#1 most frequent
United States of America
71.9%189 installations of 263
What is Google Cloud Contact Center AI?
Google has launched a cloud based contact center software which uses artificial intelligence (AI) to improve the customer experience and provide real-time insights for agents.
Announced in July 2018, this product adds three core AI functionalities to the contact center software tool belt with its Dialogflow feature: virtual agents, AI assistance for human agents, and contact center analytics. Google’s product streamlines inbound and outbound communications by handing off simpler customer requests to digital agents and freeing up live agents to deal with more complex issues.
The product also uses natural language processing (NLP) capabilities to detect customer sentiment and machine learning (ML) processes to suggest intuitive solutions for live agents and facilitate digital agents learning from real-time customer interactions.
This software is integratabtle with leading Contact Center vendors such as Genesys, Cisco, Mitel, Twilio, and Five9.
Categories & Use Cases
Top Performing Features
Call analytics
Gathers key performance indicators (KPIs) such as average time in the queue, average call abandonment rate, average handle time (AHT), average speed of answer etc..
Category average: 8.3
Historical reporting
Ability to analyze long-term call patterns and trends such as peak call times and downtimes.
Category average: 8.5
Click-to-call (CTC)
Allows one-click calling for agents.
Category average: 8.7
Areas for Improvement
Customer surveys
Allows agents to gather post-interaction feedback from customers on the communication channel of their choice.
Category average: 8.1
Validate callers
Authenticates inbound callers with a customer ID.
Category average: 8.8
REST APIs
Open APIs, SDKs, and supporting documentation, that enable businesses to customize and build on the Contact Center platform.
Category average: 8.4
Who Buys & Uses Google Cloud Contact Center AI
#2 most frequent
Canada
5.3%14 installations of 263
#3 most frequent
United Kingdom of Great Britain and Northern Ireland
5.3%14 installations of 263
Google Cloud Center Review
Use Cases and Deployment Scope
Google cloud contact center AI is used for incoming calls from customers who want to make inquiries about different types of financial products, the business problems it addresses are the poor response of human employees, its scope is to use it for different areas or departments of the bank for a better connection of the bank with its clients.
Pros
- a friendly environment
- good connection
- the support
Cons
- a better price
- more configuration options
- more accessible to people with little knowledge
Return on Investment
- better connection with customers
- increase in sales due to the use of the contact center
- better feedback
Alternatives Considered
IBM Watson Assistant
Other Software Used
IBM Watson Assistant, BoxOffice, Microsoft 365
Google it.
Use Cases and Deployment Scope
Overall the integration and level of service are excellent. All things considered, it was an excellent choice to select and implement this software. The VOIP and applications work together very well and all functionality of the software is excellent. Overall conclusion and summary are very good for this product and I would recommend it for any other call center applications as well.
Pros
- Applications integration.
- Robust and quality programming.
- Ease and usefulness.
Cons
- More detailed error messages.
- Possibly more training.
- Training guides.
Return on Investment
- Simplified integration and use of software.
- Easy learning curve.
- Ease of implementation.
Alternatives Considered
Five9
Other Software Used
AgencyBloc, Oracle Agile PLM, Azure Data Science Virtual Machines (DSVM)
Usability
Google Cloud AI
Use Cases and Deployment Scope
My overall experience was good. The AI contact center worked pretty well, honestly better than I had expected. The native language processing is really good for multiple dialects and languages. The speech-to-text and text-to-speech modules are on point and the best part is Dialogflow. It allows the software/program to be used fairly easily.
Pros
- Auto speech learning
- Text to speech
- Ease of use
Cons
- Maybe more languages could be added.
- Outside party companies could be easier to use.
- More examples of different language phrases.
Return on Investment
- Lower minutes used to translate
- Easy to use
- Could be better
Alternatives Considered
Google Authenticator
Other Software Used
Google Authenticator, Google Ads, Amazon Advertising Sponsored Products
Virtual Agents are helpful!
Use Cases and Deployment Scope
Clean, easy-to-use interface. Engaging format and intuitive and interactive tools. It helps agents see overviews at a glance and understand statistics about their recent contacts. Breaks down call types and allow for quick reskilling if necessary. The ability to use virtual agents for some tasks helps cut labor needs and costs, as well as focuses that labor where it is most effective.
Pros
- Virtual agents are able to handle a wide variety of tasks.
- Virtual agents streamline the workforce by allowing more complicated cases to be handled sooner.
- Interface allows at a glance viewing of call types.
Cons
- Virtual agents can frustrate some customers.
- More ADA-friendly features would be appreciated (high contrast settings, text-to-speech capabilities).
- Diversity amongst virtual agents would be helpful.
Return on Investment
- Competitive pricing allows for a positive impact on ROI.
- Virtual agents help reduce labor costs.
- Improved labor costs help alleviate some staffing concerns.
Alternatives Considered
NICE CXone
Other Software Used
Zendesk Talk, Nextiva Customer Relationship Suite, Talkdesk
Google cloud contact center AI- welcome to future world.
Use Cases and Deployment Scope
It is used for customer service under the ISNT function to resolve frequently occurring problems in day-to-day business life, that can be solved without an actual human being helping to solve them. Just pick out of listed problems and get the issue resolved. In case it doesn't help, it will automatically lead to some human expert in that case.
Pros
- Supporting numerous projects.
- Workload simultaneously.
- Shared infrastructure.
Cons
- Relatively fewer global data center than competition.
Return on Investment
- It helps in quick resolution of issues.
- It saves time and human efforts.
- It increases the reach.
Alternatives Considered
TensorFlow, IBM Watson Studio on Cloud Pak for Data and MATLAB
Other Software Used
Navisworks, Revit, MicroStation