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Beyond dispositions - Why Customer Analytics Can’t Depend on Disposition Codes
Call dispositions are an acknowledgement that calls contain valuable information that businesses need to know to manage their sales & customer service departments. In an attempt to capture the value, call disposition codes enable companies to categorize calls based on the purpose and/or the outcome of the call. Organizations do need to know basic metrics about their call activities, for instance, the amount of inbound calls are customer complaints. But while call disposition codes are a step up from having no insight at all on calls, they create more questions than they answer.
The Questions Left Unanswered by Call Disposition Codes.
Call codes offer basic insight that leave analysts scratching their heads. Take these common disposition codes and the unanswered questions that accompany each:
- “Call resulted in sale”
- What message did the rep use to persuade the buyer to purchase?
- What reasons did the customer give for purchasing?
- “Issue was resolved”
- What was the customer’s issue?
- How did the rep go about solving it?
- “Customer complaint”
- What was the reasoning behind their feedback?
- What does the customer intend to do next?
Even the analytics run on disposition codes leave questions that deserve an answer. For instance, call codes could indicate that “address-change calls take the more time than password-reset calls.” The logical question to ask is why - is there customer confusion around the address change process? Does it take too long for the rep to access the appropriate field to change the customer information?
Call dispositions offer information on what happened, when what organizations need is insight on why it happened.
Why Dispositions Don’t Produce Answers
A simple code collected at the end of a call will be just that; simple. Dispositions by their very nature only offer a limited number of variables that can be captured and analyzed. Adding more codes has quickly diminishing returns as it takes more time for the agent to complete and accuracy diminishes.
Plus, there is no guarantee the organization is tracking the right outcomes. The organization certainly won’t have a code for a problem that they don’t even know exists. For instance, imagine a company with a software product thinks it needs to be tracking the number of questions it receives about certain features within the software program. The software company decides that it needs to invest in enhancements for a certain feature because it has been getting the largest volume of calls on that feature, as indicated by disposition codes. In reality, however, customers are only calling with questions about how to access the feature, because they are confused by the title of the menu option used to navigate to it. Rather than making a simple change to a menu title, the software company decides to overhaul the feature, and delivers an enhancement its customers didn’t need. These are the types of problems dispositions identify without the answers behind them, and why it is dangerous to depend on them.
How Call Dispositions Bias Customer Feedback.
Because dispositions are manually classified by agents, there is opportunity for human error and bias. Instead of capturing the most important part of the call to the business, representatives are most likely to capture what was most important to them. Imagine, for instance, that a customer calls to complain about a product. The customer is audibly frustrated and offers specific feedback about what is wrong with the product and how she would like to see it fixed. The representative, meanwhile, is focused on calming the customer down and issuing a refund. At the conclusion of the call, the agent isn’t likely to categorize the call as “product enhancement suggestions,” if the organization even has the code as an option. Instead, the reps will likely categorize the call based on what happened to them. They’ll likely use a code like “customer complaint - resolved.” Not only would this completely miss crucial customer feedback, it could also mislead the company into thinking it is resolving customer complaints.
The rep may have solved the problem in the moment - and call dispositions codes can even tell you how many problems were solved. But the real goal of contact center analytics is to learn, from experience, about how to avoid problems from happening in the first place.
Call disposition codes are easy to collect. They are better than nothing. But competitive businesses can’t depend on easy-to-capture data points that don’t provide the answers the company needs.
How Speech Analytics Captures the Answers Companies Need from Calls
Call disposition codes are great for understanding that there is a problem, but speech analytics can reveal the reasons behind the problem and what to do about it.
Speech analytics platforms like LucidVueCX can automatically listen to the entirety of the call. These tools can automatically and objectively categorize the call activity, the outcome of the call, and the quality of the call. From there, marketing analysts can scientifically extract rich insights on what matters to the business; for example:
Driving more revenue by message testing based on keywords used in successful sales calls
Making product enhancements using direct feedback from customers’ own words
Improving the customer experience by finding what went wrong in calls with poor service delivery
Redesigning processes using the reason behind why calls are taking agents too long to complete
Reducing customer attrition (hyperlink to previous article) by gathering previously hidden data on trends amongst customers that defect.
Improving customer service representative performance using data on quality of call delivery.
Advanced speech analytics offer meaningful intelligence not only on performance indicators, it also enables organizations to determine what its key performance indicators actually are. Analytics of speech within calls can identify what words customers use in each type of call and how each correlates to outcomes such as repurchasing, complaints, and issue resolution. With this insight, companies can pinpoint the specific interactions that matter most to their business.
It’s important to recognize calls as a valuable source of business intelligence. Take that revelation to its logical conclusion and extract all the answers contained within calls using speech analytics.