Marketers are tapping into AI’s analytics and research capabilities in higher numbers than for genAI content production, according to a new survey of over 1,200 marketers by adtech platform Mediaocean.
The same marketers are also keeping a watch on consumer interest in AI and other trending technologies. Where AI topped the list of consumer trends in a previous survey, CTV now leads the field.
AI capabilities. Data analysis (45%) and market research (40%) were the top ways marketers are using AI.
“Marketers continue to focus on data analysis and market research to enhance decision-making processes, to optimize campaigns and gain deeper insights into consumer behavior,” said Karsten Weide, principal and chief analyst for W Media Research, during a roundtable discussion about the report.
“Using generative AI for automated content creation, such as dynamic creative optimization, that only comes after analytics,” said Weide.
Consumer trends. Many marketers also rated genAI as a top consumer trend (55%), just below CTV (56%). TikTok/social video came in third at 47%. GenAI scored first in the previous survey.
Here are all the top consumer trends rated by marketers and where they landed in the rankings:
“As so many dynamics are changing and with the focus on first-party data and performance, brands still need reach,” said Deborah Wahl, former CMO of General Motors, at the roundtable. “It’s incredible watching the growth of the CTV market and where that can go. … I changed a lot of the spending, when I was running things [at General Motors] to really focus on [CTV], and it’s good to see that’s the number one trend that everyone is looking at.”
Dig deeper: 3 reasons why digital video and CTV are booming in 2024
Why we care. Creating images and texts from a simple prompt is working its way into marketing workflows. Three-quarters of marketers in this survey haven’t yet taken the plunge, perhaps due to lingering concerns over brand safety. What many marketers can verify, however, is the ability for AI to help “sift through the data you often can’t fully process,” Weide said.
With the holidays coming up, marketers will likely deploy AI capabilities to help shoppers find the right gift. Consumers are interested in how retailers are using these tools. And for wary consumers, they might not even know when the experience is AI-powered.
The full report can be read here (registration required).
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**AI Use Cases: Data Analysis and Market Research Lead the Way**
Artificial Intelligence (AI) has rapidly evolved from a futuristic concept into a transformative force across various industries. Among the myriad of applications, two areas where AI has made significant strides are data analysis and market research. These fields, traditionally reliant on human expertise and manual processes, are now being revolutionized by AI technologies, enabling businesses to derive deeper insights, make more informed decisions, and stay ahead in an increasingly competitive landscape.
### The Role of AI in Data Analysis
Data analysis is the backbone of modern business strategy. It involves the collection, processing, and interpretation of data to uncover patterns, trends, and relationships that can inform decision-making. However, the sheer volume of data generated today—often referred to as “big data”—poses a significant challenge for traditional data analysis methods. This is where AI steps in.
#### 1. **Automated Data Processing**
AI-driven algorithms can process vast amounts of data at unprecedented speeds, far surpassing human capabilities. Machine learning models can be trained to recognize patterns in data, identify anomalies, and even predict future trends based on historical data. This automation not only saves time but also reduces the risk of human error, leading to more accurate and reliable insights.
#### 2. **Predictive Analytics**
Predictive analytics is one of the most powerful applications of AI in data analysis. By analyzing historical data, AI models can forecast future outcomes, such as sales trends, customer behavior, or market demand. This allows businesses to anticipate changes and make proactive decisions, whether it’s adjusting inventory levels, launching targeted marketing campaigns, or optimizing pricing strategies.
#### 3. **Natural Language Processing (NLP)**
Natural Language Processing (NLP) is a branch of AI that enables machines to understand and interpret human language. In data analysis, NLP can be used to analyze unstructured data, such as customer reviews, social media posts, or survey responses. By extracting sentiment, key themes, and other insights from this data, businesses can gain a deeper understanding of customer preferences and pain points.
#### 4. **Real-Time Analytics**
AI-powered systems can analyze data in real-time, providing businesses with up-to-the-minute insights. This is particularly valuable in industries where conditions can change rapidly, such as finance, retail, or logistics. Real-time analytics allows businesses to respond quickly to emerging trends, mitigate risks, and capitalize on new opportunities.
### AI in Market Research: A Game Changer
Market research is another area where AI is making a profound impact. Traditionally, market research has involved time-consuming processes such as surveys, focus groups, and manual data analysis. AI is streamlining these processes, making market research faster, more accurate, and more actionable.
#### 1. **Enhanced Data Collection**
AI can automate the collection of data from a wide range of sources, including social media, online reviews, and customer feedback forms. AI-powered tools can scrape data from the web, aggregate it, and organize it in a way that is easy to analyze. This not only speeds up the data collection process but also ensures that businesses have access to a more comprehensive and diverse dataset.
#### 2. **Sentiment Analysis**
Sentiment analysis, powered by AI, allows businesses to gauge public opinion and customer sentiment in real-time. By analyzing text data from social media, news articles, and other sources, AI can determine whether the sentiment is positive, negative, or neutral. This insight is invaluable for understanding how customers perceive a brand, product, or marketing campaign, and can inform strategies for improving customer satisfaction and brand reputation.
#### 3. **Customer Segmentation**
AI can analyze large datasets to identify distinct customer segments based on behavior, preferences, and demographics. This enables businesses to tailor their marketing efforts to specific groups, improving the relevance and effectiveness of their campaigns. AI-driven customer segmentation can also reveal emerging trends and shifts in consumer behavior, allowing businesses to adapt their strategies accordingly.
#### 4. **Competitive Analysis**
AI can be used to monitor competitors’ activities, including pricing strategies, product launches, and marketing campaigns. By analyzing this data, businesses can gain insights into their competitors’ strengths and weaknesses, identify market gaps, and develop strategies to differentiate themselves in the market. AI-driven competitive analysis can also help businesses anticipate competitors’ moves and respond proactively.
### The Future of AI in Data Analysis and Market Research
As AI continues to advance, its applications in data analysis and market research are expected to become even more sophisticated. Here are a few trends to watch:
#### 1. **AI-Driven Personalization**
AI will enable businesses to deliver highly personalized experiences to customers by analyzing individual preferences, behaviors, and interactions. This level of personalization will not only enhance customer satisfaction but also drive loyalty and increase lifetime value.
#### 2. **Integration of AI with IoT**
The integration of AI with the Internet of Things (IoT) will allow businesses to collect and analyze data
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