be integrated into social media platforms, messaging apps, and websites, ensuring seamless communication across channels.
#### 5. **Ad Optimization**
AI is revolutionizing the way marketers approach advertising. Programmatic advertising platforms use AI to automate the buying and placement of ads, ensuring that they reach the right audience at the right time. AI can also analyze ad performance in real-time and make adjustments to improve results, such as tweaking ad copy, targeting parameters, or bidding strategies.
Additionally, AI-powered tools can generate ad creatives, test multiple variations, and identify the most effective combinations. This not only saves time but also maximizes the impact of advertising campaigns.
#### 6. **Voice and Visual Search Optimization**
As voice and visual search become more popular, marketers are turning to AI to optimize their content for these emerging technologies. AI can analyze voice queries and image searches to identify relevant keywords and trends, helping brands improve their visibility in search results.
For example, AI can help retailers optimize their product images and descriptions to ensure they appear in visual search results on platforms like Google Lens or Pinterest. Similarly, AI can analyze voice search data to identify conversational keywords and phrases that resonate with users.
#### 7. **Customer Journey Mapping**
Understanding the customer journey is crucial for creating effective marketing strategies. AI can map out the entire customer journey by analyzing data from multiple touchpoints, such as website visits, social media interactions, and email engagement. This provides marketers with a comprehensive view of how customers interact with their brand and where improvements can be made.
AI can also identify bottlenecks in the customer
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