Effective consumer research involves identifying and analyzing trends. Brands that understand trend analytics can utilize data on consumer behavior to spot opportunities to distinguish themselves from competitors.
The key is knowing which broader trends are relevant to the brand’s industry and target audience. With the rise of innovative AI and data analytics technology, companies have more access to data on trends in consumer behavior than ever before. Companies that can effectively capture and sort through this data can implement branding strategies that respond to existing trends and anticipate future trends, creating a competitive edge in their market.
What Are Trend Analytics?
Trend analytics involves gathering and analyzing data on the attitudes and behaviors of a brand’s target audience, with the goal of identifying shared sentiments and anticipating possible shifts in behavior that could be relevant to a brand’s strategic approach. This process should involve consumer research on purchases of the company’s product or service, but it should also involve studying attitudes and behaviors that may initially appear to be less directly relevant.
For example, trends in attitudes towards social, political, and environmental issues can have a significant impact on consumer behavior. If a clothing brand’s target audience is millennials, it is important to understand not just how millennials feel about fashion, but also how they feel about environmental and social issues related to the manufacturing of clothing. This may include issues such as working conditions and sustainability of production methods. Using trend analytics, companies can study these sorts of broader cultural trends and create products and strategies that connect with the zeitgeist of the consumers they want to reach.
Using Sentiment Analysis to Identify Trends
As consumers turn to social media to discuss brands, products, and brand-relevant trends, consumer research has shifted away from surveys and focus groups and towards analyzing online content. Sentiment analysis, which utilizes AI techniques such as natural language processing (NLP), text analysis, and image analysis to identify the emotions expressed in online content, has become an indispensable tool for identifying trends in modern consumer research.
For example, NetBase Quid AI enables users to identify positive or negative attitudes expressed in both image-based and text-based content, including posts on social media platforms such as Instagram, Facebook, and Twitter. AI can sort through a large amount of data and identify posts that are relevant to a brand, even if the brand is not explicitly mentioned in the post. This data is then organized and presented with visualizations that highlight commonalities such as key words or images that tend to appear in positive or negative posts.
Companies can also use sentiment analysis for consumer research on targeted audience segments rather than brand-focused content. If a company is considering a campaign that emphasizes its brand’s commitment to a particular social issue, sentiment analysis can be useful in identifying the appropriate tone to use in the campaign. A company could perform sentiment analysis on an audience segment of millennial or Gen Z consumers to identify key words and phrases used in their posts about the issue. In this way, sentiment analysis identifies trends in how a target audience communicates, and understanding these trends helps a brand communicate with that target audience.
Sentiment analysis generates data that is invaluable when identifying trends. The data sets analyzed are larger than those available from traditional consumer research methods such as surveys, and they can provide a more fine-grained and natural representation of emotional outlooks. Companies use sentiment analysis to move beyond considering trends in behavior; instead, they track trends in how consumers feel about key issues.
Understanding the Trends that Matter for Consumer Research
While consumer research tools provide companies with the ability to identify a wide variety of trends in consumer attitudes and behaviors, the most effective use of these tools is to distill information and focus only on the trends relevant to strategic decisions.
The goal in utilizing trend analytics is to learn more about the trends that matter to a brand’s target audience. Using AI-based tools such as audience segmenting and sentiment analysis, companies are better able to focus their consumer research on the appropriate target audience and identify the trends that really matter to that audience.
