The goal in consumer research has always been to anticipate trends. With the number of variables that contribute to trends, including current events, technological developments, and unexpected pop culture phenomena, predicting where an industry is headed has never been an exact science. But while no company can know the future, there are more and less precise methods of prediction when it comes to consumer research. Traditional methods such as surveys and focus groups could yield some consumer insights, but companies are now using sentiment analysis, a powerful AI-based tool, to get ahead of trends by analyzing the online conversation.
What Is Sentiment Analysis?
Sentiment analysis utilizes AI to analyze large data sets of online content and discern the emotional tone and opinions expressed. Content analyzed includes posts on social media platforms such as Facebook, Twitter, and Instagram; online review platforms such as Yelp; and news websites.
When conducting sentiment analysis, the aim is to not only assess which topics, brands, and products are the subject of the highest volume of online conversation, but to also measure the positive or negative valence of that conversation.
Using Sentiment Analysis to Make Predictions
Making predictions of industry trends using sentiment analysis requires an understanding of which channels to target and how to interpret the data uncovered.
A helpful initial step would be to use sentiment analysis to conduct consumer research on general industry keywords, including popular brand names, across a variety of social media and news platforms. This process should tell you which brands and topics tend to be discussed most on specific platforms. Conducting this process over time can identify when brands or industry keywords receive spikes in attention.
This information is valuable for understanding which channels to target with marketing campaigns. A snack brand might recognize that there is untapped potential in connecting with influencers on TikTok, for example.
But the key insights provided by sentiment analysis extend beyond understanding the volume of mentions. Not all attention is good attention. Some brand-relevant topics will be the subject of more positive posts than others.
For example, a competitor may be the subject of a high volume of news pieces, but it is crucial to assess the tone of those pieces. If they tend to discuss the competitor’s use of automation in a positive light, then this could suggest a heavy emphasis on innovative automation in marketing and product development might be a productive avenue to pursue. But if they tend to discuss automation in a negative light, perhaps due to employees’ or customers’ complaints or technical problems, this suggests that emphasizing your company’s competing approach to automation requires more nuance.
The takeaway is that understanding industry trends requires more than simply understanding which topics are being discussed; it requires an understanding of how they are being discussed, and this level of understanding is what sentiment analysis is designed to achieve.
Once a company understands the emotional tone of the online conversation around a brand, product, or brand-relevant topic, it can better predict consumer behavior within the industry. Sentiment analysis enables a company to see which topics are trending up in terms of positive sentiment, and these topics do not always overlap with those topics trending up in terms of raw volume of mentions. Yet the former understanding is more valuable than the latter when it comes to getting ahead of positive consumer sentiment and positioning a brand to draw positive rather than negative attention.
Choosing the Right Targets for Trend Analysis
Whether a company is in a retail industry such as clothing or consumer electronics, the entertainment industry, or a service industry such as dining or travel, sentiment analysis can help predict trends. The technology is not industry specific; it is designed to understand sentiment and can be targeted to consumers across a variety of profiles. This might mean analyzing consumers on a specific social media platform, consumers that fit a particular age demographic, or consumers that have a particular shared interest profile.
Sentiment analysis’ possibilities for consumer research are endless, but to gain actionable consumer insights, the key is to understand what a company should be trying to predict, and to direct the technology at the relevant targets. Equipped with this understanding sentiment analysis can be a powerful social listening tool to access a high volume of fine-grained data that would otherwise be unavailable and that is invaluable when predicting industry trends.