Speech analytics offers substantial value to businesses through its unique ability to “listen” to every customer call and give insights into the conversations. You can find lots of examples of success on the internet. What’s harder to find are insights into why some companies fail to achieve expected results. Surprisingly, speech analytics technology is usually not the culprit. The problems are usually introduced during the implementation process.
I recently hosted a webinar on the Top Five Reasons Speech Analytics Initiatives Fall Short. My top-five list is below. The hour-long session is available for replay if you want to find out more.
Top Five Reasons Speech Analytics Fail to Meet Expectations
- Lack of executive-level support – speech analytics uncovers issues that often span across different organizations with the business and require their support to implement changes.
- Low call recording coverage – more audio to process makes for better results. You can get benefit with low recording percentages; you just need to set expectations accordingly.
- Inadequate training – speech analytics requires a dedicated knowledge set. If you can’t staff internally, then look at third-party or vendor supplied options.
- Unclear goal definition – make sure everyone knows what success looks like and that the goals are a good fit for the technology.
- Inability to operationalize results – you need a process that links analytic results to operational improvement.
Thanks for the article, you have made some valid points. I would say that one of the key aspects is to make sure that staff training is of a high standard, as this is often the main reasons that speech analytics can be below par.