Many businesses are straining to listen and understand what consumers are saying to them. Purporting to fulfil that need is a plethora of Voice of the Customer (VoC) products. VoC is, of course, a relatively modern phrase that is used to describe what traditional business owners would have simply called ‘listening to your customers.’ The increasing prevalence of VoC technology just goes to show how much importance businesses place on knowing their customers’ opinions. However, it also seemingly indicates that we haven’t yet found the perfect formula for accurately measuring, analysing, and understanding consumers.
Modern day businesses have access to an overflowing heap of customer data that can be used to work out what their customers think of them and their products, their needs and desires, and what they prioritise in their everyday lives. Information from contact centres, in-store and online shopping interactions, social media engagement, blogs, reviews and the increasingly dominant vlogs can all give useful insights on what customers are thinking and feeling.
Traditional VoC programmes mostly rely on determining the sentiment behind contact centre interactions. Text from call transcripts or online chat functions can be categorised into angry, sad, happy or other states using formal naming conventions, machine learning, and teaching a computer how certain words and concepts are related to each other.
Teaching a computer to analyse the way we communicate is no easy task. It is made much more complex by different languages that have widely diverse grammar, punctuation, sentence structures, and other syntax. Another layer of complexity is then added by misspellings, slang, text speak and, that mainstay of the English language, sarcasm. Then add in our modern day habit of emphasising speech using emojis, or indeed, communicating exclusively using these little icons and you can see why computers may be left scratching their motherboards when trying to work out what it is we’re saying. As a result, sentiment analysis is not a perfect, tailored solution for translating your customers’ voices.
A better way of understanding what your customers are saying is to combine sentiment analysis with a technique called text mining, and another known as topic modelling. Text mining determines patterns in what your customers are writing about, or to, you. Topic modelling complements this, by determining the main subject areas that your customers are talking about and then grouping them accordingly.
Put simply, whereas with sentiment analysis you have to teach a computer the connections between different words; combining this with topic modelling and text mining, along with machine learning, allows the computer to work it out for itself. Another important benefit to this approach is that the computer can analyse much more data than a human ever could.
A good example of using this trio of techniques in action is in working out the sentiment behind a body of text that contains the words ‘kills’ ‘bacteria’ ‘rarely’ and ‘fails’. At first glance, you may think that the overall sentiment is negative, and this is what traditional VoC is likely to have picked up. However, by looking at the complete phrase “…rarely fails to kill bacteria” you can see that the text was actually positive. VoC powered by sentiment analysis, topic modelling and text mining will have discovered this.
In the current volatile marketplace, being able to understand what your customers think of you and what they want from you, both now and in the future, can be the difference between your company being a John Lewis or a BHS. VoC programmes have a significant part to play in this, especially if they can provide you with insights in a matter of days.
Information from contact centres can be evaluated to determine how well a particular product or service is performing in the eyes of your customers. If people have been contacting you to complain about a new or re-vamped product, you have a chance to offer alternative products, change the product design, or find another solution to their complaints. Similarly, getting positive responses to a product can tell you to ramp-up production, marketing spend and what qualities you should perhaps consider in your next product design.
Receiving feedback at all stages of the customer journey can also help you in identifying pain points for your consumers and ways to fix them.
Finally, analysing contact centre communications with your customers will provide your customer service staff with on-going feedback on their performance and customer satisfaction – which is useful for training and on-going professional development purposes.
Reaping the benefits of VoC technology does require some prior preparation. Before a VoC programme is put in place, you need to set clear objectives for the project that align with your business aims. You will need to determine what data you have, or what you would like to collect, to be included in the programme. Data sources such as chat transcripts, survey data, transactional data, product data, event calendars and planned product launches can all be analysed through VoC technology.
Ultimately, any way to bring your business greater insight and understanding of your customers is bound to be advantageous. Having that fly-on-the-wall view of what consumers think about you, what they love and hate, and what they need, will have widespread benefits across your organisation. In an increasingly competitive marketplace, businesses that take the steps to really listen and understand consumers will find they hold the engagement and loyalty of their customers far better than their competitors. In catching the ear of consumers, it is most effective to use your own ears first – and VoC programmes are the aid you need to hear clearly what your customers are saying.