For decades, opinion-measuring techniques like focus groups and phone surveys were key methods of primary market research. This often meant identifying and recruiting a representative audience sample and engaging professional researchers to facilitate the process. It was expensive and cumbersome, but it was important for enterprises to keep their finger on the pulse of consumer sentiment.
For small and medium-sized businesses, though, conducting regular focus groups and surveys simply wasn’t practical. So, we’ll bet that many SMB marketers will be glad to learn that the primary research of the past is being replaced by new methods of sentiment analysis that are faster, cheaper – and often better.
Does My Business Need Sentiment Analysis?
It’s extremely useful for marketers to understand how current or prospective customers feel about a variety of things, such as the company brand, industry trends, specific products, or relevant issues. These is one area where it may actually be useful for businesses to take cues from politicians, who often use this kind of analysis to gauge public opinion as part of their planning and strategy.
In the business world, sentiment analysis can provide insights into:
- Phrases or emotions that reflect brand reputation.
- How people are talking about your, or a competitor’s brand.
- Whether customer interactions are positive or negative.
- How well a company is serving customers.
- Reactions to certain products or services.
These sentiments can often be correlated directly to a business’ key performance indicators.
Four Key Advantages of Modern Sentiment Analysis
Social media and digital communications have opened the door to entirely new methods of gaining customer insight. Now, artificial intelligence can process language from social media, online reviews, customer service logs, and other data sources to detect patterns in text and classify the emotional tone.
In many ways, these new approaches are proving to have key advantages over previous methods.
It’s more representative. Past methods relied on a small number of people to speak for a larger group. AI-powered sentiment analysis is conducted at scale, with the ability to examine massive troves of opinion data from various sources. It can provide more representative views of a larger population.
It’s more accurate. There’s a significant drawback of conducting research via in-person interviews …
People, unfortunately, don’t tell the truth.
It may sound a bit harsh, and we’re not implying anything malicious or overly devious. It’s simply a natural human tendency to worry about being judged – even by a professional researcher. People often answer questions to reflect how they want to be perceived instead of how they actually behave or feel.
Modern sentiment analysis research is conducted very differently. It analyzes unstructured and spontaneous feedback, where there isn’t the same “performative” aspect. And certainly, people can still be untruthful, but a small group has less opportunity to skew the results.
It’s faster. The availability of online data combined with modern AI tools means brands can get an incredibly quick read on brand sentiment or a specific issue. It’s faster and simpler to conduct regular “temperature checks” and to measure audience sentiments before and after key events, such as a product launch or announcement. It’s even possible to gauge reactions in real-time.
It can monitor shifts. We’re living a dynamic age where information is shared rapidly – and attitudes can change just as quickly. The old methods of sentiment research captured a moment in time. AI and machine learning can monitor continuously, tracking not just snapshots, but how sentiments evolve and change. This puts brands in a position to be more nimble, recalibrating quickly if perceptions move off-course.