Today’s marketers have a rich mine of information about how the public perceives their brand posted across the internet. Yet, trying to track down and understand this information and then translate it into usable data is too laborious for a human team. Consequently, marketing analysts have turned to machine solutions to gauge the sentiment of what customers are saying on the web.
What factors should a marketing analyst consider to choose a sentiment tool that fits their firm’s needs?
What Is Sentiment Analysis?
Sentiment analysis is a subset of text analysis. It searches the web to find posts about your business or product and identifies three specific things:
- Topic – is the post about the subject matter the marketing analyst wants to track
- Opinion – is the data source positive or negative?
- Emotion – what feelings drive the post? Understanding the mood of a particular post can be very tricky for text analysis software. Sarcasm can be particularly difficult to pick up for textual or AI-based sentiment tools.
Factors to Consider Before Choosing a Sentiment Analysis Tool
Is Sentiment Analysis the Best Text Tool to Fit Your Firm’s Needs?
Sentiment tools are only one five types of text analysis tools available. Does another type of text analysis better fit your firm’s analytical needs?
Types of Text Analysis:
- Sentiment – recognizing the emotions and intent of internet posts
- Explicative – unearthing the underlying reason for a particular sentiment assessment
- Summarization – finding the significant content in a single source or a defined range of sources
- Classification – identifying the subject of a source or range of sources
- Investigation – identifying the best sources for a specific issue
- How Well Does It Handle Complex Expressions?
Misunderstanding the emotion or opinion expressed by a post can yield a wildly inaccurate assessment. For example, failing to pick up sarcasm could make the software classify a highly negative opinion as an extremely positive one. Clearly, marketing insight requires accurate data.
- How Good Is the Software’s Report Generation?
A tool that can take unstructured data from across the web an analyze it is a great tool. But, it’s not very useful if it fails to generate reports that can help marketing teams understand the implications of the data.
- How Many Data Sources Can the Tool Handle?
There are a wide variety of data sources to survey across the internet. If a tool only samples a limited scope of opinions, it could miss key data that will help an analyst understand customer opinion. A good sentiment analysis tool will be able to handle many different sources and kinds of data.
- Does the Software Allow Your Firm to Manually Train the Tool?
Every firm or project can have specific analytical needs. The same data might not hold the same significance for even direct competitors. To get the most out of a sentiment tool, it usually will have to have the ability for marketing analysts to manually train the tool.
Manual training requires an extensive list of annotated sentences to help the machine learn to identify the sentiment of a post.
Benefits of Sentiment Tools
Sentiment analysis can provide great insight in tracking how public sentiment changes over time. When correlated with information about specific ads or marketing campaigns, this data can help marketing teams understand the impact of their efforts. However, firms must take great care to ensure their sentiment tools fit their analytical needs.
