What are your customers telling you? Maximize the effectiveness of sentiment analysis by using simple tips
September 7, 2017
Sentiment analysis is one method to gather and process customer-supplied information, and then convert it to a quality customer experience. Gartner predicts that 85% of all businesses will compete in the area of customer experience by 2020.
As sentiment analysis explodes onto the scene, what can technology actually do to enhance business efforts?
Hints on applying sentiment analysis
Here are some tips on how to implement various sentiment analysis techniques with ease and utmost efficiency.
– Opt for the proper type of analysis
Some platforms apply automated (machine-powered) sentiment. Others believe in human-powered sentiment analysis, while many use a hybrid system. Decide which is best for your business before launching the effort.
For example, advancements in natural language processing make machine-powered processing a perfect choice for enterprises operating at a large scale with the need for timely analysis of huge data volumes. Though with some limits, automated sentiment analysis is statistically accurate compared with human-powered analysis.
We experimented with more than 10 machine learning algorithms for gathering and processing online customer sentiments in order to find the most accurate and promising ones. You can find the experiments overview and results here (http://www.corevalue.net/sentiment_analysis/).
Human-powered platforms perform better for small project-based data sets. Even in the era of artificial intelligence, human potential in research tasks is still irreplaceable. Platforms like Mechanical Turk or Canvs claim to understand language through nuance and intonation, but it is recognized that interpreting the whole complexity of emotions, sarcasm, double meaning and slang is mostly beyond the reach of the machine learning tools.
– Value opinion Leaders first
Field-oriented influencers spread their thoughts and ideas to a wide audience and specifically impact their field. There are many popular bloggers, social personalities, and columnists that are followed by huge audiences across the digital world, including Twitter, LinkedIn, Facebook, Instagram, YouTube, on personal blogs, etc. Their linguistic behavior can guide public opinion and their sentiment is especially valuable for further opinion evaluations for your dimension of interest. Consequently, you can sharpen your marketing efforts and focus on effective work with influencers, either by mitigating critics or intensifying positive feedback.
– Relevant vocabulary is vital
Domain-specific sentiment dictionaries are also helpful for efficient sentiment analysis. There is a large array of customized sentiment lexicon resources that could help increase the accuracy of your analysis. Some domains are better investigated than others, and some lack thorough studies. Before implementing an analysis, search for an appropriate sentiment dictionary or domain-specific lexicon lists to ease the process.
– Negative reviews first
Customers’ negative sentiment can provide an even more complete picture for your analysis. Evaluation of unfavourable opinions is extremely beneficial for enterprise development, as it gives you the opportunity to address controversy and make your business perform better without compromising efficiency.
Application areas for sentiment analysis
70% of the most successful companies consider customer feedback to be of primary importance. Sentiment analysis helps business to deliver better customer experience by extracting the underlying meaning from the message. Where can it be used? The application area is immense:
- Sentiment analysis enables customer service by fast-tracking positive or negative opinions. This can bring real value by making it possible for the customer to get what he/she really wants.
- Online and offline brand reputation management can also gauge success through consumer sentiment. It allows the measurement of branding, rating status of the brand, and brand influence in the real world. It facilitates evaluation of customer trends and media reviews, as well as the mining of other metrics that drive strategic thinking.
Is marketing a prevalent application area for sentiment analysis? It is, but certainly not exclusive.
- Public thought on the relevant financial searches is scrupulously investigated through social media sentiment, and monitored by the biggest finance and media holdings.
- Big data algorithms informing sentiment are also applied to today’s human resource market. Learning and analysis of employee opinion is crucial in this highly competitive hiring market. Comprehending employee feedback enables HR to deliver a more effective corporate message, address employee satisfaction, and apply effective employee retention plans.
- Business can track product intelligence by means of sentiment analysis. Product performance is benchmarked through social media or reviews defining real customer’s need.
- Successful product development is hardly possible nowadays without end-customer feedback. Receiving accurate and timely opinion from users is vital for maintaining product quality. In the agile environment, customer’s input is especially important, and prompt sentiment measurement allows for instant feedback solicitation, which simultaneously leads to a better quality product release.
- Politics is not devoid of the latest tech achievements. Sentiment analysis is an integral component of a larger strategy. It facilitates the expert mapping and exploitation of voting districts, superior predictive analytics, and better surveys, which provide audience insight at a much deeper level.
Driven by the increase of two-way communication, business is striving to improve the understanding of the potential customer. Analysts and computers aggregate and evaluate human reaction on social media, call-center feedback, and websites. In order to conform to the language evolution, and to re-categorise sentiment, sentiment analytics will continuously evolve.
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