Google Cloud Contact Center AI vs. Microsoft Azure

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud Contact Center AI
Score 7.0 out of 10
N/A
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…N/A
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 AIMicrosoft 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 AIMicrosoft Azure
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsThe free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
More Pricing Information
Community Pulse
Google Cloud Contact Center AIMicrosoft Azure
Features
Google Cloud Contact Center AIMicrosoft Azure
Contact Center Software
Comparison of Contact Center Software features of Product A and Product B
Google Cloud Contact Center AI
8.4
Ratings
1% above category average
Microsoft Azure
-
Ratings
Agent dashboard8.50 Ratings00 Ratings
Validate callers7.90 Ratings00 Ratings
Outbound response8.20 Ratings00 Ratings
Call forwarding8.60 Ratings00 Ratings
Click-to-call (CTC)8.90 Ratings00 Ratings
Warm transfer8.80 Ratings00 Ratings
Predictive dialing8.30 Ratings00 Ratings
Interactive voice response8.40 Ratings00 Ratings
REST APIs7.20 Ratings00 Ratings
Call scripts8.10 Ratings00 Ratings
Call tracking8.40 Ratings00 Ratings
Multichannel integration8.70 Ratings00 Ratings
CRM software integration8.70 Ratings00 Ratings
Workforce Optimization (WFO)
Comparison of Workforce Optimization (WFO) features of Product A and Product B
Google Cloud Contact Center AI
8.5
Ratings
3% above category average
Microsoft Azure
-
Ratings
Inbound call routing8.30 Ratings00 Ratings
Omnichannel inbound routing8.10 Ratings00 Ratings
Recording8.80 Ratings00 Ratings
Quality management8.90 Ratings00 Ratings
Call analytics9.00 Ratings00 Ratings
Historical reporting9.00 Ratings00 Ratings
Live reporting8.40 Ratings00 Ratings
Customer surveys8.10 Ratings00 Ratings
Customer interaction analytics8.40 Ratings00 Ratings
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Google Cloud Contact Center AI
-
Ratings
Microsoft Azure
8.5
Ratings
6% above category average
Service-level Agreement (SLA) uptime00 Ratings9.00 Ratings
Dynamic scaling00 Ratings8.00 Ratings
Elastic load balancing00 Ratings9.00 Ratings
Pre-configured templates00 Ratings8.00 Ratings
Monitoring tools00 Ratings8.40 Ratings
Pre-defined machine images00 Ratings8.00 Ratings
Operating system support00 Ratings8.90 Ratings
Security controls00 Ratings9.00 Ratings
Automation00 Ratings8.00 Ratings
User Ratings
Google Cloud Contact Center AIMicrosoft Azure
Likelihood to Recommend
8.5
(0 ratings)
8.9
(0 ratings)
Likelihood to Renew
9.0
(0 ratings)
10.0
(0 ratings)
Usability
9.0
(0 ratings)
9.4
(0 ratings)
Availability
-
(0 ratings)
6.8
(0 ratings)
Support Rating
-
(0 ratings)
8.0
(0 ratings)
Implementation Rating
-
(0 ratings)
8.0
(0 ratings)
User Testimonials
Google Cloud Contact Center AIMicrosoft Azure
Likelihood to Recommend
In a specific scenario in which I would not recommend it, it would be in a hospital, since the level of margin of error must be minimal, human lives are at risk and can cost dearly if Google cloud contact center AI fails, in the scenario in which I would recommend it, it would be in that of a legal company
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Actually, migrating to Microsoft Azure is a good solution for almost any situation, especially when all components of your network are ready to become cloud-based. The only drawback I personally encounter frequently is that older software packages cannot always be easily picked up and moved to Microsoft Azure in an optimal manner.
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Pros
  • 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.
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  • Azure simply provides end to end life cycle. Starting from the development to automated deployment, you will find [a] bunch of options. Custom hook-points allow [integration] on-premise resources as well.
  • Excellent documentation around all the services make it really easy for any novice. Overall support by [the] community and Azure Technical team is exceptional.
  • BOT Services, Computer Vision services, ML frameworks provide excellent results as compare to similar services provided by other giants in the same space.
  • Azure data services provide excellent support to ingest data from different sources, ETL, and consumption of data for BI purpose.
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Cons
  • It's still in the beginning phase of sentimental Analysis and more data sets can really help during tough conversations.
  • Automation can be made a little simpler and basic for anyone to be able to work on it.
  • Each instance of the software can have its own AI learning for a wider range of real time issues.
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  • In our experience, Azure Kubernetes Survice was difficult to set up, which is why we used Kubernetes on top of VMs.
  • Azure REST API is a bit difficult to use, which made it difficult for us to automate our interactions with Azure.
  • Azure's Web UI does a good job of showing metrics on individual VMs, but it would be great if there was a way to show certain metrics from multiple VMs on one dashboard. For example, hard drive usage on our database VMs.
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Likelihood to Renew
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.
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We have been very satisfied with Windows Azure and now a lot of our business depends on it as more teams are now deploying their applications into Azure. Our next step is to have our Infrastructure team move their resources to Azure. It will take awhile for that to happen but we are positive that it will.
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Usability
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.
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Microsoft Azure's overall usability has been better than expected. Often times vendors promise the world, only to leave you with a run-down town. Not the case with our experience. From an implementation perspective, all went perfect, and from the user-facing experience we have had no technical issues, just some learning curve issues that are more about "why" than "how"
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Reliability and Availability
No answers on this topic
It has proven to be unreliable in our production environment and services become unavailable without proper notification to system administrators
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Support Rating
No answers on this topic
Support is easy with all the knowledge base articles available for free on the web. Plus, if you have a preferred status you can leverage their concierge support to get rapid response. Sometimes they’ll bounce you around a lot to get you to the right person, but they are quite responsive (especially when you are paying for the service). Many of the older Microsoft skills are also transferable from old-school on-prem to Azure-based virtual interfaces.
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Implementation Rating
No answers on this topic
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.
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Alternatives Considered
Google is a known product that many have used and we didn't see any other competitors having the edge that they do in their products. This is seen in their customer service when it comes to learning how to use the product and they have the resources to self-learn it.
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I feel that Microsoft Azure typically outperforms Google Cloud Platform in hybrid cloud capabilities, integration aspects, and, primarily, security compliance features. Azure offered superior integration with Microsoft's enterprise software ecosystem, and it's second to none in my opinion. This made it the natural choice for most, especially if heavily invested in Windows, Office 365, or Active Directory deployments. We chose Azure over GCP because we simply needed Windows workload support as a strong driver, more access to global regions, and let's not forget that most tech teams in an organization are Microsoft Certified, which makes skillset transfer from on-prem to cloud a minimal learning curve over shifting to a different provider.
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Return on Investment
  • Reduced the number of minutes spent by live agents on trivial queries.
  • Our client saved thousands of dollars by using the AI contact center as now the agents spend most of their time solving real issues.
  • Customer satisfaction got increased exponentially.
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  • Times and growth went into it. By balancing on-premises maintenance with continuous cloud improvements, we’ve budgeted and planned endlessly increased capacity.
  • In today’s world of cyber-crime, clients can put even more faith in what they’ve heard. We built an innovative single-sign-on hub for all users. Also, other business platforms use Azure application gateways, reducing worker switching time and increasing productivity.
  • Its step can automate to improve the investment. In addition, we can integrate our organization’s credentials into an authorization for other systems.
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ScreenShots