Does your data collection system prevent conditional branching?


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“Does your data collection system prevent conditional branching?” is one of the questions in the eBook and self-assessment 25 Mistakes to Avoid with Post-call IVR Surveys, the compilation of the mistakes I have seen in the twenty years since inventing the post-call IVR survey methodology for contact centers. Take the self-assessment to determine where your program has weaknesses. The data collection system conditional branching as one of the self-assessment items is what I talk about in this article.

Why is this a problem?

The question that seems to hit the heart of this topic is to think about the collective group of your contact center’s calls and ask “does one size fit all?” If the majority of your calls are ostensibly the same, you do have a one size fits all scenario. I have not seen many customer service centers where that is true, despite what people think internally. This fact typically comes out when I lead the measurement design portion of our managed service programs. As soon as you think about the different kind of calls, the attributes that need to be measured begin to deviate from the one-size-fits-all list. I generally have to invest a lot of effort trying to reign in a client’s purported differences to identify a core set of service criteria across call types. Eventually we do come to a solution that will allow me to collect the data needed to drive their desired outcomes.

You have heard me say it many times, “surveying is not a technology” but it is significantly affected by technology. The software or solution that collects data for your post-call IVR survey program may limit the customer experience analytics that can be conducted, thereby impacting the value of your voice of the customer measurement program. Does your data collection tool require that the same questions be asked of every caller? If you are nodding your head to this question, I am so sorry for you. Don’t forget that one-size does NOT fit all, so this would be a severe limitation. Let’s think about why it’s a limitation.

What do you when you have a self-service problem on a website? You call the contact center, right? So do your customers. So then, self-service performance on your website is important to the customer experience with your company. Would you like to include survey question to quantify the impact. “Did you use our website before calling us today?” Everyone is asked this question, but without the capability of conditional branching, any follow up questions about that experience is asked of everyone. You’d want the non-users to skip to the next general question and not have to select “not applicable” to two or three diagnostic questions about how the website served their needs (or not). That would be a pain for everyone.

Similarly, if you want to build models and conduct analytics on segments of the data the ability to identify the customer’s definition of the reason for their call is important. You cannot have a list of 30 reasons and have them pick one from the list. But you can break it down easily for the caller and quickly capture the customers’ reasons. “Was the primary reason for your call today A, B, C or D?” For those who say that it was A, “was it W, X, Y, or Z?” and so on for the B, C, and D categories.

The Solution

This is a tool selection issue. If you want deeper and actionable insights, do not accept a data collection system that does not permit conditional branching patterns. If you have been led to believe that it is too difficult or too expensive to use a technical solution that will garner the right kind of data, think again. Measuring the customer experience cannot be frustrating to your customers and needs to be robust enough to insure that the right analysis yields predictive models, not merely reports. In the long run, it’s actually more harmful to your agents, customers, company and to your position within the company to have a limiting voice of the customer program. Remember, no voice of the customer program is better than a bad voice of the customer program.

Republished with author's permission from original post.

Jodie Monger
Jodie Monger, Ph.D. is the president of Customer Relationship Metrics (CRM) and a pioneer in business intelligence for the contact center industry. Dr. Jodie's work at CRM focuses on converting unstructured data into structured data for business action. Her research areas include customer experience, speech and operational analytics. Before founding CRM, she was the founding associate director of Purdue University's Center for Customer-Driven Quality.


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