All of you know that it takes a team of QA professionals to get this done.
You take a random selection of calls and screen them to see how our agents have been performing.
This is error prone but that has been the only solution for us.
Most of you became QA leads because of the excellent customer service you provided in your careers as agents.
You didn’t quite become QA leads because you were great at listening to call recordings and spotting issues.
In other words, you went from being great at your jobs to doing REALLY Boring jobs.
But with Amazon Contact Lens, most of your work is taken care of (the tedious parts anyway).
Now, you can spend your time on the stuff you like – COACHING!
With Amazon Connect Contact Lens, you set up automated quality control of calls like this:
- Enable Amazon Contact Lens in your Contact Flows.
- Create Rules for words or phrases you want to monitor. E.g. you might have specific rules that an agent has to follow that you need enforced.
- Automatically categorize contacts based on uttered keywords and phrases against the Rules you created.
- Pull reports on a regular basis to audit the calls as usual – only difference being that you no longer have to do random sampling and will only listen to audio recordings of calls that have been tagged by Contact Lens as “issues”.
- Speak to your agents about the issues you and Amazon Contact Lens have identified, coach them, guide them, move on.
On this page
How to alert call center managers about angry patients
Many times you have angry callers/customers/patients.
Sometimes you have abusive callers.
Either way, a supervisor or call center floor manager needs to step in.
Sometimes when you are making a collection call, the customer asks for a discount. That’s another time the supervisor with higher discounting authorization needs to step in as well.
In any case, you can set up Amazon Contact Lens to alert supervisors about these situations.
Call center managers don’t have to be glued to their laptops or computers to get these alerts either.
To do this, you follow these steps:
- Enable contact Lens in Amazon Connect Contact Center.
- In your contact flow, enable Real Time Analytics. (not always the best transcription option). Real time analytics option will always come with post call analytics as well, so there’s no need to worry about losing the post call transcription option.
- Next, create rules that you want to monitor for. Make sure you understand how rules work and whether you need exact matches, AND OR , whether the agent should utter certain words or whether the customer / patient should utter certain words.
- There are a few examples here “Alert supervisors in real-time based on keywords and phrases – Amazon Connect”
- Once you do this, your call center manager (or designated person) can start getting alerts and can actually listen in on conversations to take further action (or whatever is the protocol for your hospital’s call center).
How to perform call sentiment analysis
As a call center manager you will be doing call sentiment analysis over periods of time to analyze the performance of your agents, the experience of your callers and to get ideas on how to improve.
Amazon Contact Lens can help you tremendously with this.
To do this, you would need to use this API of Amazon Contact Lens. Example Contact Lens output files – Amazon Connect.
Effectively, here’s what to do.
- First, understand the schema that Amazon Contact Lens produces. Understand how and where the redacted information segments start and end. Understand how and where the loudness, sentiment scores, sentiment analysis, interruptions etc are marked.
- Have a simple web application pull data from your Contact Lens file storage S3 bucket.
- You can search by “ParticipantRole” :”AGENT” or “ParticipantRole” :”CUSTOMER” or search by “LoudnessScore” or “Sentiment” or “MatchedCategories” that might be of interest to you e.g. “Swearing”, or “Interruptions” or “NonTalkTime” etc
- Slice and Dice the data that you find to perform sentiment analysis of past calls at your hospital’s contact center.