The 80/20 Rule in Customer Support – And the Need to Break It

Dec 3, 2020 | Autonomous Insights, Customer Experience, Customer Support

By Prosenjit Sen

Co-Founder and CEO,

We’ve all been there. Drumming our fingers for hours or even days while a customer-support organization struggles to resolve what we consider to be a straight-forward issue. First we get a non-answer. Then an incomplete answer. Sometimes even a wrong answer.

You’d think they get this question all the time, we mutter to ourselves. If they can’t resolve this, what else can’t they do? 

What is invisible to us is that the customer support representative is frequently thinking the same thing. The typical corporation’s inability to search its own internal knowledge base means that the answer to the customer’s question might as well be a needle in a haystack.  And that’s regardless of the channel for the query. If it’s a complex issue requiring a support ticket, the combination of an arduous search and a back-up of other inquiries means that a resolution sometimes takes two or three days. On a chatbox, customer and support often engage in a frustrating and seemingly endless exchange of non-sequitors. When it’s voice, difficulties in articulation and comprehension often sends a support engineer scouring the fine print of irrelevant internal documents for hours.

According to Esteban Kolsky, the right answer can be unearthed only 20% of the time, anyway. And that 80% fruitless search takes up 28% of a typical agent’s time. It’s the new 80/20 Rule in customer support. And it’s a rule that needs to be broken.

Those seeking solace in technology-driven resolutions are chagrined to find that the state of self-service may be even worse. A November 2020 Gartner survey of 6,000 customers showed that 87% of those seeking self-service customer support resolutions ended up needing to interact with customer support representatives – presumably those same reps who spend 28% of their time searching for resolutions that can be found only 20% of the time. 

The price of failure can be stiff, too. We at have heard more than one story of million-dollar contract cancelations in the wake of bad customer support experiences.

There are macro-trends that threaten to make this sorry state of affairs even worse. The pandemic-driven work-from-home phenomenon has driven dramatic growth to nearly every enterprise’s digital customer base. At the same time, it has dispersed the customer-support organizations that need to serve these expanding customer bases. And the acceleration of enterprise digitization in numerous other areas has made digital laggards stand out like sore thumbs.

The Gartner report was especially instructive in its identification of three points of failure in customer support: External Search, Site Navigation, and Self-Service Capabilities.  

At, we can confirm the veracity of Gartner’s assertion, which pertains equally to every channel, whether it involves a support ticket, chat or voice. We addressed these same challenges in recent deployments at multiple organizations.

At one, in particular, the platform is providing a robust engine powered by NLP, NLU, and Voice Recognition that quickly interprets and cognitively understands highly sophisticated and complex sentences, even when articulated in five disparate ways. While the results of this deployment are preliminary, the improvements and cost savings are dramatic enough that the customer is already expanding our engagement significantly.

In these cases,’s autonomous platform provides resolutions that eliminate hours of document reviews by support engineers. The platform can also be used for “auto response” — a process in which automatically responds to a case or takes corrective actions for resolutions in which it has a very high confidence. In these early days, we have seen an increase in support productivity of over 40%

Our own deployments, as well as the recent Gartner report, make clear that there is increasing demand to break the 80/20 Rule of customer support. There is an emerging customer support requirement for an autonomous solution that interprets complex customer cases and automatically provides resolutions via multiple channels with high accuracy and speed. And enterprises are simply going to have to deploy it. Otherwise, those customers will be drumming their fingers on their keyboards in search for another provider with better customer support. 

This is one of a series of periodic observations of the customer-support sector by Prosenjit Sen, Co-Founder and Chief Executive Officer of

About is the technology vanguard provider of Autonomous Customer Support.’s multi-channel platform combines Deep Learning, NLP, and Computer Vision to interpret complex customer cases and automatically provide resolutions at scale with unsurpassed accuracy and speed. The result is unrivaled efficiency and scalability in customer support, with lower escalations, higher CSAT, and significant cost savings.   More information may be found at