Collecting customer feedback through surveys is a common way to determine what your customers are thinking. But reading through and categorizing every open-ended response can be tedious, time consuming and prone to error.
The challenge is that in these feedback surveys, your customers typically speak/write in an unstructured, fragmented and nongrammatical manner. So how can this feedback be classified in an accurate, classified, repeatable, and cost-effective way? One that leads to improvements in customer experience (CX)?
We use machine learning to mimic how the human brain processes language by recognizing the patterns of language, then we tag each verbatim with each of these distinct patterns so you can easily see what your customers are trying to say.
What distinguishes our approach from that of others is we use a curated, consultative process to arrive at text classifiers called Topic Agents that are tailored to your customers.
We review open-ended responses and consult with you as to whether you have certain concepts or themes you wish to track.
We build and train a set of Topic Agents to act as text classifiers that will capture these and other themes using a sample of the verbatims.
After reviewing with you the initial results from applying the Topic Agents to a subset of open-ended responses, we will refine and apply them to the entire set of responses.
We can work with you to automate a process a verbatim is immediately routed to the appropriate person or team to respond to and reconcile the issue immediately.
It's about time you know exactly what people are saying about you and take action. Our survey analytics in combination with interview and research analytics solutions will convert years of survey and marketing data into a knowledge repository yielding valuable insights.
Ready to transform your customer feedback into actionable insights?