Composite entities are a type of entity in Dialogflow that is a combination of multiple different entities. For example, if you build an agent with the “Size” and “Item” entities, you will create an order_item entity that is a composite of both of those.
Both “@size @item” or “@item @size” would be part of your order_item entity. This allows for different permutations and combinations in speech and allows our bot to recognize both “Large Coca-Cola” and “Coca-Cola large.”
Using this composite entity structure we can stitch entities together and allow the bot to in a sense “learn” the menu and listen for those items.
Another key feature in Dialogflow CX, which shines in verticals like QSR and healthcare, is Auto Speech Adaptation. Auto Speech Adaptation is a feature in Dialogflow that automatically uses the conversation state to pass relevant entities and training phrases over to the Speech-to-Text (STT) engine as context for the transcription. This enables the STT engine to favor use case-specific words like the entities it is expecting in that state of the conversation and tremendously helps improve transcription. For QSR use cases where the bot is extracting menu items from the users’ utterances, this becomes necessary, especially for menu items unique to that restaurant chain.
Custom Voice is one of the most recent and fun features that Google has added. Custom Voice lets you define your brand and engage with your customers through voice. Google allows you to build custom voice models that can be a fun way to improve customer experience and showcase or define a voice behind the brand.
Another feature is Automated Test Cases, through which Dialogflow CX allows developers to convert conversations into test cases that can be run via APIs. This gives the product team a robust set of tests that can cover all the different conversations the bot is expected to support. This in turn gives us the confidence to release the bot and continue iterating on it, knowing there are quick tests available to ensure backward compatibility.
A/B Testing: The Google Dialogflow CX team also released a neat A/B testing feature that allows you to version the agent at different states and split the traffic going to each state to test the performance for any changes. It is a great way to reduce the impact of any large changes to the agent.
Personally Identifiable Information (PII) redaction gives us the ability to keep PII data redacted in logs to ensure that any customer information is secure.
Dual-Tone Multi Frequency (DTMF) inputs are integrated with Dialogflow CX for voice agents. This gives the user multiple options to enter the desired information. When collecting numbers, it is often easier to let the customer type the keys into their phone instead of saying it out. This DTMF support is often leveraged when verifying a customer’s identity, either with the last four digits of their social or phone number. Such sensitive information is better typed out, especially if the user is in a public space.