Maisie Lloyd
Maisie is the Digital Content Manager at Intelligency, handling all things creative for the agency. Her experience centres around the production of digital content, pertaining to graphic design, writing copy, and video and audio content.
AI sentiment analysis is becoming increasingly valuable as businesses collect more feedback than ever before. Reviews, survey responses and social media conversations can provide useful insight, but manually reviewing hundreds of comments can be time-consuming.
By analysing large volumes of feedback, AI can help marketers identify recurring themes, common concerns and areas of interest much faster. This allows businesses to better understand audience perception and make more informed decisions around their marketing, content and customer experience.
How can AI sentiment analysis be used?
AI sentiment analysis can provide greater insight than clicks, for instance. This helps them develop a stronger strategy around products, content, messaging and even customer service.
Other applications of these insights include:
- Competitor research
AI can help marketers understand how customers feel about competitors. This can reveal common frustrations and pain points, helping businesses position themselves more effectively and attract dissatisfied customers.
- Content and campaigns
This can provide qualitative data that explains why audiences are responding in a certain way. While clicks show what users do, sentiment analysis helps marketers understand how they feel.
- Brand monitoring
Its applications also extend to being able to monitor customer responses. If customers are reporting a negative experience, you’re able to anticipate and correct before it has the chance to develop into a greater issue.
- Market research
This can also offer insight to marketers on what their audience likes, dislikes and what topics they connect with the most. This helps marketers make an informed decision around campaigns, content and customer interactions.
How can marketers use the data with AI?
Traditionally, marketers would need to manually look through comments, reviews and surveys to gauge the customer’s response. Once customer feedback and conversations have been collected, AI can analyse the data and identify patterns, trends and recurring themes.
Imagine your business receives:
- 200 Google reviews
- 500 survey responses
- 1,000 LinkedIn comments
Reading all of that manually would take days.
AI can quickly tell you:
Positive themes
- Friendly team
- Flexible bookings
- Good location
Negative themes
- Parking
- Internet speed
- Service/ product availability
Emerging topics
- Demand for specific services or products
- Interest in certain topics
- Requests for more availability
AI sentiment analysis gives marketers a faster way to understand how audiences feel about their brand. Rather than manually reviewing hundreds of comments, reviews and survey responses, AI can identify positive and negative themes, emerging trends and customer concerns. These insights can then be used to improve content, campaigns, products and customer experience.
