- The surveys are completely biased. I know Dynata is a third party to collect data from sponsors, but when researching these sponsors, you can see that they are affiliated with a political party. I do not think they know what actual academic research really means and how to better streamline analytics and not partisan politics - this is coming from someone who studies Data Science and Python.
- You have no control over how surveys go even though the metric system they use, they will dox you on said "control." Quality assurance team are nit-picky when it comes to the most diminutive thing. For example: you have to be quick and cannot take a two second pause during a survey between questions, they want you to have "control" over the survey, albeit, you have to read everything verbatim even if the questions are predisposed. The way that the surveys are being written, it does not engage the respondent to stay on the line to continue the survey. QA are constantly being nit-picky (despite your performance rate being relatively good), and they will pick the one survey that you did not meet all the criterias for and dox you points off of that one survey (this is coming from me, an agent, who gets interviews during a shift). And they use this metric to level this with your performance quality, which is unfair and partial. It is not like we are sitting on our butts and dwindling the time away. This type of rubric is unachievable to agents who have to learn all of the correct dispositions while being timely and efficiently to the objective; basically having to be perfect on every call you make so that your quality scores don't hinder - that, in itself, is blapshemy.
- They cut hours but want people to stay longer on busier projects? Proof that management do not care about employees but care about clients.
