Dashbot, a conversational AI and data platform, launches today its proprietary Conversational Data Cloud, letting customers build and optimize their chatbots from their businesses’ conversational data.
The trademarked Conversational Data Cloud turns unstructured, noisy, interrelated and often tangled conversational data into immediate action.
Dashbot says that across the increasing number of communication channels (contact centers, support tickets, social media, IVR, live chat, etc), a business can receive up to 3 million customer messages per day. The pandemic has accelerated this flood of customer communications.
In addition, the complexity of human language makes it impossible to predict every way users will speak with bots. As a result, Dashbot says more than 50 percent of chatbot sessions fail. Optimizing existing bots can reduce the failure rate by up to 35 percent and reduce the escalation rate by up to 57 percent.
Dashbot’s Conversational Data Cloud enables businesses to:
- Centralize all conversational data including chatbot transcripts, Zendesk, email and live agent voice calls.
- Decipher tens of thousands of daily conversations and transcripts.
- Group similar messages and topics to determine areas of failure and opportunities for new use cases, leveraging its proprietary machine learning algorithms.
“We’re expanding beyond reporting and analytics to be able to ingest raw conversational data which can be difficult, but also very valuable for our customers,” said Andrew Hong, CEO of Dashbot. “We’re on a mission to decipher language, which is one of the most complex types of data that has ever existed. We listened to our customers that are challenged to make sense of all their conversational data, so we built our Conversational Data Cloud to help businesses automate, analyze and optimize their conversation channels.”
Dashbot’s Conversational Data Cloud is powered by three core features:
- Transcript Transformer – Ability to search and categorize thousands of daily transcripts
- DashbotML – Machine learning models hyper tuned from more than 10 billion conversations. Topic Modeling to visualize flow and conversation loops. Phrase clustering (message grouping) to identify new use cases and unhandled topics.
- Automated Training Data – Export messages as training data to optimize NLP model.
For more information on Dashbot, please visit www.dashbot.com.
