Insights

Why disposition codes will never reveal the real reason customers are calling

We explore how the standard call disposition process prevents you from getting the best customer insights. 

Organizations need to understand why customers are contacting their customer service teams. Doing so enables you to optimize the customer experience, deflect unwanted demand to self-service and improve productivity. 

Traditionally, disposition codes have been the go-to method for categorizing contact drivers. But in most instances, the manual call disposition process is fundamentally flawed and will never provide the level of insight you need to proactively address customer concerns. Let’s dive into why.

The limitations of call disposition codes

1. Limited code selection

To avoid cognitive fatigue and the paradox of choice, disposition codes typically come with a relatively small, pre-defined list of call disposition categories that agents can choose from.

However, customer inquiries are diverse and often complex, meaning they don’t always fit neatly into one of the available categories. This limitation forces agents to choose random codes or select the ‘closest’ option, which may not truly represent the customer’s actual issue.

At best, this means incorrect classification. At worst, you’re making important decisions based on very inaccurate data. 

2. Agent selection bias

Contact center agents and sales teams are often working under pressure, handling high volumes of calls and trying to wrap up interactions quickly. In many cases, they resort to selecting the first available option in a drop-down menu, rather than taking the time to accurately categorize the call. 

One of our clients estimated that only 30% of disposition codes were selected correctly – meaning 70% of the data they relied on for decision-making was inaccurate.

3. Lack of granularity

Even when an agent makes a genuine attempt to select the right disposition code, these codes are often too broad to provide meaningful insights.

For example, a code like ‘Billing Issue’ doesn’t reveal the customer’s intent to the businessan organization. Was the issue due to incorrect charges? Confusion about a set up charges form, pricing or trouble over pricing, or trouble accessing a bill online? Without granular insights, you can’t take targeted action to resolve root causes.

Manual analysis: a time-consuming, inefficient alternative

Recognizing the shortcomings of disposition codes, some organizations attempt to manually analyze contact drivers to extract more meaningful insights. This involves listening to calls, reading transcripts, and categorizing issues manually – a process that:

Despite the good intentions, this approach is unsustainable and still prone to human error and bias.

AI-powered analysis: the only scalable solution

The reality is that to analyze contact drivers with accuracy, you’ll need a scalable, automated solution. This is where AI-driven platforms like evaluagentCX come in. By leveraging artificial intelligence, you can:

AI doesn’t just replace disposition codes – it revolutionizes the way you understand your customers, leading to better decision-making, reduced operational costs and ultimately, happier customers.

The future of contact center intelligence

Relying on disposition codes is an outdated approach that will never provide the depth of insight organizations need to truly understand their customers. 

The only way forward is to leverage AI-powered solutions to automate contact driver analysis and proactively address the root causes of customer issues. Organizations that embrace this technology will be the ones that stay ahead in the ever-evolving CX landscape.

Are you ready to move beyond disposition codes and unlock real insights? Find out more by exploring the evaluagent platform.

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