Bad customer reviews left about a company on a social media website, on the company’s own website or even review sites such as Trip Advisor can spread quickly. No matter how skilled and trained your staff and customer service team are, mistakes will be made and customers will complain.
Similarly, a reduction in complaints does not necessarily mean an increase in customer service, for example, our infographic will tell you that the likelihood of customer complaints online after a bad experience is only ay 31%. Just because you have not heard about their complaints, does not mean they are not complaining, because they’re complaining online and to their friends and family and passing bad reviews about your organisation without your knowledge. It is preferable for you to hear their complaints as that enables you to do something about it enabling an organisation to convert complainant into an advocate for their business.
An organisation should strive to encourage their customers to complain and then act to resolve their qualms as quickly, easily and painlessly as possible, thus ensuring customers go home talking about how quickly you solved their issue instead of speaking of the issue itself. This process will enable your organisation to develop the credentials and positive reputation for customer service. A good way of achieving this is by having customer complaints (feedback form).
It is worth pointing out again that customers are speaking about your organisation not only directly to your company but also on social media; therefore it is important to monitor activity but is a difficult task. Organisations employ either external agencies to monitor social activity and larger companies may employ in-house dedicated social media teams. Regardless of the way an organisation chooses to audit social media, customers are speaking about your organisation constantly and even if organisations can transparently view their customer’s thoughts, how do they react and act on them quick enough?
The vast amounts of unstructured and free text data constantly being produced has to be managed processed and analysed, thus allowing an organisation to react in the most appropriate way. A structure has to be put in place that gives customers a personal feel i.e. the organisation is speaking directly to me and not its customer base in general; as well as using the data to make wholesale, local or nationwide changes i.e. the identification of re-occurring and common issues and acting upon them.
An appropriate way to achieve this is to use an engine named text and sentiment analytic. A text and analytics engine is the application of sentiment and emotion to free text responses, providing organisations with an indication as to how strongly customers felt about their experience. Naturally, customers will be talking about a variety of different topics and the engine is able to gather all the data, be it on social media, feedback to the business directly and anywhere else, theme the data, apply a sentiment scale to the themes identified and report on those themes using a dashboard.
The engine uses an 11 point sentiment scale and carefully analyses the words in the comments in order to determine the sentiment and the strength of that sentiment. For example, the comments “the food was bad” and “the food was disgusting” are exactly the same sentiment, however, the word “disgusting” is stronger in representing that sentiment hence it would be rated higher in the sentiment scale than the term “bad” and it is to this detail the engine can ascertain how strong a customer feels (either positively or negatively) towards their experience with your business.
Referring back to the dashboard, which is the final output once processing and theming is complete, it will consist of the following:
– Bar chart measuring the different themes identified against the amount of time each theme was mentioned allowing an organisation to understand the most heavily talked about topics.
– Word relationship cloud. Rather than forming the word cloud from a count of words, the cloud displays different themes as well as relationships between words for added accuracy. The colour of the word relationships depicts sentiment, while the size of the word represents the frequency of its mention.
– Double-axis chart, similar to the bar chart, however compares each theme against the total volume of sentiment received for that theme i.e. a combined value of sentiment per theme.
– Heat map showing different themes in different shaped and sized blocks, as with the word cloud, colour depicts sentiment and size depicts volume of theme.
The dashboard is organic and can be added to and combined with different data sets as required and preferred. For example, an organisation may want to correlate customer feedback with staff feedback to determine any correlations i.e. an increase or decrease in staff satisfaction may be proportionate to customer satisfaction.
The numerous benefits for applying a text and sentiment engine include:
– Better justification behind decisions and changes implemented due to the ability to look at data on a granular or generic level.
-Better justification behind decisions made and changes implemented.
-Identification of small issues, when corrected, has a major impact on a customer experience.
-No manual processing/data entry involved resulting in savings in time and money as well as fully accurate data.
– Dashboard is user friendly.
– Greater transparency and insight due to the capabilities of the dashboard.
Contact us to learn more or alternatively book you free onsite assessment where DCC are able to prepare a dashboard using your own data to demonstrate the powers of automation and the text and sentiment analytics engine.