Unseen customer loss: the reality
‘Quiet quitting’, ‘click bait’ and the delightful ‘touch grass’ are all phrases we’ve come to incorporate into our collective lexicon but are you familiar with the concept of ‘slow failing’? It’s a term now being used to describe the seemingly inexplicable loss of custom caused by businesses who are, in fact, failing to harness their customer service data and spot signs of dissatisfaction.
Whether a customer chooses to communicate with a brand online, via a messaging app or over the phone, that interaction will be captured in separate silos, making it difficult to gain a unified view. Digital and assisted interactions are treated as separate streams, so a customer’s chatbot session might be logged in one system, and a subsequent call logged in the telephony system, with no link between the two.
This lack of integration means the full context of the customer’s journey is lost when they transition channels. Management cannot tell, for instance, whether the customer who emailed yesterday is the same person calling today. This inevitably leads to customers becoming exasperated by the lack of transparency within the business and the inability of agents to gauge their frustration levels and respond accordingly.
All data is good data
In addition, contact centres often have interactions and agent activities that go unreported or under-analysed because legacy reporting tools consider them “noise” or simply don’t capture them. These might include short-abandoned calls (customers who hang up quickly), repeat dials to the IVR that never reach an agent, blind transfers that lead nowhere, prolonged hold times that end in hang-ups, or time spent by agents on after-call work or in idle states.
These unproductive contacts and activities can consume significant resources and degrade customer experience, yet they remain hidden in fragmented logs or are excluded from standard reports. As a result, management might not realise, for instance, that 10% of callers give up in the Interactive Voice Response (IVR), or that a certain percentage of an agent’s day is spent in states that aren’t tracked as part of handle time.
Over time, these hidden inefficiencies can add up. In fact, studies have found that a substantial portion of contact centre time – potentially up to 40% – is unproductive but is unlikely to be tracked by traditional analytics. Without visibility into these missed contacts and wasted efforts, contact centre leaders struggle to identify where processes are breaking down or where customers are encountering friction.
Instead, success is being measured in the contact centre using metrics such as average speed of answer (ASA) which focuses on quantity over quality. The board, meanwhile, uses the Net Promoter Score (NPS), which tracks how likely a customer is to recommend a business, or the Customer Satisfaction (CSAT) score. Both reflect the experience of a select few customers who choose to respond to a survey at a given point in time rather than actual behaviour.
Reliant upon fragmented data, siloed reporting tools, and contact-centric metrics, it’s not difficult to see why many companies are struggling to obtain a complete picture of their performance. It’s this lack of visibility that is making it so difficult for both executives and operations teams to make informed decisions and why they are at risk ‘slow failing’.
Extra plumbing
So, what can be done to create a single standardised view of the customer journey? To start with, rather than logging only ‘successful’ contacts (like connected calls), the business needs to capture each and every attempt or event in the customer journey. An abandoned call, for example, should be logged together with details on how long the caller waited and what menu they reached in the IVR. Likewise, if a customer makes three attempts to make contact but only gets through on the third attempt, these should be logged as opposed to being ignored.
Agent activity also needs to be recorded in a similar way to identify where improvements can be made. For instance, the data might show a large volume of short abandons in a certain queue. Upon further investigation it might transpire that an IVR prompt is causing customers confusion resulting in them hanging up or the calls might have come in at a time when the call centre was understaffed. These insights can then be used to address the pinch point and streamline the customer journey.
Accessing this kind of data requires the business to add another layer on top of the CX technology stack. This acts like a real-time data pipeline, connecting every touchpoint across voice, chat, email, IVR, and third-party systems to create a single, standardised view. And adding this additional plumbing enables not just accurate performance monitoring and sentiment analysis but an operational metric: the Customer Effort Score (CES).
Measuring dissatisfaction
CES provides real-time visibility into friction across the journey by capturing those signals previously ignored such as long holds, transfers, failed deflections, repeat contacts, and digital drop-offs which are all indicators of unresolved customer frustration. When surfaced to agents, supervisors, and executives via live dashboards, it enables teams to anticipate when a disgruntled customer might be about to turn turtle. For instance, a customer who has had a bad experience could be escalated to an agent with the right skillset and level of authority to resolve their issues and prevent them from churning.
It's only by pooling the data from different channels, adding context to interactions, and analysing the results that organisations can begin to fully understand the customer experience in this way. For example, at the executive level a dashboard might include the percentage of journeys resolved in one contact versus multiple contacts, the top reasons customers contact support (pulled from IVR or agent tagging data), and real-time CSAT from post-call surveys, alongside traditional metrics like call volume and agent utilisation. This creates a warts and all picture, giving a far more comprehensive understanding of where the business is winning and where it is falling short.
We all know that in order to succeed you must learn from your mistakes, the trouble today is that many businesses remain blind to their failings and so are doomed to repeat them. Combining the data from different contact channels and including unresolved or incomplete customer contacts could allow these businesses to begin to make truly effective changes, and in so doing move from slowly failing to rapidly reactive operations.