Customer Service

How sentiment analysis and social listening can improve customer experience

Sentiment analysis may be popular with social media, but it probably has far more uses outside of social media. Sentiment analysis and social listening are invaluable tools that enable organisations to gather valuable insights into customer experiences. It involves the automated extraction of emotions, feedback and attitudes expressed in textual data. Machine learning (ML) techniques such as natural language processing (NLP) and associated calculations help analyse if the data collected is positive, negative or neutral.

When NLP is incorporated into chatbots and voicebots, both tools become almost human-like in their conversational and language skills, and can adjust tones during conversations. By leveraging these techniques and technologies, businesses can proactively address customer needs, resolve issues, and ultimately deliver an exceptional customer experience.

Points to ponder

Before embarking on this journey, organisations must be aware of certain facts:

• What is the purpose of the exercise? Is it to understand the competition in the industry or to identify the most discussed features of a product or service? 
• What are the metrics that would answer the questions asked? While mentions in online posts can give a clear idea about the volumes of conversation about the product or service, the sentiments marked such as likes, comments, favourites - indicate whether the opinions will harm or help the brand discussed, and the engagement with the brand gives an idea about what features of the brand appeal to the customer. 
• Analysis of all the information collected is the most challenging step. There are tools available or the organisation could have an internal team of scientists and data analysts to collect and analyse the data. While the scientists could predict patterns by using past patterns, data analysts could gather meaningful insights.

Key benefits of sentiment analysis and social listening

Sentiment analysis, or opinion mining, and social listening enables organisational departments to attach measurable metrics to pieces of data and use them in daily functions. Data-driven decisions and targeted actions can be taken to boost customer satisfaction. Benefits of sentiment analysis include:

Real-time feedback and action

Organisations can monitor customer sentiment in real-time and whenever possible, take prompt action to address any negative issues and experiences. Customer queries and complaints can be managed immediately too. A real-time alert system that gets triggered when a particular subject is mentioned or an influencer is active can help getting updates quickly. Early detection of such posts can help organisations manage the situations at the right time.

Identify trends

By considering customer sentiments at various touchpoints, organisations can easily identify areas for improvement and also recurring trends. Strategies to address them can be developed proactively. Interest about the product or service can be gauged and brand owners get a better idea about how to connect with the customer.

Personalise customer experiences

By understanding customer sentiment, organisations can customise their offerings and communication to meet individual needs, resulting in a more personalised and engaging customer experience.

Analyse the competition

Organisations can gain a competitive edge by monitoring competitor activities and analysing customer sentiments. Gaps can be identified and strategies can be developed to meet these requirements.

Identify individual or group influencers

Social listening enables organisations to identify individuals or groups that influence customer action. Influencers can be engaged in conversation and persuaded to be brand advocates who would then drive positive sentiments.

Listening posts

There are many points or sources from which data for sentiment analysis can be procured. Some of them are:

Discussion points

Sentiment analysis sources are not limited to social media posts only. Products and services could be discussed in chatbot communication, phone logs, review websites, articles, emails, internal communication, support tickets and more. This is where artificial intelligence (AI) steps in. It can analyse text and human language from all these sources and provide real-time insights. Based on these data-driven insights, organisations can address specific situations.

Requests

Organisations are frequently overwhelmed by requests from customers on a wide variety of topics. It is with the help of NLP and natural language understanding (NLU) that customer emotions and tones are deciphered from both the written and spoken requests. The urgency of each request can be understood and sorted better by the AI techniques. Responders can then prioritise the jobs and also ensure that each request is diverted to the appropriate channel or department.

Project discussions

Sentiment analysis can be utilised within the organisation too. Project managers can get insights into employee sentiments regarding a project - how the project is perceived, how each team member feels about his/her role in it, and how effective the team communication is. Any negative sentiments, if valid, can be addressed and nipped in the bud. The manager can steer the project better after being updated with all the information.

By keeping tabs on employment websites, internal messaging platforms and email communication, organisations can easily gather insights into employee sentiments and take necessary steps to reduce turnover.

Sentiment analysis is a way of life

When it comes to experience and customer service solutions, consumer expectations are undoubtedly high. Automated sentiment analysis provides actionable insights to organisations enabling them to better understand customer pain points as well as what makes customers happy and satisfied. Metrics provided by sentiment analysis can help organisations make sound data-driven decisions into many unexpected areas of customer experience.

If the data sourcing techniques and the analysing algorithms are accurate and sound, most organisations can gain significantly from sentiment analysis in terms of customer support, employee retention, marketing efforts, product development and more.

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