DevRev vs. Google Cloud Customer Experience Agent Studio (CX Agent Studio)

DevRev is well suited for both multi-team and single-team environments, and teams can realize meaningful value even without having product, engineering, and support all onboarded at the same time. Its strength is clearest when used by customer-facing and delivery-adjacent teams that benefit from shared context and tighter feedback loops. However, DevRev is less appropriate out of the box for teams that sit outside those core functions, as the platform’s terminology and workflows are opinionated toward product, engineering, and support use cases. Without deeper custom object support and greater flexibility in redefining terms and processes, it has been challenging to demonstrate value to those teams and to help them move away from established tools and ways of working.

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Indicated for those who have good knowledge of programming and coding in HTML and JSON, that is, it is not suitable for beginners or users without much technical knowledge. It is suitable for those who want to integrate with various platforms, such as Telegram, Webhat, Facebook Messenger, among others. I also recommend it to anyone who needs to create a chatbot in several languages (it is not automatic translation). Recommended to create new projects in CX environment and not in ES.

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• It provide AI assistance to our agents i.e. features like summarization of chat.
• It provides advanced workload management using ticket routing features.
• It helps in adding dispositions and is very DIY kind of software.
• It helps in providing advanced Analytics of tickets and dashboards.

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• Great at back-and-forth dialogue with the caller
• Integration with existing contact center plattforms
• Using the same flow for voice and chat seamlessly
• Very customizable

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• The onboarding experience could be improved for teams that are not directly implementing DevRev, as they are often introduced to a powerful platform without enough guided context and can feel overwhelmed early on.
• Creating and managing objects, dashboards, and other configurations would benefit from more robust desktop-based creation tools, as current workflows can feel constrained or unintuitive at scale. Use industry standard language and report building.
• While regressions are rarely critical, the frequency of small UI issues, such as broken date selectors or text visibility problems caused by theming, creates unnecessary friction and frustration for users.

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• Some of the features are still in beta phase.
• The languages available are still limited.
• The advanced features may not be accessible to new users.

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DevRev provides strong support through a dedicated key account manager and tech team, making the experience seamless. There might be hurdles, but they get resolved with team support. The tool is also very easy to use, with the user able to customize and use various features as needed.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Users benefit from Dialogflow's best User Interface and seamless User Experience. It's very scalable, and there are a lot of customization options to make it even more so. Dialogflow makes it simple to deploy, manage, and maintain chatbots. Artificial Intelligence algorithms make chatbots interactive, making it easier for users and chatbots to communicate and understand each other. Overall, it's a good option for those with little programming experience who want to learn Natural Language Processing.

I'm not aware of DevRev not being available in our two years using the product. The software and support team is available around the clock.

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I have no functionality, reliability, or speed concerns with DevRev. In the past, we raised a few latency issues that were fixed within days by the engineering team. The DevRev team were incredibly thankful for these being raised.

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Dialogflow is a wonderful tool that is helping to design customized chatbots. I personally recommend if you wanna know how it's works give it a try with a free APIs call, you'll love this tool

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While Freshdesk and Kapture are great tools, they lack advanced features such as agent assist and AI summarisation. Dedicated support at these companies also becomes an issue, as no dedicated team is allotted due to frequent changes. Also, these tools are not DIY kind and require external help for use and excellence.

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There is always use cases for both. We still use the other plattforms but each has its own strengths and weaknesses. We, as a contact center implementation partner always use multiple solutions both for ourselves but also for our customers to meet their needs. In the cases we choose Google Cloud Dialogflow is when we need to be able to handle specific follow-up questions from the customer. And for more complicated issues we also use a combination of this and other 3rd party plattforms. We always meet the need of our customers and as specialist and consultants we give expert advice on how to use all these different solutions in the best way possible.

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DevRev is incredibly flexible - while we started with a support and product move to the tool - Engineering, Finance, People, and our Account Management team quickly followed. The best part about these teams being in DevRev is tying everything back to the customer and being able to build intuitive, flexible workflows for any need.

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• It helped in reduction of agent count by 5 resulting in 20% cost savings.
• It reduced our average customer ticket resolution time by 50%.
• It helped improved our net promoter score by 5 bps.

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• As a partner to multiple contact center plattforms we have always been able to offer Google Cloud Dialogflow along with them because it integrates well with all.
• Many businesses want to implement smart ways to have call deflection. Bots that can handle full dialogues with the customer is very intriguing to them because it can fulfill customers requests without using up as many resources

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info