Part 1: Speech Analytics
The customer services industry is set to witness multichannel communication increase exponentially in the coming years. Analyzing the characteristics and trends of this customer journey will be critical to create a competitive advantage from the customer experience point of view. Meeting customer expectations in the new decade means shifting from being ‘customer focused’ to ‘customer committed.’ Customer journey analytics can transform organizations by taking their customer experience prowess to the next level.
By 2020, customer experience will overtake price and product as the key brand differentiator. (Walker Info)
With multi-channel communication going up with the expected increase in video chat, WhatsApp chatbots etc., the contact centers are here to stay for a few more years. While I plan to do a deep dive on the integrated customer journey analytics, let’s look at contact center analytics in this paper.
With AI starting to become an integral part of every organization, the ability of analytics in the contact center to analyze voice patterns, assess emotional states and find solutions to even the most complex queries will increase significantly.
So, no more will there be any ‘Traditional Contact Centers;’ rather, they will be upgraded to become ‘Analytical Contact Centers.’ In addition to this, with the importance of customer experience taking the center stage:
- ‘Answering customer calls’ will turn to ‘engage with the customer’
- ‘Call center agents’ will need to be ‘customer experience professionals’
But how can this happen?
A fundamental break from the past
Today, when we call/reach any customer service center, the first message we hear is “your call is being recorded for training and quality purposes.” But the question is: how many organizations have unleashed the potential of the millions and trillions of conversation data that is getting stored? Traditionally, our quality teams have been doing QC on 2% -10% based on the size of the data; that too against a set of pre-set pointers/questions.
Rather than just looking at the structured data (such as SL, AHT, start time, end time, NPS, number of calls per agent, etc.), speech analytics can extend beyond the four walls of the call center and turn unstructured audio data into actionable intelligence. This will help ‘Traditional Contact Centers’ become ‘Analytics Contact Centers’.
Speech analytics – Know your customer
The three key areas that HCL have been concentrating on through implementation of speech analytics are customer satisfaction enhancement, call volume reduction, and productivity improvement. At the end of the day, it’s all about taking customer experience to the next level.
In the next decade, customer experience will be the key brand differentiator, scoring beyond price and product. As Garyefox explained:
- 74% of consumers have spent more due to good customer service – American Express
- Maximizing satisfaction has the potential not only to increase customer satisfaction by 20% but also to lift revenue by up to 15% while lowering cost of serving by as much as 20% – McKinsey
- Customer experience leaders have more than a 16% advantage over competitors in willingness to buy, reluctance to switch brands, and likelihood to recommend – Temkin Group
- A 2% increase in customer retention has the same effect as decreasing costs by 10% - Leading on the Edge of Chaos, Emmet Murphy and Mark Murphy
- One happy customer can equal as many as nine referrals for your business – American Express
How does speech analytics work?
Agnostic of the customer environment and of the recording system, the speech analytics software can be a layer on the existing recording system. The speech analytics tool can keep fetching the new recording at regular intervals. It would give us the flexibility to search any word or combination of words or phrases into a rule, representing a specific scenario or use case that we are trying to quality and analyze the root case. This methodology is called semantic analysis.
Two important files are processed in combination: the recorded audio conversation and the meta data associated with every call. These aid in analyzing the problem from all perspectives including:
- Identifying themes from all the calls received
- Categorizing into call drivers
- Relating to emotion and sentiments
- Understanding the underlying root cause of the call
- Understanding root cause of customer dissatisfaction
- 100% compliance check
- Identifying agent and customer behavior (with speaker separation)
- Identifying agent issues and training gaps
- Product feedback/product issues
- Process and policy which is impacting performance
Here is the impact model that is being practiced at our Speech Analytics COE:
It just doesn’t stop here. Speech analytics with real-time output can be linked to the knowledge management can be breakthrough knowledge automation. Application/Environment that can comprehend the user role, user context, and the job in hand at that moment in time.