Human beings are flawed – we’re prone to subjective evaluations and in the world of customer service this is a problem. It’s really a problem when traditional monitoring methods within our contact centres are reliant on these judgements, costing firm’s time and money. Luckily, speech analytics has evolved to unearth the revenue previously lost in uncharted conversations – but are you using the right vendor?
Whether you’re a debt collector or an internet service provider, monitoring and analysing calls is vital when it comes to assessing trends and reacting effectively. Traditional methods are often labour intensive, requiring coaches and managers, while only monitoring around 2 per cent of the calls. Meanwhile, agents assessing contact centre conversations risk stereotyping generic content. On the flip-side, vaguely defined, multidimensional customer evaluation forms are not definitive – causing more difficulties than improvements.
To really carve out those revenue generating nuggets, we need to go beyond personal decisions on whether an agent remained ‘focused’, or ‘attentive to the customer’. Automating the quality management process using speech analytics is one way forward-facing businesses are able to truly tighten up their customer experience – with minimal labour and cost savings.
Making the switch
By switching to speech analytics, businesses can:
- Analyse all conversations across all channels of content in exactly the same way using a single application.
- Reliably identify predefined topics of categorisation of contact reasons and automated Quality Management.
- Automatically discover emerging trends and unexpected events that aren’t pre-defined by users.
Gone are the days when agents are frantically trying to identifying trends, and text and speech customer behaviour is analysed separately. Once conversations are categorised by topic they can now be directly correlated to KPIs using speech and text analytics, exposing the root of performance issues. The business value driven from the ability to search for words and phrases within customer interactions, and predict future trends then, is obvious.
Great – but how does it work?
Well, there are three types of technology available but all are not equal:
- Phonetics – Phonemes are the smallest unit of speech and individually, are meaningless. Therefore, using a phonetic engine is fairly useless.
- Speech to text – Transcribing text to speech is more accurate and hardware intensive. As the output is text, analytics can then be used to identify trends.
- Speech to phrase – Whole chunks of speech are converted without first being transcribed to text. This is the most efficient technology.
Despite the obvious difference in technologies, and clear disadvantages, the most common use cases within interaction analytics are Phonetics and Speech to Text. Speech to Phrase capabilities are crucial and the only vendor offering Speech to Phrase capabilities is Genesys.
Case study: iiNet
Internet provider iiNet took on Genesys’ services to conquer high average handle times and understand the intricate nuances and purposes of conversations taking place. The solution included 100 per cent monitoring of all calls and targeted agent training as a result of identified issues. This resulted in the reduction of average handle times of 7 per cent across all support call centres, saving £2,271,325. “Every extra second we spend on the phone costs us money, so Speech Analytics starts exponentially saving us money,” said Matthew Toohey, Chief Information Officer, iiNet.
Whether you have the right vendor to dig the gold from your contact centre conversations is important. Businesses need 100 per cent of their conversations transcribed for analysis – but the majority of analytics products only transcribe around 25 per cent. Those businesses serious about improving their customer experience like iiNet need to seriously question the quality of the technology and frequency of conversation monitoring by speech and text analytics vendors – who knows what insights they could be missing?