#1 most frequent
United States of America
71.6%68 installations of 95
What is Verint Speech and Text Analytics?
Verint Speech Analytics is a tool used to transcribe and analyze millions of calls to discover customer insights and improve contact center performance in the cloud.
Categories & Use Cases
Who Buys & Uses Verint Speech and Text Analytics
#1 most frequent
Finance and Insurance
43.2%41 installations of 95
“I primarily use Verint Speech and Text Analytics to identify patterns in contact trends to see if there are shifts driven by changes in our processes or initiatives that have been implemented. Verint Speech and Text Analytics assists in pinpointing the volumes and the sentiment around the efforts.”
#2 most frequent
Information
9.5%9 installations of 95
#3 most frequent
Utilities
8.4%8 installations of 95
#2 most frequent
United Kingdom of Great Britain and Northern Ireland
6.3%6 installations of 95
#3 most frequent
Canada
5.3%5 installations of 95
Pros
- Precise categorization and identification of key phrases in speech data
- Effective search and review of customer interactions
- Ability to generate actionable insights and identify trends
Cons
- Transcription accuracy issues, especially with specialized terminology
- Limitations in reporting and analytics customization
- System performance issues, including latency and slow cloud environments
Finding best and bad practices with Verint Speech and Text Analytics
Use Cases and Deployment Scope
In our organizatio we use speech analytics to find resultas for collections, how to improve the way we close agreements, the way how the agents manage the calls, if make compliance questions, if close a deal and the way they managed special customers, also Review the feelings and emotions during specific parts of the calle, also to get statictics like silencie, holds, trasnfers or prohibited actions during the contact with the customer.
Pros
- Find root causes
- Find emotions
- Increase nps
- Obtain Quality scopes of the call
- Obtain Bad words during the call
Cons
- Better reports
- Speed of the transcription
- How to export the transcriptions
Return on Investment
- Emotions
- Fast results
- Best practices
- Easy to use
Usability
Alternatives Considered
Eleveo
Other Software Used
WFM, Adobe Product Analytics
True User
Use Cases and Deployment Scope
We use Verint Speech and Text Analytics to identify areas of concern and volume increases that help us spot trouble areas within our ecosystem that directly impact our guests and create higher call volume.
Pros
- categories
- speech "key word" identifiers
- Customer and agent interaction
Cons
- Easier set up for new topics you want to identify
Return on Investment
- Once we could prove the amount of calls coming in to our mobile app team and developers, we were able to get the issue resolved and vastly improve our guest experience.
Usability
Verint Speech and Text Analytics are Head of the Class
Use Cases and Deployment Scope
We utilize speech to determine call drivers and customer experience across all calls versus just a small subset or random samples. This helps us know where to spend time training and what areas to look at for improvement. In the end, resolving these items quickly and efficiently saves us money and reduces workflow.
Pros
- Speech Categorization
- Combining speech with call meta data
- Dictating customer emotion
Cons
- Some times categories go offline without explanation and they have to be re triggered
- Root cause be be easier to manage
- Setting up flags on specific categories could also be easier
Return on Investment
- Saves us money
- Saved us customers
- Saved us time
Usability
Verint Speech and Text Analytics Rocks
Use Cases and Deployment Scope
I am a program manager for our quality and speech analytics program at First American Home Warranty. While we have been using Verint for quality for many years, we recently activated Verint Speech and Text Analytics. I'm in the process of scoping out our speech program that we will begin to develop in the next 4-6 weeks.
Pros
- I love the use of the NEAR operator.
- I'm a big fan of using transcripts for Speech Analytics vs a phonetics based program.
Cons
- In my prior role, I used NICE (Nexidia), and while no platform is perfect, I really enjoyed having the ability to auto-bypass the non-talk time to work more efficiently. More embedded efficiency tools would be amazing.
- I find the operator options with Verint Speech and Text Analytics to be a bit limited. I'd love the ability to leverage more complicated operators, like a subset, so I can target specific conversations without exceeding the 30 phrase limitation.
- The ability to really customize views would be welcomed. Often I have to piece together the data that I need which can be time consuming.
Usability
Alternatives Considered
NiCE CXone, Gong and CallMiner Eureka
Verint Speech.
Use Cases and Deployment Scope
Today we use speech and text analytics to monitor for key themes and trends that help us make actionable and easy decisions on real-time events and disruptions.
Pros
- Identifying key phrases that are critical to the patient experience, like compliance statements.
- Supporting Genie in helping provide insights that are quick and easy to locate.
- Buckets similar calls for easy review/access.
Cons
- Transcription of difficult words, like medication names and certain conditions.
- Assisting with validation of the intended words and phrases identified.
Return on Investment
- It has provided us valuable insights that help us make business decisions quickly.
