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…
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Microsoft Azure
Score 8.5 out of 10
N/A
Microsoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.
$29
per month
Pricing
Google Cloud Contact Center AI
Microsoft Azure
Editions & Modules
No answers on this topic
Developer
$29
per month
Standard
$100
per month
Professional Direct
$1000
per month
Basic
Free
per month
Offerings
Pricing Offerings
Google Cloud Contact Center AI
Microsoft Azure
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
The free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
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Community Pulse
Google Cloud Contact Center AI
Microsoft Azure
Features
Google Cloud Contact Center AI
Microsoft Azure
Contact Center Software
Comparison of Contact Center Software features of Product A and Product B
Google Cloud Contact Center AI
8.4
12 Ratings
1% above category average
Microsoft Azure
-
Ratings
Agent dashboard
8.612 Ratings
00 Ratings
Validate callers
7.911 Ratings
00 Ratings
Outbound response
8.211 Ratings
00 Ratings
Call forwarding
8.610 Ratings
00 Ratings
Click-to-call (CTC)
8.911 Ratings
00 Ratings
Warm transfer
8.89 Ratings
00 Ratings
Predictive dialing
8.39 Ratings
00 Ratings
Interactive voice response
8.410 Ratings
00 Ratings
REST APIs
7.211 Ratings
00 Ratings
Call scripts
8.210 Ratings
00 Ratings
Call tracking
8.610 Ratings
00 Ratings
Multichannel integration
8.811 Ratings
00 Ratings
CRM software integration
8.711 Ratings
00 Ratings
Workforce Optimization (WFO)
Comparison of Workforce Optimization (WFO) features of Product A and Product B
Google Cloud Contact Center AI
8.6
12 Ratings
4% above category average
Microsoft Azure
-
Ratings
Inbound call routing
8.311 Ratings
00 Ratings
Omnichannel inbound routing
8.111 Ratings
00 Ratings
Recording
8.812 Ratings
00 Ratings
Quality management
8.911 Ratings
00 Ratings
Call analytics
9.111 Ratings
00 Ratings
Historical reporting
9.010 Ratings
00 Ratings
Live reporting
8.410 Ratings
00 Ratings
Customer surveys
8.18 Ratings
00 Ratings
Customer interaction analytics
8.49 Ratings
00 Ratings
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Well suited for sites where the product is hardware because with those if there are any questions then the site could help eliminate having to contact the company directly and waiting for answers days later. This would be suited for products as the answer could be given and the more complex questions would be directed to the company.
Azure is particularly well suited for enterprise environments with existing Microsoft investments, those that require robust compliance features, and organizations that need hybrid cloud capabilities that bridge on-premises and cloud infrastructure. In my opinion, Azure is less appropriate for cost-sensitive startups or small businesses without dedicated cloud expertise and scenarios requiring edge computing use cases with limited connectivity. Azure offers comprehensive solutions for most business needs but can feel like there is a higher learning curve than other cloud-based providers, depending on the product and use case.
Google Cloud Contact Center AI is based on the same foundation infrastructure and services as Google Assistant, therefore, it is robust and flexible. The APIs are very well built and documented as well. Any newbie can start using the service with a very little learning curve.
Seamless integrations are also a great add-on. Google makes sure that Contact Center AI service integrates well with leading customer service platforms which helps any user to use only the required functionalities from Contact Center AI and meanwhile use any other primary platform.
Robust documentation which is always alive and is updated within no time is of great help! Google makes sure its end customers know what to do where and when in clear plain text and any issues/ bugs are also documented.
Microsoft Azure is highly scalable and flexible. You can quickly scale up or down additional resources and computing power.
You have no longer upfront investments for hardware. You only pay for the use of your computing power, storage space, or services.
The uptime that can be achieved and guaranteed is very important for our company. This includes the rapid maintenance for security updates that are mostly carried out by Microsoft.
The wide range of capabilities of services that are possible in Microsoft Azure. You can practically put or create anything in Microsoft Azure.
The cost of resources is difficult to determine, technical documentation is frequently out of date, and documentation and mapping capabilities are lacking.
The documentation needs to be improved, and some advanced configuration options require research and experimentation.
Microsoft's licensing scheme is too complex for the average user, and Azure SQL syntax is too different from traditional SQL.
We are happy with the implementation and functionality of the software and associated systems. In general, unless something better can replace this system we intend on continuing. We think the ease of systems implementation and integration adds value and substantiates the use and excellent functionality of the product and associated services.
Moving to Azure was and still is an organizational strategy and not simply changing vendors. Our product roadmap revolved around Azure as we are in the business of humanitarian relief and Azure and Microsoft play an important part in quickly and efficiently serving all of the world. Migration and investment in Azure should be considered as an overall strategy of an organization and communicated companywide.
Generally intuitive and easy to learn. I would like more guides but the learning curve is rather quick and makes the software rather an easy study for the average user. Generally, the support and functionality of the software make for a generally good outcome and easy implementation of the software and user experience.
As Microsoft Azure is [doing a] really good with PaaS. The need of a market is to have [a] combo of PaaS and IaaS. While AWS is making [an] exceptionally well blend of both of them, Azure needs to work more on DevOps and Automation stuff. Apart from that, I would recommend Azure as a great platform for cloud services as scale.
We were running Windows Server and Active Directory, so [Microsoft] Azure was a seamless transition. We ran into a few, if any support issues, however, the availability of Microsoft Azure's support team was more than willing and able to guide us through the process. They even proposed solutions to issues we had not even thought of!
As I have mentioned before the issue with my Oracle Mismatch Version issues that have put a delay on moving one of my platforms will justify my 7 rating.
Only IBM Watson Assistant has been the one we have used in the company, in fact, it was the first to use it because currently in the market there are not many options to use, and if there are they are not receiving enough publicity, so we have limited ourselves to google cloud contact center AI.
As I continue to evaluate the "big three" cloud providers for our clients, I make the following distinctions, though this gap continues to close. AWS is more granular, and inherently powerful in the configuration options compared to [Microsoft] Azure. It is a "developer" platform for cloud. However, Azure PowerShell is helping close this gap. Google Cloud is the leading containerization platform, largely thanks to it building kubernetes from the ground up. Azure containerization is getting better at having the same storage/deployment options.
For about 2 years we didn't have to do anything with our production VMs, the system ran without a hitch, which meant our engineers could focus on features rather than infrastructure.
DNS management was very easy in Azure, which made it easy to upgrade our cluster with zero downtime.
Azure Web UI was easy to work with and navigate, which meant our senior engineers and DevOps team could work with Azure without formal training.