Google launched DialogFlow CX for customer service use that includes pre-built bots for verticals such as telecommunications, financial services, healthcare, retail and travel.
Included in Google DialogFlow CX is support for 20 languages for each agent, support for up to 40,000 “intents,” or types of statements a customer or employee might ask during the course of a conversation, and support for virtual private cloud services that connect bots to on-premises applications such as ERP and CRM systems.
At most enterprises, the contact center is the “center of gravity” for such natural language understanding AI and machine learning technologies, said Opus Research founder Dan Miller. But as users develop and train their own instances of Google DialogFlow and its AWS counterparts to assist both their customers and agents — and they prove effective in solving problems — they will ultimately find utility across the enterprise as replacements for rudimentary answerbots that act as glorified knowledgebase search tools.
“We’ll see tens of thousands of implementations that are indifferent to whether it’s in the contact center, or sort of front-ending an enterprise search service where an employee can find things,” Miller said. “Google, of all companies, can recognize the power of search.”
Google DialogFlow users also rely on AI-powered sentiment analysis tools during conversations to determine if bot conversations are effective or if they’re off-target to the point of frustrating users, a Google spokesperson said in an email. Hundreds of Google users employ sentiment analysis on a daily basis to improve their virtual agent designs.
Like competitor AWS, Google forged partnerships with several leading contact center telephony vendors, such as Genesys and Avaya, to integrate their bots into Google’s systems. While AWS might have more cloud users in general, DialogFlow for now is probably the leading contact center bot-building platform when judging by Avaya customer interest and preferences, said Eric Rossman, Avaya VP of technology partners and alliances.
In part, that’s because Google had a year’s lead and caught on with developers, Miller said. Google’s strategy differs from AWS, too, in that Amazon Connect competes directly with some of its partners that sell their own contact center platforms, while Google doesn’t offer its own platform — choosing instead to focus on cloud microservices that extend other companies’ contact center platforms.
“There was a head start for DialogFlow, and companies tend to move in packs as they see things,” Miller said. “They got the early lead, which coincided with a lot of pilots and proof of concepts for chatbots and voicebots.”
Competition for the technology buyer’s budget is heating up between AWS and Google, with several other companies such as Microsoft, Nuance and smaller contact center-specific AI vendors enjoined in the fray.
Google DialogFlow CX costs $20 or $45 per 100 chat/voice sessions, depending on configuration; AWS Contact Center Intelligence pricing and regional availability depends upon combination of services used including Amazon Comprehend, Kendra, Lex, Transcribe, Translate and Polly.
This article originally appeared in TechTarget.
