Public sentiment, AKA opinion mining, plays a crucial role in shaping the success of PR and marketing campaigns. Successfully understanding and leveraging it can transform businesses. So why isn’t everyone doing it?
Once the preserve of political campaigns, public sentiment is a measure of how people feel about your business, right now. The joyous thing about public sentiment is that you don’t need to gather textual data by issuing customer feedback surveys that no one fills in, or by conducting market research via a team of clipboard-wielding marketers. Your customers and potential customers are already telling you how they feel via social media, online reviews and by commenting on news articles about your company: everywhere they have touchpoints with your brand.
The difficulty of an effective sentiment analysis system
However, the reason public sentiment is often underused is that human language is harder to measure than simple metrics such as the number of views, clicks, shares or survey responses.
Aspect-based sentiment analysis, or ASBA, is one way of measuring a sentiment score, by attributing sentiments such as “fabulous” to aspects of your business such as “breakfast buffet”. Even though Artificial Intelligence sentiment analysis algorithms exist, it’s hard to assess the emotional tone of seemingly positive and negative words, or natural language processing (NLP), without context. Machine learning can’t tell whether your customer is commenting “Great” because you’ve fixed their problem, or in a sarcastic manner because you’ve cancelled their flight.
Human eyes are needed in addition to a machine learning algorithm for effective sentiment analysis, making it more time-consuming and costly to perform sentiment analysis than it is to have a quick glance at Google Analytics. Coming up with your own sentiment analysis solution, including rule-based sentiment classification systems and consistent criteria for how to record overall sentiment can take longer, but will give you deeper insights than an automatic sentiment analysis tool. A middle ground might be to use a combination of both.
If you already outsource your social media monitoring to an agency, it may be simpler for the same data scientists to be performing social media sentiment analysis on your behalf too. This is particularly the case if you’re an international business requiring multilingual sentiment analysis, or wish to categorise text less bluntly than simply positive and negative sentiments, for example on a sliding scale (known as fine-grained sentiment analysis).
Monitoring negative sentiment and positive sentiment
Businesses that invest their resources into making sentiment analysis work for them gain actionable insights that can improve business performance and prevent waste of time and money.
Going way beyond a list of positive or negative words, applying sentiment analysis results can engage audiences more effectively and deliver the products and services they demand.
Insights into audience preferences
Monitoring public sentiment provides valuable insights into audience preferences, opinions and trends. By understanding what resonates with their target audience, businesses can tailor their PR and marketing strategies to align with customer expectations, resulting in more impactful and relevant marketing. This can lead to a virtuous circle of positive mentions on social media platforms, further increasing sentiment scores.
If a social media campaign isn’t landing well with your audience, you have instant information and can fix the problem. You can also tweak your business model, or decrease production of certain products if your sentiment insight shows your customers are moving on to the next big thing.
Effective crisis management
Public sentiment analysis allows businesses to gauge public perception during crises. By monitoring sentiment, companies can identify potential reputational risks, address concerns promptly and develop effective crisis management strategies to mitigate damage.
You can also spot a crisis while it’s still small enough to manage, via your sentiment analysis system. By keeping a basic sentiment analysis score, you’ll see instantly if there’s a change in how your business is perceived.
Work your learnings into your crisis management plan. Responding to public sentiment and changes to sentiment scores during critical moments helps maintain trust among your clients and preserve brand reputation.
Sentiment analysis-based communication enables businesses to personalise their engagement efforts. By using accurate sentiment analysis, and aligning messaging with the prevailing sentiment, companies can connect with their audience on a deeper level, creating a sense of empathy and understanding.
For example, this summer’s marketing success of the Barbie movie took some businesses by surprise, while others had monitored sentiment data on positive words in the build-up to the film’s release and were ready to ride the pink wave with those of their customers that were Barbie fans.
Personalised communication using sentiment analysis datasets improves customer experience, fosters customer loyalty and enhances brand reputation.
Opportunity for innovation
A sentiment analysis model helps businesses identify emerging trends and customer needs. By keeping their finger on the pulse of public sentiment, companies can adapt their products, services and marketing strategies to meet evolving demands, gaining a competitive edge and driving innovation within their industry.
For example, the production of certain products could be slowed or halted in response to worsening public sentiment around the economy if you’re alerted to this by your sentiment analysis tools.
You can also easily monitor what consumers do and don’t like about your competitors via their social media, and learn from their successes and mistakes.
Strengthened brand reputation
By actively engaging with public sentiment, businesses can demonstrate their commitment to customer satisfaction and address concerns promptly. Brand sentiment analysis allows companies to build trust, enhance their brand reputation, and position themselves as customer-centric and responsive organisations.
Frontline staff are responsible for representing your business to your customers, and while monitoring online sentiment, you can also see how your customer service staff are performing and how clients react Any interactions that lead to negative sentiments can be learned from in real-time, and you can monitor how different positive, negative or neutral words used by customer service staff are responded to by consumers, and tweak the language you use as a result.
Is performing sentiment analysis important for businesses?
Customer sentiment analysis offers deep learning into sentiment expressed by customers, which is vital for PR and marketing departments. It offers meaningful insights into audience preferences, crisis management, personalised communication, innovation opportunities and brand reputation.
By applying negative or positive sentiment analysis effectively through rule-based systems, businesses can connect with their target audience on a deeper level, tailor their messaging and build lasting relationships.
Despite sentiment analysis challenges such as the issues with sentiment analysis tools, as machine learning (ML) sentiment analysis techniques evolve we’re likely to see improved rule-based sentiment analysis become available.
Public sentiment analysis models help businesses stay attuned to the needs and expectations of their audiences, contributing to business growth, customer loyalty and overall success.